We are proud to announce the release of LANSA BI 9.16.1.1, bringing GenAI-powered enhancements to your business intelligence workflow.

With this update, you can now connect LANSA BI with the latest AI Model of choice to further simplify insights generation and accelerate decision-making for all users in your organization. Whether you’re working with Anthropic Claude, Google Gemini, Azure OpenAI or other Open AI models, this release comes with robust governance controls to help you manage security, usage, performance, and costs.

What’s New

Read on to explore how LANSA BI 9.16.1.1 supports faster data exploration, analysis, and presentation. All updates translate into embedded experiences, which means that you can deliver instant insights to your Visual LANSA application users, and they can immediately use them to make smarter business decisions.

AI-Enabled NLQ

First off, LANSA BI 9.16.1.1 brings AI-enabled NLQ, making it easier than ever for non-coders to get accurate answers from their data. With this, users don’t even need to learn Guided NLQ syntax rules to ask the platform for specific information. Just ask questions as you would in a human conversation, and the AI will translate them into structured queries. Users also don’t need to master all data columns to request insights, making this especially useful for new and non-technical users.

AI mode can be easily toggled on or off when querying data. With this update, users also get Suggested Questions to assist with data exploration. The AI automatically generates a list based on the metadata of the underlying dataset. Results can then be saved as reusable reports, added to dashboards, or inserted into data stories.

AI-Driven Insights with “Tell Me About My Data”

Next, LANSA BI 9.16.1.1 upgrades AI-assisted insights generation with Tell Me About My Data (TMAMD) which doesn’t just add GenAI narratives but also brings recommended charts to support deeper analysis. You can use this new capability when building reports, dashboards, and data stories — just look for this icon to get started.

This update generates plain language explanations to help understand trends, anomalies, and key drivers. Depending on your configuration, it can also compare and analyze data against a broader set for richer insights.

The AI-recommended visualizations will be rendered in LANSA BI as reusable and interactive charts. This significantly reduces the manual work required to create reports, variations, and presentations, allowing users to focus on analysis, collaboration, and decision-making.

With respect to governance, LANSA BI has built-in machine learning that analyzes the data before sending summaries to the external AI model. Detailed dataset records are not transmitted, and administrators can also enable or disable this feature with role-based settings.

AI Story Assistant

TMAMD is deeply integrated with LANSA BI’s built-in Data Storytelling Tool, enabling users to create multimedia narratives more quickly.

With the AI Story Assistant, users managing frequent updates can rely on the AI-generated visualizations and explanations to get their content started. They can then focus on distilling what matters most: actionable insights and value-driven recommendations.

Reminder: LANSA BI 9.16.1.1 is designed to enable faster discovery of insights without compromising control. When using the above AI-powered features, metadata such as column names, view descriptions, data types, and reference codes may be sent to the AI model together with the user’s question. Access can also be controlled by role, providing fine-grained governance over which users can use the feature.

AI Model Preference, Usage Tracking and Cost Governance

With the AI model integration, we are able to deliver a friendlier BI experience dedicated to accelerating insight discovery and decision-making. To support enterprise governance, LANSA BI 9.16.1.1 also comes with advanced auditing capabilities for AI usage.

Providing administrators with visibility to manage operational efficiency and compliance, they can:

• Easily connect to OpenAI, Claude, Gemini or Azure models (Bring Your Own Provider)
• Choose model versions to balance performance, speed, and cost
• Define AI connections at the Client Organisation (tenant) level
• Monitor accumulated token usage per connection
• View recent usage summaries in the Admin console
• Drill into individual AI requests
• Review exactly what was sent to and received from the model
• Analyze usage by tenant, model, feature type, or date

Additional Updates

Automated Tomcat Upgrades

The updater can now optionally upgrade the bundled Tomcat version automatically during system updates.

This reduces manual maintenance effort and helps ensure deployments stay aligned with current security standards. Silent installer support and safeguards protect custom configurations.

Expanded Data Connectivity

LANSA BI 9.16.1.1 expands reporting source support, including:

• Certified connectivity for ClickHouse
• Certified connectivity for StarRocks
• Snowflake support using public/private key authentication

These additions provide more flexibility across modern data ecosystems.

Reporting and Charting Enhancements

This release continues to improve performance and authoring flexibility.

Performance Improvements

• Ability to push sorting operations to the database using ORDER BY
• Better handling of row limits and large datasets

Enhanced Chart Configuration

• Configure colour for “Other” category segments
• Add additional tooltip fields to Ring and Pie charts
• Disable brush filtering where required
• Configure colour behaviour for Percentage Bar formatting
• Additional micro-configuration improvements

Authoring Improvements

• Use Reference Codes as parameter value lists
• Create new content folders directly when publishing reports
• Drill from reports to dashboards when embedded inside Stories

These improvements enhance control for report authors and embedded deployments.

Export and Integration Enhancements

Further enhancements include:

• Filter placeholders in custom export filenames
• Improved export behaviour for embedded content
• Extended JavaScript API with additional export configuration control
• Ability to purge historic Signals data to help manage repository size

These updates support embedded applications and operational efficiency.

Why Upgrade to LANSA BI 9.16.1.1

AI-powered insight generation within dashboards

Enable users to move beyond static reporting. With Tell Me About My Data, business users can instantly generate narrative explanations and recommended charts from any report or dashboard component. This accelerates insight discovery, reduces reliance on specialist analysts, and shortens the time from data to decision.

AI model flexibility and tenant-level control

Choose the AI model that best fits your organisation’s needs, balancing cost, performance, and response quality. Define AI connections per Client Organisation (tenant), supporting multi-tenant deployments and “bring your own model” strategies without compromising architectural control.

Full AI usage auditing and cost governance

Gain visibility into AI consumption with detailed token tracking and drill-down request auditing. Monitor usage by connection, tenant, model, and feature type. This supports cost optimisation, compliance requirements, and enterprise-level governance of AI workloads.

Reduced administration with automated upgrades

Optional automated Tomcat upgrades during system updates eliminate manual maintenance steps and reduce exposure to security risks. This simplifies lifecycle management and helps keep environments aligned with supported platform components.

Broader database connectivity

Expanded certified data source support, including modern analytics platforms, provides greater deployment flexibility and enables integration with evolving enterprise data strategies.

Continued seamless integration with Visual LANSA

LANSA BI 9.16.1.1 preserves the existing two-part architecture, including the ready-to-use Visual LANSA integration components. No redesign is required — simply upgrade and continue embedding dashboards, reports, and AI capabilities in your applications.

Enterprise-ready deployment on IBM i and Windows

Maintain full compatibility with IBM i and Windows environments, supporting hybrid and cross-platform deployments. LANSA BI continues to provide a stable, scalable analytics foundation aligned with enterprise infrastructure standards.

How to Install LANSA BI 9.16.1.1?

LANSA BI 9.16.1.1 is compatible with IBM i and Windows environments. It can be used as a stand-alone BI solution or an embedded analytics layer to Visual LANSA applications.

The packages comprises of two parts:

• LANSA BI software
• Visual LANSA file with sample API integration (simply input your LANSA BI credentials to start embedding dashboards and reports)

Existing users may download the latest LANSA BI version from the LANSA Support Portal and follow the included installation guide for your platform.

For detailed guidance on using LANSA BI, visit docs.lansa.com and select “LANSA BI” from the Integration section in the main menu.

Powered by Yellowfin 9.16.1.1 you may also refer to the complete release notes — including all bug fixes, new features, and enhancements here.

Not Yet a LANSA BI User?

LANSA BI is an AI-powered business intelligence solution primarily designed to support digital transformation projects on IBM i and Windows. Whether you’re starting from scratch or replacing legacy reporting tools, LANSA BI’s intuitive platform and comprehensive features can help you deliver actionable analytics directly to decision-makers.

Watch this webinar for an overview: Delivering Enterprise Analytics Your End-Users Will Love with LANSA BI

Consult with our experts to discuss your business intelligence requirements for free. We would be happy to provide a product tour based on your needs and start a proof of concept (POC) to visualize a sample dataset for your evaluation.

A LANSA BI sandbox is available for you and your team to experience AI-powered self-service analytics firsthand before taking the leap. Contact us now to get started.

The post LANSA BI 9.16.1.1: Friendlier, Smarter, Embedded Analytics with GenAI and Stronger Governance appeared first on LANSA.

What Is Natural Language Query (NLQ)?

Natural Language Query (NLQ) is a business intelligence technology that allows users to ask questions in simple, everyday language and receive quick insights from their data. Instead of writing SQL (Structured Query Language) or navigating complex dashboards, users can directly type a question like, “Show me monthly revenue trends,” and get immediate answers. As a result, many analytics barriers disappear. Teams can explore data and make decisions with less effort.

Watch how it works: LANSA BI – Natural Language Query – 5 Minute Demo

Today’s NLQ systems are also far more advanced than early keyword-based tools. Thanks to advancements in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Natural Language Understanding (NLU), and Large Language Models (LLMs), modern NLQ tools now understand both intent and context, rather than relying solely on exact keywords.^[1] Consequently, these systems can interpret complex questions, map them to the right fields, and generate accurate results. Because of these capabilities, NLQ has become a core part of self-service analytics, helping more users work confidently with data.

In addition, Natural Language Queries are now integrated into many BI environments to support everyday tasks, reduce analyst workloads, and expedite reporting cycles. As data ecosystems become increasingly complex, NLQ offers a simpler and more intuitive way for users to interact with large datasets.

Related article: How to Integrate BI into IBM i Applications

Benefits of NLQ: Why Is Natural Language Querying Important

Natural Language Querying is important because it removes long-standing barriers that prevent business users from accessing and understanding data. By simplifying how stakeholders interact with analytics systems, NLQ helps organizations move faster, reduce reliance on technical teams, and make data-driven decisions more accessible across the business.

1. Enables Self-Service Analytics
   Non-technical users can explore data independently without needing to learn SQL or understand complex database structures. This reduces repetitive requests to analysts and IT teams and allows technical resources to focus on more specialized, high-value work.
2. Expands BI Adoption
   Natural Language Query feels familiar because it works like search engines and chat-based programs. This familiarity helps users overcome intimidation and confusion when faced with overwhelming data or complex technology.
3. Accelerates Insights
   Users can review data-backed answers in seconds instead of waiting hours or days for BI reporting. Faster access to information helps decision-makers across departments — including operations, finance, sales, and marketing — respond more quickly to emerging issues or opportunities. These insights support better performance, operational efficiency, customer satisfaction, and competitive agility.

Overall, NLQ helps organizations build a stronger data culture, with employees becoming more confident in using data and applying insights to their daily work.

How Does NLQ Support Business Intelligence

Natural Language Query introduces a simpler way to extract business intelligence. Instead of relying only on predefined dashboards or static reports, users can ask questions and immediately generate visual results from the available data. This allows decision-makers to investigate performance metrics, explore trends, and analyze specific business dimensions such as regions, time periods, or product lines without waiting for new reports to be created.

In AI-powered BI environments, NLQ works alongside automated analytics that continuously analyze data for patterns, anomalies, and emerging trends. When the system identifies unusual activity or notable changes, users can investigate the underlying drivers by asking targeted questions about the data. AI capabilities can also analyze the results of NLQ queries to highlight key contributors, explain changes in performance, or summarize important findings that support faster and more informed decisions.

LANSA BI supports all of these capabilities and allows NLQ to be embedded directly into existing business applications. This enables decision-makers to access data and insights within the systems they already use to manage operations. Visualizations generated from NLQ queries can be added to a business intelligence dashboard to monitor key metrics or incorporated into data stories to provide narrative context around trends.

Related article: How to Get Real-Time Insights with LANSA BI

How Does NLQ Help Analytics Users

Natural Language Querying simplifies several technical steps that traditionally exist between a user and the data they want to analyze. In conventional BI workflows, retrieving an answer often requires locating the correct dataset, selecting the appropriate metrics and dimensions, defining filters, and structuring a query before results can be visualized.^[2] NLQ automates much of this process. The system interprets the user’s question, maps the request to the relevant fields in the data model, constructs the query, and returns the results as charts or tables.

For operational users, NLQ removes the need to navigate complex data models or understand how metrics are structured within the analytics system. Instead of selecting measures, defining grouping logic, and configuring filters, users can describe the information they need using business terms. The system translates that request into the underlying query logic and generates the visualization automatically.

For analysts, NLQ simplifies the process of retrieving and validating data during exploratory analysis. Analysts can quickly test questions, review different aggregations, or examine specific segments without manually writing queries or rebuilding visualizations. This allows them to move faster during early stages of analysis and focus their efforts on deeper investigation, modeling, and interpretation.

For executives and decision-makers, NLQ reduces the steps required to access specific performance indicators. Rather than navigating multiple dashboards or requesting new reports, leaders can directly query the data to review metrics, investigate trends, or examine changes across business dimensions.

By automating query construction, metric selection, and visualization generation, NLQ reduces the technical steps involved in accessing business intelligence while still allowing users to interact directly with enterprise data.

What are the Differences Between NLQ, NLP, and NLU?

Although these terms are often used together in discussions about AI-powered analytics, they refer to different technologies that work at different stages of language processing.

Natural Language Processing (NLP) is the broad field of artificial intelligence that enables computers to process and analyze human language. It includes techniques for breaking down text, identifying grammar and sentence structure, recognizing keywords, and processing language input in a way machines can understand. NLP forms the technical foundation for many language-based technologies, including chatbots, translation tools, and voice assistants.

Natural Language Understanding (NLU) is a specialized area within NLP that focuses on interpreting meaning and intent. While NLP processes the structure of language, NLU attempts to determine what the user actually means. It analyzes context, relationships between words, and business terminology to interpret a user’s request accurately. In analytics systems, NLU helps determine which metrics, dimensions, or datasets a user is referring to when asking a questions.

Natural Language Querying (NLQ) applies these technologies within business intelligence systems. It allows users to ask questions about their data using everyday language and receive results from analytics datasets. NLQ relies on NLP to process the language input and NLU to interpret the user’s intent, then translates the request into a structured query that retrieves the appropriate data. In this way, NLQ serves as the user-facing capability that makes conversational data access possible within BI platforms.

Types of Natural Language Queries — What are the Types of NLQ

Natural Language Queries can be implemented in several ways, depending on how the BI platform interprets user questions and guides data exploration. The three most common approaches are search-based NLQ, guided NLQ, and AI-driven NLQ.

• Search-Based NLQ  – allows users to type questions into a search bar that matches keywords with elements in the underlying database. Many BI platforms include this type of NLQ directly in their user interface, enabling users to enter a question and receive a quick answer based on the available data.However, capabilities vary widely between systems. Some platforms support only a limited set of keywords or data types, while others may restrict the volume or complexity of data that can be queried. In addition, search-based NLQ tools often provide little guidance on how to structure queries, which can make it difficult for users to know what questions the system will understand.
• Guided NLQ –  helps users construct more accurate queries by offering structured options that align with the platform’s data model and business rules. Instead of relying entirely on free-text input, the system presents selectable prompts that guide users step by step.For example, a user looking for information about customers in a particular area might begin by selecting “Customers.” The system may then present follow-up options such as “living within,” “onboarded before,” “onboarded after,” or “doing business with us for.” After choosing “living within,” the system may provide additional categories, such as geographic ranges or predefined customer segments. By guiding the query process, this approach helps users ask more precise questions and retrieve relevant insights.

Related article: Extracting Insights with Guided NLQ

• AI-Driven NLQ – uses artificial intelligence to interpret questions written in everyday language. Rather than relying solely on keywords or predefined prompts, the system analyzes the full meaning of the question to determine what the user wants to know. A user can ask a detailed question without understanding how the data is structured, and the system will identify the intent, generate the appropriate query, and return the results automatically. AI-powered NLQ can also recommend follow-up questions, explain results in simple terms, and guide users through deeper data exploration. Because it can interpret longer and more conversational questions, this approach supports a broader range of analytics users—from experienced analysts to occasional business users—while making data exploration more accessible across the organization.

What are Some Examples & Applications of Natural Language Queries?

Natural Language Query can support many industries and use cases, including:

Healthcare
In healthcare, clinicians can ask questions like, “Show patient admissions by risk category.” They can also explore trends in length of stay, treatment outcomes, or daily patient volume. With NLQ, they no longer need to open multiple dashboards or run manual reports. Instead, they receive clear answers in seconds, which helps them make faster and more informed decisions about patient care.

Retail
Retail teams can explore purchasing patterns, stock levels, and seasonal trends. They can also check which products sell the fastest, which items are running low, and which promotions perform well. With NLQ, they get these insights without digging through long dashboards. As a result, planning and forecasting improve when data is updated regularly.

Financial Services
In financial services, analysts can spot fraud indicators or review credit risk. With NLQ, they can also check transaction patterns, customer behavior, and unusual account activity in seconds. This gives them faster and clearer insights, which helps speed up risk evaluation processes and strengthens overall compliance.

Manufacturing
Manufacturing teams can track production delays, monitor equipment issues, and review output through simple Natural Language Queries. As a result, they gain quicker visibility into operational performance and can respond to issues before they affect output.

Education Platforms
Education administrators can track enrollment numbers, monitor learning progress, and review performance results with NLQ. This gives them quick access to key metrics without digging through multiple systems or spreadsheets. As a result, they spend less time on manual reporting and more time improving learning outcomes.

The Challenges of Natural Language Query Adoption

While Natural Language Query has advanced significantly, organizations may still face several challenges when adopting the technology.

1. Complex Query Handling
   Some NLQ systems still struggle with complex or layered questions. When phrasing is unclear or multiple conditions are combined, older tools may misinterpret the request. This can lead to incomplete, misleading, or inaccurate results.
2. Data Modeling and Storage Limitations
   NLQ performs best when the underlying data is clean, structured, and well-modeled. However, many organizations still operate with fragmented datasets or outdated data models. When data structures are inconsistent, the system may return confusing or incorrect answers. As a result, strong data modeling remains a critical requirement for reliable NLQ performance.
3. Transparency and Trust
   Users often want to understand how an NLQ system interpreted their question. When the logic behind the result is not visible, confidence in the output may decrease. Small changes in phrasing can also produce different results, which can create uncertainty for users who rely on the data for decision-making.
4. User Resistance and Habits
   For users who are accustomed to traditional dashboards or manual SQL queries, adopting NLQ can initially feel unfamiliar. However, with proper training and experience, many users recognize that NLQ can accelerate analysis and reduce repetitive reporting tasks.

What is LANSA BI and How Can it Benefit Your Business?

LANSA BI is a business intelligence platform that helps organizations process data, uncover insights, and analyze results for day-to-day operations and decision making. It enables teams to explore business performance, identify trends, and communicate findings through clear visual outputs. The platform includes built-in Natural Language Queries (NLQ), along with interactive dashboards, data stories, assisted insight generation, and BI automation that simplify how insights are generated and shared across the business.

LANSA BI connects to data from a wide range of enterprise systems, allowing organizations to bring information from different sources into a single analytics environment. It also supports embedded analytics within applications, including those running on IBM i, enabling insights to appear directly inside operational systems where work takes place. This flexibility makes the platform suitable for organizations across many industries, whether they are replacing legacy reporting tools with a modern analytics platform or implementing business intelligence capabilities for the first time. LANSA’s BI experts also support customers with legacy report migration and overall analytics delivery to ensure timely and successful implementation.

Related article: JDBC-Based Db2 Integration from LANSA

Final Words

Natural Language Query is changing how organizations interact with their data. By allowing users to ask questions in plain language and receive immediate answers, NLQ removes many of the technical steps that once made analytics difficult to access. As businesses generate larger volumes of data and decision cycles accelerate, tools that simplify data exploration become increasingly important. Platforms that combine NLQ with modern analytics capabilities give teams a practical way to investigate performance, uncover trends, and turn information into action more efficiently.

Organizations interested in exploring these capabilities further can see how NLQ works in practice through LANSA BI. Contact us for a private demonstration or book a free consultation with our experts about your business intelligence requirements.

References
[1] “How does an LLM handle ambiguous or multi-purpose tools? | Milvus.”
https://milvus.io/ai-quick-reference/how-does-an-llm-handle-ambiguous-or-multipurpose-tools

[2] “The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling | Ralph Kimball & Margy Ross.”
https://ia801609.us.archive.org/14/items/the-data-warehouse-toolkit-kimball/The%20Data%20Warehouse%20Toolkit%20-%20Kimball.pdf

[3] “Natural Language Processing (Computer Science) | Britannica.”
https://www.britannica.com/technology/natural-language-processing-computer-science

[4] “Natural Language Processing (NLP) | IBM.”
https://www.ibm.com/think/topics/natural-language-processing

[5] “Natural Language Understanding (NLU) | IBM.”
https://www.ibm.com/think/topics/natural-language-understanding

The post What is Natural Language Querying (NLQ)? An In-Depth Guide appeared first on LANSA.

LANSA Integrator helps developers deliver these integrated and automated workflows by managing the critical connections between Visual LANSA applications and external systems, including secure email communications. With the new EPC150058 release, those communications get a security upgrade: built-in OAuth 2.0 authentication for SMTP, POP3, and IMAP email services.

Jump to more details: What’s new in LANSA Integrator EPC150058.

This enhancement replaces or complements older Basic Authentication methods with modern, token-based security — ensuring your automated email workflows stay secure, compliant, and ready for the future.

Why OAuth 2.0 Authentication Matters

OAuth 2.0 uses short-lived, scoped tokens that grant access without exposing long-lived credentials, significantly reducing the risk of credential theft. As the industry shifts away from Basic Auth (static username/password authentication) for email services, LANSA Integrator 150058 helps make the transition simple and sustainable. Fully compatible with Microsoft 365, it aligns LANSA applications with modern security standards and evolving provider requirements.

What’s New in LANSA Integrator EPC150058

OAuth 2.0 Authentication is now available in:

• SMTPMailService – Send emails with support for attachments, encryption, and flexible configuration options — now with OAuth 2.0 authentication.
• POP3MailService – Securely receive and process messages using token-based authentication via POP3.
• IMAPMailService (NEW) – Access and manage mailboxes with robust IMAP functionality using OAuth 2.0 tokens.
• SMTPMailAttachmentSignatureService – Send digitally signed emails with attachments securely through token-based authentication.

With OAuth 2.0 built directly into LANSA Integrator’s email services, you can upgrade to a more secure authentication method and keep automated processes running smoothly.

Update to Integrator EPC150058 Now

Simply download LANSA Integrator EPC150058 from the Support Portal and refer to the documentation for guidance on IMAPMailService, POP3MailService, SMTPMailService, and SMTPMailAttachmentSignatureService. Remember, you can always chat with our AI Assistant for help —  it’s available 24/7!

Note: Support for OAuth 2.0 is also available by default in Visual LANSA 16. Contact your Account Manager to explore your upgrade options while limited-time offers are still available.

Just Getting Started?

LANSA Integrator works with Visual LANSA to streamline your development stack and accelerate the delivery of custom business applications. Build to your specific needs with less coding, while eliminating the complexity of integrations and automations. Here are some examples of enterprise-grade solutions we can help you deliver:

• ERP-Integrated Order Management Systems – Process online and offline orders automatically, update inventory in real time, and send confirmations without manual intervention.
• Automated Claims Processing Platforms – Receive claims via secure email, extract data, and route it through review and approval workflows.
• Compliance-Driven Document Portals – Deliver contracts, policies, and other regulated documents with secure, digitally signed email integration.
• Supply Chain Tracking Systems – Integrate supplier updates, shipping notifications, and inventory adjustments into a single, automated platform.
• Customer Service Request Platforms – Capture and route customer inquiries from multiple channels, trigger automated responses, and update case records instantly.

Talk to us to discuss your requirements and explore how we can help bring your automated solutions to life.

The post Secure Automations: LANSA Integrator Adds OAuth 2.0 for Email Services appeared first on LANSA.

What Is AIX?

AIX (Advanced Interactive eXecutive) is a Unix-based operating system. IBM released it in 1986. It supports different hardware, including IBM RS/6000 series, Power and PowerPC-based systems, IBM System i, System/370 mainframes, PS/2 personal computers, and the Apple Network Server. AIX is a popular and widely-used operating system since it is secure, scalable, and robust. IBM maintains and improves it, releases updates, and adds modern features.

What Is IBM i?

IBM i is an operating system with an embedded database that was created for midsize businesses. Now many modern companies use it. IBM created it for AS/400 system in 1988. The first operating system name was OS/400. Also, it is known as IBM iSeries.

IBM AIX vs. IBM i: What Are The Similarities And Differences?

AIX and IBM i are operating systems created by IBM at the end of the last century. Then it constantly updates these systems and adds features that are important for modern business. Both AIX and IBM i are scalable, secure, and reliable systems.

AIX can be used in different hardware platforms, while IBM i was developed for AS/400 line of systems. Also, AIX is used in servers, NAS, and workstations, and IBM i is used in minicomputers and servers. And the last thing to note, IBM i is usually installed on IBM devices, while AIX works on devices of various companies.

IBM AIX vs. IBM i: What Are The Pros And Cons?

AIX and IBM i have similar pros:

• High stability. These systems can work for several years without failure.
• Powerful and convenient interface.
• High level of security.
• The ability to easily scale as the business grows.

AIX vs IBM i cons:

IBM AIX has an encrypted, difficult-to-manage, and fragmented software maintenance process. Different types of updates have their own way of managing and applying them.

IBM i does not have enough CASE tools such as RDi. Also, it does not have a JSON-based parser for working with modern data formats.

Is IBM AIX Dead, And Isn’t Unix Relevant In Today’s Market?

Some experts say that AIX OS is dead, but we disagree with this view. AIX runs a lot of business-critical applications and it is important for many companies. It is used by most of the top banking, insurance, healthcare companies, and retailers. Unix also remains relevant to modern business. A lot of companies continue to use AIX and migrate to it from other outdated systems.

What Is IBM AIX Used For?

IBM AIX is usually used for corporate servers, NAS, and workstations. It allows you to distribute access to memory, processor, and disk between different tasks. In addition, you can configure various security options, such as Kerberos V5 network authentication and dynamic secure tunnel authentication.

What Are The Reasons The IBM Power Systems AIX Is The Enterprise Strategic Choice?

IBM AIX has a number of significant advantages over other systems, and modern companies widely use it. There are several important reasons for this.

1. Reliability. This operating system can run various critical business processes with high loads without crashing.
2. Consolidation of servers. AIX systems enable the use of fewer servers, reducing costs and freeing up IT resources.
3. The Workload Manager is a standard component of AIX OS that allows you to automatically manage the allocation of resources between processes. It can provide information about physical memory and disk I/O, allowing you to classify and decide where to allocate your resources in the OS.
4. Cluster capabilities. You can combine computers, servers, and other resources to function as a single unit. This makes it possible to create a more reliable infrastructure in which, if one resource fails, others can compensate for it. In addition, you get a more productive and scalable system.
5. Security. Various authorization methods, security options, and access levels ensure the security of your business.

Learning AIX and IBM i: What Are The Courses, Tracks, And Certifications Available?

There are many different courses that help you learn to work with AIX and IBM i. Some of them provide the basic knowledge needed to perform daily tasks using these operating systems. Others, more advanced, teach how to install, configure, and administer operating systems.

You can also gain knowledge in different ways: attend virtual group classes or simply watch technical webinars. Many text and video materials are available on the official IBM portal. After learning these materials, you can take the AIX v7 administrator certification on the same site.

To search for additional materials, you can use the educational portals Global Knowledge and Redbooks. Use the search words AIX and IBM i and you will find many useful resources.

How LANSA Supports IBM Power System Modernization For Better Performance?

LANSA is a platform that provides a lot of opportunities for IBM i application modernization and creating new software using modern technologies. It offers several tools that provide different benefits. One of them is aXes. It allows you to turn 5250 screens into modern web pages on the fly without writing any code. You can also easily modify them and add new functionality.

RAMP, LANSA’s application modernization platform, allows you to create new applications using modern technologies while preserving existing important functionality from legacy applications. Using RAMP, you can modernize your IBM i applications incrementally, so that it does not have a major impact on business operations.

The post AIX vs IBM i: What Is IBM AIX Used For? appeared first on LANSA.

A business intelligence platform brings data from disparate sources across the business into a single environment for presentation, analysis, and sharing. It transforms raw data into structured insights through visualizations, dashboards, and multimedia narrative reports. A BI platform serves as a reliable foundation for understanding performance, identifying trends, and making faster, more accurate decisions.

Today, businesses work with data from various systems, including sales, finance, customer, and operations tools. Without a business intelligence platform, this data often remains scattered, making it difficult for teams to identify patterns or understand performance.

Modern BI platforms are designed for more than just analysts. Executives, managers, and frontline teams can all access insights without technical skills, making business intelligence a core part of day-to-day work rather than a separate reporting function.

Choosing the right business intelligence platform is just as important as understanding what it does. Different organizations have different data environments, users, and goals, so the right solution must align with both current needs and future growth. Factors such as ease of use, scalability, integration with existing systems, and strong data governance all play a role in long-term success. A well-chosen BI platform delivers value today while continuing to support better decisions as the business evolves.

Why Are Business Intelligence Platforms Important for Businesses?

A good business intelligence platform connects data directly to action. Organizations that understand the benefits of business intelligence
are better positioned to align strategy, operations, and performance around consistent, data-driven insights.

A good business intelligence platform connects data directly to action. Instead of relying on guesses or outdated reports, teams work with real-time, reliable information, ensuring decisions are based on accurate, up-to-date data. Organizations using BI tools report up to 27% improvement in decision-making speed and 91% of companies had planned to expand BI investments.

By creating a single source of truth, a business intelligence platform improves consistency across the organization, reduces conflicting numbers, and strengthens trust in the data used for operational and financial decisions. For instance, a BI platform can combine sales data, customer activity, and financial data into one BI dashboard. With it, leaders can immediately see how revenue, customer behavior, and operational performance relate to each other in real time. This visibility is critical in today’s fast-moving markets, where organizations must quickly understand what is happening across the business in order to respond to changing demands and conditions. Keeve reported that data-driven companies are 23x more likely to acquire customers.

Modern BI platforms also enable self-service analytics, allowing business users to explore data independently without advanced technical skills. Managers, executives, and operational teams can access dashboards, drill into reports, and ask questions directly from the data. This ensures that insights are available when decisions need to be made. For example, a sales manager can adjust pricing or promotions when demand drops, an operations team can reallocate inventory when stock runs low, and finance leaders can quickly identify cost overruns or revenue gaps. Instead of waiting for analysts to produce reports, teams can act immediately based on the latest data.

Beyond responding to immediate issues, business intelligence platforms also support better forecasting. By analyzing historical performance and current trends, leaders can anticipate shifts in demand, understand customer behavior, and identify growth opportunities earlier. In fact, more than three‑quarters of global enterprises consider BI essential for operational and strategic planning, and organizations using BI report significantly faster decision-making and improved return on investment.

A business intelligence platform is also easier to scale as organizations grow. Traditional reporting processes often rely on spreadsheets, manually compiled reports, or custom queries that require constant maintenance from analysts and IT teams. As data volumes increase and more users require access to insights, these approaches quickly become inefficient and difficult to manage. BI platforms address this challenge through automated reporting, scheduled refreshes, and centralized dashboards that reduce manual effort and errors. This allows teams to focus on improving processes instead of compiling data. Over time, these efficiency gains help control costs, improve productivity, and support stronger profitability.

In addition, BI platforms strengthen security and data governance. Centralized access controls, role-based permissions, and audit capabilities ensure sensitive data is protected while still being accessible to the right users. This balance of access and control reduces risk, supports compliance, and ensures insights remain trustworthy as data usage expands.

BI Platform Benefits Recap

• Improved data consistency and trust through a single source of truth
• Greater access to insights through self-service analytics
• Faster decision-making with real-time, actionable insights
• Better forecasting and planning through analysis of historical and current data
• Greater operational efficiency through automated reporting and centralized dashboards
• Scalable analytics capabilities for growing data volumes and users
• Stronger data governance and security through centralized access controls

How Do Business Intelligence Platforms Work?

A business intelligence platform transforms raw data into actionable insights through a structured workflow that includes data collection, preparation, analysis, and visualization. Each stage ensures data accuracy, relevance, and usability for decision-making.

Gather Data

The first step is collecting information from across the organization. In a BI platform, this means connecting to the systems where business data is generated. Common sources include ERP systems, CRM tools, finance applications, cloud software, spreadsheets, and legacy databases.

These connections are typically established through built-in connectors, APIs, or direct database queries. Instead of looking at data in isolation or manually exporting files, the platform retrieves information directly from operational systems and consolidates it into a central analytics environment.

Related article: Integrating IBM i Data with Multi-Platform Insights

For example, a retailer may combine sales transactions, inventory levels, supplier deliveries, and customer orders. When these records are viewed together, teams can see which products are selling, whether stock levels can meet demand, and how supply chain activity affects revenue.

Clean Data

After collection, the information must be prepared before it can support analysis. Records from different systems often contain duplicates, missing values, or inconsistent formats that prevent accurate comparisons.

Cleaning and preparation involve correcting errors, standardizing fields, and aligning records across datasets so information can be evaluated consistently.

BI platforms support this step with built-in preparation tools that profile datasets, detect inconsistencies, and apply validation rules based on pre-defined business logic. These capabilities reduce manual cleanup and ensure dashboards reflect reliable information.

Visualize Data

Once preparation is complete, the BI platform presents the information through dashboards, charts, and reports. Visualization converts structured datasets into formats that are easier to interpret than raw tables.

Typical visualizations include line charts for trends, bar charts for comparisons, pie charts for distribution, and KPI dashboards that track performance. Because BI platforms connect directly to underlying systems, these visualizations can update in real time as new data becomes available.

Dashboards allow teams to monitor metrics such as revenue growth, operational performance, or customer activity from a single interface.

Watch this demo: IBM i Data Reporting and Visualization

Understand Data

Business intelligence platforms help analyze data to uncover meaningful insights. This includes identifying trends, correlations, outliers, and patterns that are not immediately visible in raw data. Built to help teams understand context and drivers behind performance, not just surface-level results, they provide interactive BI reporting tools that allow users to filter views, drill through details, and compare data across different dimensions.

For example, a business may identify declining sales in a specific region. By analyzing related operational, customer, and delivery data together, the BI platform can help highlight contributing factors such as fulfillment delays, changing customer behavior, or product availability. These insights enable leaders to prioritize actions based on evidence rather than assumptions. Modern solutions may also include AI-assisted capabilities to interpret data faster.

Outcome: Democratized Access to Data

Ultimately, a business intelligence platform expands access to data across the organization. Instead of relying on IT teams for every report, users can explore insights on their own, while governance rules continue to protect sensitive information and maintain data integrity.

With interactive dashboards presenting real-time data at the point of decision-making, end users can act quickly and with confidence. They no longer need to wait on IT for data pulls and can query additional information on demand using plain language. Designed for self-service, BI platforms allow non-technical users to customize reports on the fly and create personalized workflows that support their roles.

As the McKinsey report shows, broader access to consistent, trusted data promotes wider BI adoption, which can translate to stronger organizational alignment, better business outcomes, and sustained competitive advantage. With the right BI platform, you can also free up your IT team to refocus on higher-value initiatives such as improving data architecture, supporting new business requirements, and driving innovation.

Considerations When Choosing a Business Intelligence Platform

Choosing the right business intelligence platform requires more than reviewing a feature list. Decision-makers need to consider how the platform will support the organization over time, including its ability to scale with growth, remain easy to use, maintain data control, and deliver long-term reliability. A strong BI platform should address current business needs while remaining flexible enough to adapt as priorities, users, and data volumes evolve.

Below are the key considerations when shortlisting business intelligence platforms, along with practical guidance on what to look for and what to avoid.

Scalability and Performance

As businesses expand, data volumes increase and more employees across departments require access to dashboards and reports.^[3] A business intelligence platform must support this growth in users and data without slowing down or becoming unstable.

Test how the BI platform performs with large datasets and multiple users. Ask whether it can scale storage and processing power as data increases. Cloud-based BI platforms often make this easier, but on-premise solutions should also support growth through flexible architecture.

A common mistake is choosing a BI platform that works well during early use but struggles as demand grows. Slow dashboards and long refresh times reduce trust and adoption.

Ease of Use and Self-Service Analytics

A BI platform only delivers value if people actually use it. Since not everyone is a data expert, ease of use is critical for adoption across the organization.

Check whether non-technical users can create dashboards, explore data, and answer questions without extensive training. Look for clear navigation, guided workflows, and self-service analytics features that reduce reliance on IT teams.

Avoid BI platforms that require technical skills for basic reporting. When every request depends on IT, insights are delayed and users lose interest.

Watch this demo: IBM i Dashboards for Real-Time Analytics

Integration and Data Connectivity

A business intelligence platform is only as useful as the data it can access. If it cannot connect to your systems, insights will be incomplete.

Look for native connectors to ERP systems, CRM tools, databases, cloud applications, and even legacy platforms for comprehensive reporting. Open APIs and standard data connectors can help ensure flexibility as your technology stack evolves.

Platforms that rely on manual data exports or custom workarounds create delays and increase the risk of errors. These approaches also make real-time insights difficult.

Automation and Workflow Efficiency

Automation reduces manual effort and keeps insights current. Without it, BI often turns into another reporting burden.

Check for automated data refreshes, scheduled reports, and alerting based on key metrics (e.g. monitor thresholds and detect trend anomalies). These features help teams stay informed without repetitive, manual analysis, enabling faster responses to changes.

However, automation should be applied thoughtfully. Automating reports that do not support real business decisions or sending too many data notifications can overwhelm users and make it harder to focus on the insights that matter.

Watch this webinar: Analytics Your End-Users Will Love

Data Governance and Quality

Decisions are only as good as the data behind them. Strong governance ensures that insights are accurate, secure, and trusted.

Review role-based access controls, audit logs, and compliance features. A strong BI platform should support data quality rules, track data sources, and manage access according to user roles.

Poor governance leads to conflicting reports, data misuse, and compliance risk. If users do not trust the data, they will stop using the platform.

Built-In Intelligence and AI Capabilities

AI features can help users discover insights faster by highlighting trends, anomalies, and patterns that may not be obvious.

BI platforms with Natural Language Querying (NLQ) allow users to ask questions in plain language and instantly retrieve relevant data. BI software like LANSA BI also include Assisted Insights that automatically explain the relationships, contributing factors, and comparisons behind key metrics using contextual, statistically grounded analysis.

Related article: Making Data-Driven Choices with Assisted Insights Generation

With generative AI now integrated into modern BI platforms, narrative reports and data stories can also be created with a single click. However, structured data models and governance controls remain essential for ensuring insights are accurate and reliable.

Deployment Flexibility

Organizations have different infrastructure, security, and compliance requirements. A BI platform should support deployment models that align with these needs.

Determine whether the platform supports cloud, on-premise, or hybrid deployment. Flexible deployment options make it easier to integrate BI into existing environments while maintaining control over sensitive data.

Platforms with limited deployment options may create unnecessary infrastructure constraints or complicate integration with existing systems.

Vendor Reliability and Support

A business intelligence platform is a long-term investment. Vendor stability and support quality directly affect success.

Review customer feedback, support options, documentation, and product roadmaps. A reliable vendor should provide clear support processes and demonstrate a commitment to ongoing product improvement.

Vendors with limited support, unclear plans, or infrequent updates can create risk over time. Poor support often leads to downtime, unresolved issues, and stalled adoption.

How Can LANSA BI Help?

LANSA BI is an AI-powered business intelligence platform you can deploy either as a stand-alone or an embedded analytics solution. Designed to simplify reporting for non-technical users and to support IT with enterprise data governance, it excels in delivering modern data experiences out of the box.

Whether you’re implementing BI for the first time or replacing end-of-life tools, LANSA BI offers native integrations, intuitive self-service features, and flexible deployment options to accelerate adoption.

Watch this webinar to learn more: Modern Business Intelligence with LANSA BI

• Create reports and dashboards with simple drag-and-drop functionality
• Get answers from your data without coding using Natural Language Query
• Analyze data with interactive tools and AI-assisted insights
• Automate report distribution and set up critical alerts
• Collaborate on presentations and get AI assistance in building narratives

Turn data into action faster while reducing the burden on IT and supporting long-term growth. Contact us for a private demonstration or a free consultation with our BI experts to tailor a proof of concept to your needs.

References

[1] “The age of analytics: Competing in a data-driven world | McKinsey & Company.”
https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-age-of-analytics-competing-in-a-data-driven-world

[2] “39 Business Intelligence Statistics for 2025 | KeeVee.”
https://www.keevee.com/business-intelligence-statistics

[3] “Business Intelligence Statistics | DataStackHub.”
https://www.datastackhub.com/insights/business-intelligence-statistics/

[4] “AI-driven operations forecasting in data-light environments | McKinsey & Company.”
https://www.mckinsey.com/capabilities/operations/our-insights/ai-driven-operations-forecasting-in-data-light-environments

[5] “A Systematic Literature Review on the Impact of Business Intelligence on Organization Agility | MDPI.”
https://www.mdpi.com/2076-3387/15/7/250

The post What Is a Business Intelligence Platform and How to Choose the Right One appeared first on LANSA.

Developing PWAs with Visual LANSA helps developers design, build, and deploy a PWA for any device with ease. From a streamlined development process to cross-platform compatibility and offline functionality, Visual LANSA provides a comprehensive toolkit that empowers developers to create PWAs that meet the highest standards of performance and security.

Key Insights

• Low-code PWA development made simple
  Visual LANSA enables developers to build progressive web applications using drag-and-drop functionality and pre-configured service worker and manifest files—no extensive coding required.
• Unified toolkit with full customization
  With built-in templates, widgets, and responsive design support, developers can fully customize PWAs while maintaining consistent branding and performance across devices.
• Built-in offline support and caching
  Advanced caching mechanisms allow PWAs built with Visual LANSA to work offline, improve loading times, and deliver a reliable user experience even in low-connectivity environments.
• Enterprise-grade security and integrations
  Visual LANSA ensures secure data handling via HTTPS, SSL, and integrated authentication options—making it ideal for building secure, enterprise-ready progressive apps.
• Lower development and maintenance costs
  Since PWAs work across platforms without separate Android or iOS builds, businesses save significantly on development costs while reaching a broader audience faster.

Bridging the gap between web and mobile applications with PWA development

Developing PWAs with Visual LANSA offers a range of benefits that not only simplify the development process but also enhance user experience and overall performance. Furthermore, the professional low-code platform allows developers to design and develop applications through simple drag-and-drop actions and eliminates the need for extensive manual coding.

Whether it’s the intuitive visual interface or the seamless deployment process, the professional low-code development solution transforms the journey of PWA development into an efficient and user-centric experience. Let’s dive into the key benefits of building PWAs with Visual LANSA.

1. Easy to develop

Visual LANSA simplifies the development of Progressive Web Applications (PWAs) through its professional low-code platform. Creating a PWA is the same as creating any other Visual LANSA application. Developers can take advantage of its low-code drag-and-drop interface to select assets. This enables developers to build feature-rich PWAs without learning different programming languages and other web technologies. Not to mention, Visual LANSA is integrated with the LANSA repository which makes the application development very easy. Furthermore, when developers start building PWAs, this professional low-code development platform automatically generates the components (Manifests and Service workers) to make the PWA development process easier.

Visual LANSA makes it easy for developers to set their caching strategies and select the resources to be cached. Developers simply need to select the cache strategy and then drag and drop assets they would like to have cached when end users visit the site or use the application. Any asset defined by the developer to be cached will be automatically handled by the service worker, making Visual LANSA the simplest tool to create PWAs.

With Visual LANSA, transforming existing web applications into PWAs is made simple and straightforward. Developers can use this professional low-code development tool to add the necessary PWA components, such as the web app manifest and service worker. The web app manifest defines the PWA’s metadata, including its name, icons, and display preferences, while the service worker enables offline functionality and caching for a faster and more reliable user experience. Find out how to turn existing web applications into PWAs in Visual LANSA.

2. Fully customizable

Visual LANSA is equipped with a repository containing a rich set of application components tailored for PWA development. From intuitive UI elements to seamless data integration, this professional low-code development platform offers a well-rounded toolkit that caters to various PWA development needs and streamlines the development life cycle. It provides pre-built widgets and templates for common PWA features such as push notifications among others. Developers can use these widgets and templates to kickstart their progressive web applications without creating these elements from scratch.

Moreover, Visual LANSA’s built-in support for responsive design ensures that progressive web applications easily adapt to different devices and screen sizes. Additionally, this professional low-code development tool is integrated with debugging tools for testing that assist developers in finding and resolving bugs easily.

3. Enhanced Security

With cyber threats increasing significantly, implementing robust security measures is of utmost importance to application developers. PWAs developed using Visual LANSA incorporate secure communication protocols such as HTTPS and SSL to protect the application and accompanying user data. These secure communication between the web server and the application server by encrypting data in transit. Furthermore, it provides secure authentication and enables developers to integrate authorization and authentication features into PWAs.

4. Reduced development costs

Developing custom business solutions is a task that can yield substantial benefits, but it also typically demands a significant investment. Not to mention, when it comes to developing native mobile applications, businesses often need to create and maintain different versions for the Android and iOS operating systems, doubling the cost. PWAs, on the other hand, do not require separate versions for various devices. A single progressive application meets the requirements of all endpoints on which it operates. Building PWAs with Visual LANSA significantly reduces costs due to the unified codebase. Developers do not need to write separate code to run the web application on different devices. It not only reduces the developer’s efforts but also the development costs.

Watch our webinar on how to cut development costs with low-code solutions.

4. Excellent performance

Visual LANSA not only empowers developers to create PWAs with impressive features but also incorporates robust offline functionality. It allows users to access critical features and content offline. One key feature in Visual LANSA is its advanced caching mechanism, which enables applications to cache resources, improving application performance and loading speed. Visual LANSA provides developers with cutting-edge tools to enhance the speed and efficiency of their PWAs. This includes optimizing code execution, minimizing network requests, and employing effective caching strategies.

PWAs: The future of web development

As businesses increasingly recognize the importance of delivering seamless digital experiences, Visual LANSA has emerged as an efficient solution for transforming development paradigms and creating PWAs that meet the highest performance standards. This professional low-code solution empowers developers to design and deploy PWAs effectively with speed and precision, enabling businesses to stay ahead of the curve in a tech-driven landscape. The combination of PWAs and Visual LANSA offers a compelling alternative to traditional mobile development. Its commitment to enhancing performance, reducing development costs, and expediting time to market sets the stage for businesses to thrive in the digital world. Whether you are a startup company or a large enterprise seeking to revitalize your online presence, Visual LANSA opens up new avenues for creating PWAs that set your business apart in today’s competitive marketplace.

LANSA and PWA — A match made in heaven!

Are you ready to transform your web presence? Dive into the world of PWAs with Visual LANSA, a professional low-code development solution that empowers developers to create engaging, secure, and high-performance applications effortlessly.

Visual LANSA accelerates your development process, reduces costs, and keeps you ahead of the curve. Whether you are a seasoned developer or just starting your journey, Visual LANSA’s intuitive design empowers you to quickly grasp the essentials of PWA development and efficiently bring your vision to life. Contact us today to start your journey towards developing progressive web applications with Visual LANSA.

The post Creating PWAs using Visual LANSA appeared first on LANSA.

Visual LANSA is a low-code platform that supports the creation of various types of applications, including mobile applications. It offers a reliable IDE (integrated development environment) for building native mobile, responsive, and progressive web applications. With this professional low-code tool, developers can create applications end-to-end using just one language, saving their organization a lot of time and resources.

Braum’s success story illustrates the transformative impact of Visual LANSA on mobile application development. In their case, they needed a mobile application that makes it easy for their employees to access information without relying solely on back-office PCs. Visual LANSA helped them by enabling the implementation of mobile applications that allowed managers to access essential business reports such as inventory, sales, and store inspections on their mobile phones and tablets. It further proved instrumental in replacing Braum’s outdated paper-based customer/complaint system. The mobile solution facilitated instant notifications for managers, empowering them to promptly respond to customer inquiries. This transition from a PC-centric environment to a mobile-friendly platform not only enhanced accessibility for managers but also ensured they could stay informed and make timely decisions while on the go.

Key Insights

• Unified low-code approach for mobile apps: Visual LANSA empowers developers to build native, responsive, and progressive mobile applications using a single language and platform—drastically reducing complexity and development time.
• Rapid prototyping and deployment: Developers can create interactive prototypes and deploy mobile apps faster using pre-built components and drag-and-drop tools, speeding up the feedback loop and time-to-market.
• Cross-platform compatibility with modern UX: Applications built with Visual LANSA are mobile-responsive by design and include material design controls, ensuring a seamless user experience across devices and screen sizes.
• Seamless integration and high security: Built-in support for RESTful APIs enables easy integration with enterprise systems, while embedded security features ensure safe data handling and compliance with industry standards.
• Support for PWAs and offline capabilities: Visual LANSA makes it easy to build progressive web apps (PWAs) that work offline, send push notifications, and are easily shareable—enhancing accessibility and performance in low-connectivity environments.

Simplify native mobile application development

Visual LANSA simplifies the development of native applications by offering a unified solution that allows developers to create applications for multiple platforms like Android and iOS. With it, developers do not need to know the different languages, frameworks, and plug-ins required by each platform. The cross-platform capability of Visual LANSA enables developers to code once and deploy their applications anywhere across environments. Let’s dive deeper into the benefits below.

1. Low-code development

With its low-code development capabilities, developers can build native applications with minimal manual coding. Visual LANSA streamlines the development of native mobile applications by providing visual development tools for designing user interfaces, defining data models, and specifying business logic. By using pre-built components, developers can quickly build mobile applications and deploy them across multiple platforms without doing platform-specific coding. Not only does it simplify the application development process, but it also accelerates time-to-market.

2. Rapid prototyping of new applications

Prototyping is one of the most essential parts of mobile application development, allowing developers to create a working model of the application before investing time and resources into coding. With Visual LANSA’s rapid prototyping tools, developers can design an application easily and quickly. Needless to say, creating prototypes not only helps detect design flaws and usability issues, but also enables users to provide feedback and suggestions. By visualizing and testing the application, resolving design issues, and improving user experience, developers can create high-quality mobile applications that meet user expectations.

3. Modern design and user experience (UX)

In the ever-evolving competitive world of mobile applications, a beautiful interface and seamless user experience can make or break the success of an application. Visual LANSA places a strong emphasis on modern design and user experience by enabling developers to build applications that are not only intuitive but also visually appealing. This professional low-code development tool offers material design controls for those developers who are not experts in building modern UX. It provides a standard set of UI/UX elements that users are already familiar with and know how to operate so that developers do not need to start from scratch.

4. Reusable components

Visual LANSA transforms mobile application development with its repository of reusable components and advanced building blocks. In it, developers can store business logic, visualizations, and custom parts ready for cross-platform deployment. Beyond speeding up development, it ensures a consistent and robust approach, especially beneficial for implementing shared functionalities across diverse enterprise applications.

5. Easy integrations

Visual LANSA provides a wide range of options for integrating with existing systems, databases and applications through APIs. This capability allows developers to seamlessly connect their mobile applications with other business-critical tools and services. Unlike other platforms that often require custom development to build integrations, Visual LANSA supports RESTful APIs, simplifying the integration process. Whether it’s establishing connections with enterprise databases, third-party applications, or proprietary systems, this professional low-code development solution ensures that developers can create mobile applications that work within the existing technological stack of any organization.

6. Security

No one likes to use a mobile application that’s not secure, regardless of how aesthetically pleasing or feature-packed it may be. Visual LANSA addresses this issue by integrating robust security features into the development environment from the ground up. From secure authentication and authorization mechanisms to data encryption and compliance with industry standards, this professional low-code development solution protects mobile applications built on it against potential threats and vulnerabilities. Moreover, it ensures that data remains protected throughout the application development lifecycle.

Create mobile responsive applications with Visual LANSA

Visual LANSA enables developers to create web applications that can be easily accessed from a smartphone or tablet. It gives users a better experience irrespective of OS, device, orientation, screen size, or browser. With this cutting-edge solution, developers can build dynamic enterprise applications for mobile devices that are fully integrated with their application server using a single language for client-side logic, server-side logic, and everything in between. Furthermore, developers can design responsive applications without using front-end frameworks such as Bootstrap.

Not to mention, the professional low-code development solution enables developers to design interfaces that automatically adapt to various devices with different screen sizes. Visual LANSA incorporates a built-in device detection mechanism that identifies the device type, whether it’s a mobile or tablet, and adjusts the interface accordingly.

Build PWAs effortlessly with Visual LANSA

There’s no denying the fact that progressive web applications have revolutionized the way businesses approach application development. Traditionally, businesses faced the challenge of distributing their applications across various application stores, each catering to different operating systems (e.g., Android, Apple, and Microsoft). However, PWAs have resolved this issue, as they can be accessed directly through web browsers. These applications can be installed either from the platform’s application store or directly from the web, simplifying both go-to-market and user adoption.

When it comes to developing PWAs, Visual LANSA aids the process by providing a drag-and-drop user interface design, often with standards like Google Material Design built-in. Like native applications, PWAs created using Visual LANSA can work offline, send push notifications, and access device hardware such as GPS, or camera.

Progressive web applications created with Visual LANSA take advantage of both web and browser technologies, making them easily shareable through a URL. Users can send the URL via emails or text messages or share it directly on a webpage. This simplifies the process of sharing the application amongst new and existing audiences.

Furthermore, cache also plays a very important role in making PWAs versatile. The ability to cache resources provides better application performance and reduces network load in areas of low connectivity and slow service. Visual LANSA makes it easy for developers to set their caching strategies and select their resources to be cached. Developers just need to select their cache strategy and drag-and-drop assets they like to have cached when end users use the application or visit the site.

Harness the power of mobile applications with Visual LANSA

To stay competitive in today’s fast-paced business world, it is essential to leverage the latest technological developments. Mobile applications, once considered optional, have now become indispensable tools for modern businesses. Embracing the potential of mobile applications can not only improve customer relationships but also position a company for long-term success in the digital world.

Watch our lightning session on Simplifying Mobile Development with Visual LANSA now.

Deliver mobile solutions that fuel digital transformation fast

Take the next step in mobile application development with Visual LANSA. Whether you’re looking to build a native mobile application or want to release a mobile-friendly solution quickly through PWAs and responsive web, our professional low-code solution is available to support your developers. Enjoy significant cost savings and simplified processes using LANSA’s unified codebase for cross-platform development. Do not compromise quality, security, and scalability for faster time to market. Ask us how you can have it all. Contact us to learn more.

The post Developing Applications for Mobile Users Using Visual LANSA appeared first on LANSA.

The Visual LANSA repository acts as a database, serving as a centralized hub for managing, storing, and retrieving information about applications. Developers can reuse the information stored in the repository in any application to radically increase flexibility and efficiency. In addition to bringing a systematic approach to the development process, the repository also simplifies application maintenance because the centrally stored information is easy to find and change.

Key Insights

• Centralized asset management: Visual LANSA offers a centralized repository with a unified space to define, store, and access application components, ensuring consistency and minimizing duplication across projects.

• Reduced development time: By reusing predefined fields, business rules, and components, developers can accelerate application delivery and focus on value-added functionality instead of writing repetitive code.

• Simplified cross-platform deployment: With platform-agnostic definitions, developers can build once and deploy everywhere—across Windows, IBM i, Linux, mobile, and web environments—without rewriting logic.

• Streamlined maintenance and updates: Changes made to a component in the repository automatically apply to every application using it, significantly reducing maintenance effort and risk.

• Enhanced team collaboration: A shared repository promotes collaboration and version control, allowing teams to track, update, and reuse logic with minimal friction.

Types of information stored in the LANSA Repository

The Visual LANSA repository stores a vast range of information about applications in a central location, helping streamline the development process. It significantly reduces application coding as information is defined just once in a central location rather than being repeated wherever it is used in application programs. For instance, a business rule for a field is defined once instead of in every program that uses that field.

LANSA repository stores all the information in a non-platform-specific format that enables developers to develop applications for Windows, iSeries, and Linux.  The reusable field and file definitions are available to all LANSA applications, whether these are executed on Windows or IBM i. Other applications can also use these definitions through LANSA’s middleware.

Here are some of the things that can be stored in the LANSA Repository:

• Fields: The LANSA repository contains field-related information, such as data type, length, description, visualizations, default values, column headings, edit codes, prompt programs, and many more. It acts as a data dictionary for the application you are building.
• Files/Tables: In addition, the repository stores information about the files/tables or application database, like file relationships, physical files, file definition attributes, logical views, file validation rules, virtual fields, and many more.
• Business rules: File/Table and field columns can have validation rules defined that can be applied during updating, adding, or deleting a table record. Examples include Date Check, Range Check, List Check, and Simple Logic Check. These rules are implemented by table. It means that most data validation rules can be automated instead of built into each component.
• Components: Visual LANSA supports a wide range of application components for web, desktop, and mobile applications. All of these components are written using the same high-level object-oriented language, providing power and flexibility to develop modern applications with rich interfaces. The repository created on Visual LANSA supports higher-level components such as visual styles, themes, cursors, and icons.
• Resources: The repository contains resources that can be used in your application, such as system variables, multilingual variables, external resources, widgets( Visual LANSA wrappers around external code), ActiveX controls, images, styles, themes, and many more.

How the LANSA repository boosts productivity

With the Visual LANSA repository, developers can accelerate the development process by simply reusing stored application information, including fields, tables, rules, relationships, components, system variables, and more. LANSA’s active repository provides numerous benefits to application developers and end users of applications, ranging from simplifying the development process to enhancing application performance. Let’s dive into the key benefits of building a repository on Visual LANSA. 

• Reduce application coding

The Visual LANSA repository architecture significantly reduces extensive coding whenever you want to build a new application or extend the functionality of an existing application. Learn more about the benefits of low-code development and how it enables faster, more efficient application building.

By defining information and reusable components just once in a central location, such as functions and fields, developers can cut down the lines of their code. They can reuse the defined components wherever it is needed in application programs. Rather than investing time in writing the same code repeatedly in an application program, developers can concentrate on creating unique and value-added features for their applications. It not only also enhances the overall quality of the application, but also reduces the likelihood of errors.

Consider a scenario where the same validation logic is required for a data field in multiple places while developing an application. Instead of writing redundant code, developers can create a standardized date validation component in the repository using Visual LANSA. Once the component is created, they can integrate it effortlessly into different sections of the application. 

• Simplify application maintenance 

In addition to accelerating the development process, the Visual LANSA repository also simplifies application maintenance. When an update or change is needed in applications, modifying a component within the repository automatically makes the same changes across all applications that are using that component. This feature enables developers to make changes without impacting other parts of the code. It not only reduces the risk of inconsistencies but also makes updates more efficient.

• Facilitate collaboration

One of the key benefits of using Visual LANSA’s repository is its ability to facilitate effective collaboration among developers. By providing a centralized location for storing and sharing information, it enables developers to easily access relevant data and reusable components to build a new application.  Share your work with other developers and track changes made to the codebase over time. 

• Simplify cross-platform development

Visual LANSA’s repository plays an important role in simplifying cross-platform development by offering a platform-agnostic approach to coding. It centralizes the definition of fields, functions, and other reusable components. This enterprise low-code platform allows developers to build code once and deploy it everywhere, ensuring seamless adaptation across multiple platforms without requiring extensive modifications.

With this solution, developers no longer need to develop and maintain application versions for different platforms. Whether on desktop or mobile, Visual LANSA makes it easy for developers to simplify and automate development on different devices and platforms. Learn how to develop mobile applications with Visual LANSA and accelerate cross-platform deployment with a low-code approach. By supporting cross-platform development, Visual LANSA saves developers from the complexities of managing several codebases and reduces the effort required to update applications across various platforms.

Streamline application development using the LANSA repository

The dynamic digital landscape is forcing organizations to tap into new technologies. With the rising demand for digital applications, a well-organized repository is a game-changer. Learn how to build your repository on Visual LANSA to maximize efficiency, improve maintainability, and streamline development workflows.

From tables, fields, rules, and relationships to components, system variables, and many more, the Visual LANSA repository stores all information about applications in one place. This repository can be shared with developers easily so that everything in it can be reused within the same or across different applications, reducing the amount of code to write. By embracing the benefits of shared application information and reduced coding, organizations can accelerate application development processes.

Eliminate code redundancy and speed up development in one fell swoop!

Are you tired of code redundancy and writing a lengthy code to develop an application? Gone are the days when software development used to be a time-intensive task. Visual LANSA’s repository makes the development process faster by enabling developers to share and reuse application information.

Start building your repository on Visual LANSA today and discover how it can streamline your development process and help accelerate your time to market. Watch our on-demand webinar to see how Visual LANSA simplifies application development and boosts productivity.

Contact us today to get a demo and learn how Visual LANSA repository can help businesses get applications developed in a quick turnaround time without investing a huge amount of money.

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It’s challenging to deal with the variety of platforms, frameworks, and applications. Each one of these can have its own distinct demands and syntax. Instead of losing your sanity in learning all the languages and tools out there, there is a simple alternative to these frustrating complexities – professional low-code development.

Being able to develop in an Integrated Development Environment (IDE) with a simple learning curve is a real game-changer. It streamlines the development process and enhances application delivery times.

Key Insights

• One framework, endless possibilities: Visual LANSA empowers developers to build web, desktop, and mobile apps using a single low-code framework—eliminating the need to learn multiple languages or tools.

• Rapid learning curve: Whether you’re a seasoned developer or new to coding, Visual LANSA’s intuitive IDE, built-in documentation, and code completion features make it easy to get started and productive within days—or even hours.

• Unified development experience: Visual LANSA allows developers to handle both front-end and back-end logic in one environment, streamlining workflows and reducing handoff delays between teams.

• Proven speed in real-world projects: From MoMA building three major systems in a year to ICS doubling their customer service efficiency, organizations consistently report faster development cycles with Visual LANSA.

• Cost-effective alternative to traditional stacks: Companies like Allianz switched from Java/WebSphere to LANSA after performance and training challenges—achieving better outcomes without inflating budgets.

• Encourages innovation by reducing overhead: By minimizing the time spent on boilerplate coding and debugging across platforms, developers can focus more on delivering high-impact features and tailored user experiences.

Why learn multiple languages when you can count on one framework?

Whether it is web applications, mobile solutions, or desktop software every domain has its own programming languages and libraries that developers must grapple with. Visual LANSA, a low-code platform helps you develop applications for different devices using a single framework. This approach is designed to reduce cognitive load, coding errors, and slow development cycles.

Streamlining your development efforts

Develop new applications without worrying about their integration with other applications. LANSA enables you to integrate applications built using different languages without hiccups. It serves as a unified coding, debugging, and testing platform. This consolidation of essential development activities and modules into a single workspace can significantly reduce the friction involved in managing different tools.

Faster project delivery

Developers have been switching to Visual LANSA to accelerate application delivery. The speed comes from the ability to work on the front-end and back-end simultaneously, on the same platform.

With Visual LANSA, they can seamlessly move between different components of the application reducing friction. It also removes the need to sync or combine the finished components. Everything is orchestrated within Visual LANSA, this saves time and energy at every step of the way. This enables a faster time-to-market for applications.

Driving innovation without compromising time

Professional low code reduces the time and energy needed to code every line. The result is shorter development cycles, leaving more room for innovation. With a short learning curve, agile design, and professional low-code features, developers can take their efforts beyond development.

A swift learning curve

The learning curve with Visual LANSA is simple and short. LANSA makes it easier with features such as code completion, built-in documentation, and integrated version control. These enable you to reduce the learning curve for developers significantly. Many developers prefer Visual LANSA over other tools trying to do something similar because the acquisition of new skills is much more rapid.

Watch our recorded webinar on building modern business applications with Visual LANSA.

MoMA builds 3x faster

Some time ago the Museum of Modern Arts (MoMA) came to LANSA with a problem. They faced the challenge of transitioning from their existing iSeries application to a more user-friendly and integrated solution.

They identified a need for a new membership system to replace outdated and unconnected systems. This transition was necessary to streamline their operations and improve services to their members. Their team had a heavy task at hand to transform and web-enable the application in a limited time before a major event.

Their developers learned quickly with the knowledge base and documentation available in Visual LANSA. Within a week, they were able to develop rapidly. Once they gained familiarity with the LANSA interface, their productivity increased significantly. The team was able to implement the new system days before the launch.

When they were about to deploy the system, they realized there was potential to transform operations further. The development team proposed an additional application. However, through LANSA they could prototype, build, and deliver the event module within a few days.

LANSA’s productivity benefits allowed the development of multiple major systems in short timeframes. In a span of one year, they built three major systems after the successful launch of the first one.

The use of Visual LANSA improved efficiency, enhanced the member experience, and provided opportunities for future growth and innovation. It allowed MoMA to achieve its goals without a budget increase for application development.

Explore the full MoMA case study to see Visual LANSA in action.

Allianz’s new strategy to implement user-friendly applications

Allianz wanted a full-fledged software revamp to make their applications user-friendly. Given their experience, the developers at Allianz recommended a three-tier Java architecture based on WebSphere. For this, the firm started investing in training their staff in Java and setting up the WebSphere infrastructure.

Within six months, they developed a B2B prototype for their online projects using Java. However, performance issues emerged when a small pilot group began testing their Java-based site. These issues indicated that a substantial investment would be required to achieve the necessary functionality and performance levels. It meant more money, more time, and additional training sessions.

Allianz Ireland was using Visual LANSA already as their tactical interim solution for web development. However, Java-based applications were not getting them the results they were looking for. Plus, the team wanted greater agility without a long learning curve. So they decided to switch to LANSA as their strategic web development tool entirely.

Allianz’s web development team was at first skeptical about the implications of switching to low-code and learning something new again. However, the team knew it could save time and offer great agility in the long run, so they decided to give it a shot.

After a week or less of experimenting with LANSA, the team dived into the creation of efficient B2B solutions that simplified complex processes. Their solutions improved consistency and reduced manual intervention. This team harnessed Visual LANSA to streamline business operations anywhere and everywhere possible.

The adoption of LANSA led to successful B2C and B2B projects. The user-friendliness and effectiveness of LANSA as a web development tool ensured that they used it for all major upcoming projects at the firm.

Allianz management trusted Visual LANSA due to its cost-effectiveness. It was chosen over more complex three-tier Java and WebSphere architectures, demonstrating that LANSA offers a more economical and practical solution. With a quick learning curve and easy adoption, it was possible.

This approach allowed them to meet business demands effectively and complete various successful web projects. The use of LANSA helped Allianz stay competitive and deliver faster and better service.

Furthermore, Allianz leveraged LANSA to create a rule-based process for Mid Market Commercial (MMC) insurance, enabling automation and standardization. This solution reduced the time and effort underwriters spend on straightforward cases, allowing them to focus on more complex risks. It also opened up more time for the development team to explore features that added greater value to the firm.

Visa card builds tailored solutions

The experience of Visa Card Services (now International Card Services – ICS) with LANSA enabled the development of high-performing strategic applications. The decision to use LANSA was made for one and only reason: it was easy for developers to learn and deliver on it.

LANSA allowed ICS to develop a tailored solution for their specific challenges in the credit card industry. It offered the flexibility to build applications to streamline their processes and web-enable their applications.

With a few hours of learning and understanding the platform, the team at ICS was empowered enough to start their development process. They built applications that significantly improved the efficiency of their customer service department. It allowed for online inquiry and update capabilities, making customer interactions faster and more effective. They were able to double their efficiency, with Visual LANSA, producing results quickly.

The management was thrilled to do more. The developers then built more nuanced applications, such as the Chargeback module. LANSA allowed them to build more intricate rules and conditions. These applications were managed much more efficiently with LANSA as compared to manual coding.

The development team could focus on complex development issues by leveraging LANSA templates, and the central LANSA Repository allowed for easy maintenance of business rules and triggers. ICS’s developers have had a positive journey leading to the decision to stick with it for future projects.

In a nutshell

Every day LANSA comes across new stories of how developers and their enterprises love Visual LANSA. Some seasoned developers take a few hours to learn and understand the platform. Some take a few days. Others can dive right in and start exploring. New developers without prior experience can take a few weeks or less. It is simple once you get into it. Stop overthinking and experience the power of professional low code today!

Ready to simplify your development journey with professional low code?
Whether you’re building enterprise applications or modernizing legacy systems, Visual LANSA helps you do it faster—with less code and more confidence.
Contact us today to explore how LANSA can accelerate your next project.

The post Trouble-free Low-code Adoption: Stories of Learning LANSA appeared first on LANSA.

The history of business intelligence begins as early as the 1800s when author Richard Millar Devens cited a banker who gathered market intelligence before his competitors [1]. Armed with this unique intelligence, he acted on it to outsmart the competition. Evolving through the centuries, business intelligence as we know it grew in popularity in the 1990s, but it was incredibly complex and required information technology (IT) experts or developers.

Now, BI tools are revolutionizing the power of big data, putting it at the fingertips of the everyday employee. In this article, we will discuss:

What is Business Intelligence?

Business intelligence is the practice of turning data into actionable insights. Business intelligence combines data analytics, visualization, and infrastructure to help businesses make more data-driven decisions. The ultimate goal of business intelligence is to transform large, raw data sets into actionable insights that can be understood by anyone. As of 2020, the global adoption rate of BI was around 26%, with a primary objective to improve efficiencies [2].

How Does Business Intelligence Work?

Business intelligence typically works in a multi-step standard process. BI platforms automate and perform much of this process, allowing human engineering and IT team members to support when needed. Below is a general overview of how BI works.

Data collection

To create graphs, charts, and other visual tools, data has to be gathered from various departments and sources within an organization. This data can come from spreadsheets, software-as-a-service (SaaS) platforms, and other databases, and it can also include both historical and real-time information.

Analysis

Once data is gathered from multiple sources, it needs to be organized and transformed into a consistent, standardized format. This includes basic data hygiene practices like cleaning up naming conventions, merging files, or correcting inconsistencies. Once data is in a unified format, it can be stored and processed, and infrastructure can be built underneath for further analysis.

Reporting

Business intelligence reporting is the end stage of business intelligence, what most people recognize as “BI.” Once data has been collected, cleaned, and analyzed, BI platforms can create highly valuable visualizations, showing trends, relationships, significant changes, and more.

Why is BI Important?

BI is so much more than colorful graphs and charts. Business intelligence plays a key role in driving data-driven decision-making, a critical business practice that offers a variety of benefits from increased efficiency to cost savings to increased employee productivity and, ultimately, a competitive advantage.

Without BI, companies risk losing ground to competitors and falling behind the innovation curve. Organizations also run the risk of missed opportunities and inefficient budget spending. It can also result in poor customer experiences, increased churn, and lost revenue.

Industries That Benefit From Business Intelligence

BI in Manufacturing

Some of the most interesting BI examples come from the manufacturing world. For SKF, a Sweden-based global manufacturer, 17,000 distributor locations created a mess of disorganized spreadsheets that made it difficult to forecast sales, inventory, and demand [3]. By investing in BI tools that create a single, centralized data repository, marketing, sales, and logistics teams across SKF can improve the planning process.

BI in Travel

BI enhances the ability of travel organizations to increase efficiencies, reduce operating costs, and create a more positive customer experience amongst razor-thin operating margins. For example, Delta Airlines invested heavily over the last few years into big data analysis and new applications for baggage collection, leading to a reduction of 71% in lost baggage since 2007 [4]. Similarly, Expedia adopted business intelligence software to provide detailed reports to its business-travel clients [5].

BI in Healthcare

Healthcare is one of the biggest industries right for opportunity when it comes to BI. BI is transforming patient outcomes, reducing nurse burnout, and allowing for collaboration amongst providers. For example, Clinical Decision Support (CDS) software provides prescriptive analytics to practitioners, supporting real-time alerts and analysis [6]. Collaborative tools are bringing together patient data, imaging, physician notes, and more to provide more holistic care and allow healthcare practitioners to work in sync. Especially across geographical zones, BI brings together the huge amount of healthcare data generated every day to create actionable insights, identify trends, and improve patient care.

BI Methods

Depending on your company’s goals and infrastructure, different BI methodologies and approaches might work better than others.

Data warehousing

In data warehousing, large volumes of data are stored, managed, and organized as structured data. Data is organized in a centralized repository, also known as a warehouse, and is designed to be neatly organized into rows and columns. This structure makes it easy to search and analyze, creating the foundation of data visualizations.

Data warehousing is an ideal BI method for large data sets that need a centralized, organized single repository.

Data mining

Data mining is a more active BI methodology, where various techniques and algorithms seek to uncover hidden patterns, trends, and valuable insights within large data sets. Data mining as a BI approach shines as it allows machines to extract meaningful information. It identifies sequences, clusters, or abnormalities when it comes to data.

ETL (Extract, Transform, Load)

ETL moves data from the original source to the centralized data warehouse while transforming it along the way. ETL builds consistency and ensures high-quality, clean data is sorted into the central repository. Data might be cleansed, validated, aggregated, properly formatted, or even enriched as it undergoes analysis before reaching the data warehouse. Then, data is properly “loaded” into the correct format and stored.

Business Intelligence Benefits

Adopting and implementing BI offers numerous benefits to organizations of any size in any industry:

• Increases customer satisfaction
• Improves operational efficiency
• Informed decision-making
• Transparency and visibility across departments
• Increases employee productivity
• Reduces manual efforts
• Facilitates strategic planning by proactively identifying trends, opportunities, and areas of improvement.

Read more about the benefits of business intelligence.

Challenges IBM i users face in harnessing business intelligence

For IBM i users, the power system is critical for organizations and industries that focus on reliability, efficiency, and security. However, IBM i users face a variety of challenges when it comes to harnessing business intelligence to democratize data visibility, empower individual users, and utilize data-driven decision-making [7]. For IBM i users, LANSA BI’s embedded analytics provide powerful real-time insights [8].

Hefty costs

Many IBM i users are concerned about the cost and complexity of implementing BI solutions. An on-premise BI implementation could cost an average of $200,000, including software, hardware, and infrastructure, but costs can also go significantly higher [9]. However, a solution for high costs is adopting a BI tool that is tailored to the IBM i platform so less integration and migration are needed.

Data fragmentation

IBM i users face a struggle with fragmented, siloed data across departments and databases. This causes a lack of standardization, which makes it difficult to pinpoint insights and trends and create action. Another solution to IBM i fragmented data is to adopt a BI platform that integrates seamlessly with IBM i. This allows users to unlock insights and enable more informed decision-making.

Hard-to-visualize charts and graphs

IBM i houses huge amounts of data for organizations, but in its raw form, it’s not helpful or actionable. With a tool like LANSA BI, natural language query allow users to express their ask in everyday language, and the system will intelligently respond with data. Once business intelligence dashboards and visualizations are created, each individual end-user can analyze thousands of data points at a glance [10].

Security concerns

IBM i users also worry about security issues when it comes to integrating with new platforms and applications. Especially with the sensitive, confidential nature of data, any third-party integration, potentially puts that security at risk. With a business intelligence tool like LANSA BI that embeds analytics directly into existing IBM i applications, it reduces the risk of unauthorized users along with potential vulnerability concerns.

BI Trends

As we mentioned above, business intelligence has come a long way since its earliest iterations. As companies’ BI strategies mature, more sophisticated data analytics tools are created, and artificial intelligence reaches the masses, the BI landscape is looking different every year.

The emergence of self-service analytics

Gone are the days of companies relying on IT experts or developers to harness business intelligence. Not only did this keep data trapped within engineering spheres, but when team resources or bandwidth was short, BI would often fall by the wayside. Now, companies aim to democratize data and BI, improving accessibility, making data user-friendly, and overall reducing IT dependency. With self service analytics, even the most non-technical employee can create their own reporting dashboards to drive their decision-making. Not only can I create their own visualizations, but they can optimize and tweak them.

Embedded analytics

The concept of embedded analytics is another emerging trend that powers users to access and analyze data independently. Context-enriched analytics bring visual dashboards outside of the BI platform and place them where the user needs them. The embedded analytics market itself is expected to reach $77.52 billion by 2026 [11].

With embedded analytics, users get real-time contextual analysis directly within their normal workflow. It reduces the back and forth between platforms and allows data to become more easily used.

Low-code applications

One of the biggest blockers when it comes to BI adoption historically revolved around the need for software code and software developers. Now, low-code BI platforms create a user-friendly approach that requires little to no coding. Instead of complex programming languages, users can interact in visual, simple environments that use tools like drag-and-drop modules, pre-built templates, intuitive user interfaces, and more. Once again, this empowers the everyday user to harness data, create their own reports, and iterate on their own tools to finesse the data.

Steps to Developing a Successful Business Intelligence Strategy

Developing and implementing a BI strategy is not something that’s done overnight. It involves both a culture and mindset shift for your organization, executive Biane from the top down, and a restructuring of how your company prioritizes data. Below is a quick step-by-step guide for organizations to implement an effective BI strategy:

• Understand Business Goals
• Identify Stakeholders
• Choose BI Tools and Platform
• Form BI Team
• Define Project Scope
• Prepare Data Infrastructure
• Set Goals and Roadmap

Types of BI Analysis

Depending on what data you’re looking for and what insights you’re trying to glean, different types of BI analysis might be more useful than others. Also, different approaches work well together to look at past, present, and future states to create a comprehensive picture.

Predictive Analytics

Predictive analytics uses historical data to make informed predictions about future trends and outcomes. Using machine learning and artificial intelligence, patterns are identified that might predict future behavior. With predictive analytics, companies can optimize existing products, better understand customer behavior, and even improve pricing strategies.

Descriptive Analytics

Descriptive analytics looks at past data to gain insights into current trends and performance. Descriptive analytics paints a picture of what happened in the past, while on the other hand, predictive analytics makes an educated guess on what might happen in the future. Descriptive analytics focuses more on data monitoring and post-mortem analysis.

Prescriptive Analytics

Prescriptive analytics are a more advanced form of BI that not only analyzes data but also recommends the best course of action. For example, a venture capitalist firm might use prescriptive analytics to make investment decisions instead of relying solely on financial advisors’ decisions.

Types of BI Tools and Solutions

Just as there are different types of data analytics, there is a multitude of BI tools and solutions to choose from. From simple spreadsheets that most people are familiar with to complex reporting software, all of these different BI tools play a role in creating a broader data-driven culture. Let’s take a look at some of the most popular solutions below.

Spreadsheets

Spreadsheets are familiar and versatile; in BI, they offer a great amount of versatility in data, reporting, and analysis. Even in the most advanced and cutting-edge data environments, spreadsheets act as a data collection tool while also providing valuable reporting and analysis.

Reporting software

On the other hand, reporting software is a step up from basic spreadsheets. Reporting software works well in the overall BI strategy when it comes to simplifying data presentation, making it more accessible and visual to a wider audience.

Data visualization software

Data visualization software works specifically to streamline and clarify using charts, graphs, and dashboards. This helps users interpret complex data, quickly identify trends, and, like reporting software, make data more accessible to the everyday user.

Data mining tools

Data mining involves powerful statistical and mathematical tools to sift through huge data sets to discover patterns and insights. Data mining sorts through multiple databases and software to help businesses understand their customers, pinpoint anomalies, and proactively adjust to trends.

Online analytical processing (OLAP)

OLAP is more commonly known as slicing and dicing. It involves splitting multi-dimensional data into two dimensions. This computing tool processes huge amounts of data from a single repository to export into multiple categories. It facilitates a multi-dimensional model that makes it easy for users to use their data in everyday life.

The Future of Business Intelligence

Most companies are just at the tip of the iceberg when it comes to harnessing the power of business intelligence. From embracing augmented technology, like algorithms and machine learning, to creating AI-enabled technologies of their own, as more and more corporate data is created, more BI tools will be needed.

By 2023, more than 33% of large organizations will utilize advanced BI analytics to make smart decisions faster [13]. Plus, as companies adopt self-service and embedded analytics, employees from every department will begin using data as a part of their everyday workflow. Data literacy will increase, and these powerful technologies will continue to become even more prevalent.

Key Takeaways

Over the next decade, the companies that prioritize BI strategies will maintain their competitive edge, continue to innovate, and pull ahead of the pack. Business intelligence is no longer a nice to have, but it’s a critical tool for harnessing the power of big data to increase accessibility and visibility across organizations.

Forward-thinking organizations can develop BI strategies that work best for their data architecture, business needs, and goals through different BI methods like data warehousing or data mining. They can use different types of BI analysis, including predictive analytics, descriptive analytics, and prescriptive analytics, to create a comprehensive picture of their business.

For IBM i users, actionable BI is harnessed through an IBM i business intelligence platform like LANSA BI. LANSA BI leverages smart, user-friendly tools to build transformative insights through a native DB2 database integration. Tools like embedded analytics, natural language queries, assisted insight generation, and business intelligence dashboards create easy and accurate data-rich experiences.

To learn more about LANSA BI for seamless data integration and transformative analytics, register for our free webinar here, or contact our team.

References

[1] https://www.dataversity.net/brief-history-business-intelligence/ 

[2] https://wiiisdom.com/ebook/business-intelligence-trends-2020/

[3] https://www.netsuite.com/portal/resource/articles/business-strategy/business-intelligence-examples.shtml

[4] https://d3.harvard.edu/platform-digit/submission/big-data-takes-flight-at-delta-air-lines/

[5] https://www.informationweek.com/it-sectors/expedia-turns-to-business-intelligence-to-boost-business-travel

[6] https://www.datapine.com/blog/big-data-examples-in-healthcare/

[7] https://lansa.com/blog/business-intelligence/empowering-end-users-to-make-data-driven-choices-with-assisted-insights-generation/

[8] https://lansa.com/blog/business-intelligence/how-lansa-bi-brings-real-time-insights-to-ibm-i-applications/

[9] https://www.grow.com/blog/can-an-enterprise-bi-be-expensive

[10] https://lansa.com/blog/business-intelligence/choosing-the-best-business-dashboards-for-your-project/

[11] https://www.alliedmarketresearch.com/embedded-analytics-market

[12] https://techjury.net/blog/business-intelligence-statistics/

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