Changes in the Delivery of Business Intelligence

This is the continuation of the transcript of a Webinar hosted by InetSoft on the topic of "Agile BI Best Practices" The speaker is Mark Flaherty, CMO at InetSoft.

Four Key Driving Technologies

In addition social software is creating all kinds of new information and relationships. Interesting areas come up, and there is a ton of information that’s now being collected that wasn’t available just a few years ago. Search is another technology that gets mentioned a lot, the ability to find things both in numeric and also textual data. Comments, there is a ton of information that if it’s put in a form where you can easily search it, it can be key to creating new insight and knowledge.

The survey results came and it looks like 18% are business users, 35% is management and 66% is IT. So there is a good mix. Also there is a balance between the technical side and as we go into the end user side.

I would add that the true best practices for enterprise software development and support don’t work for business intelligence. The unique BI requirements include less reliance on the traditional software development cycle and project planning and more emphasis on reacting to the constant change of business requirements. This is different than an order entry system or a sourcing or scheduling system.

This is something that’s more dynamic and requires more end-user input to define and work correctly. Earlier-generation BI solutions are less effective because they often put IT in charge, remain IT centric, continue to be mostly project-based, and focus too much on functional reporting but ignore the data.

So as we look at the business intelligence market, organizations have much more of a collaboration between end users and IT. They are much more together than in the past. What happened is business intelligence was largely focused on management. They’re the buyers. They’re the key users. They tend to get operational reports and scorecards and dashboards. They need to see information at a glance where they can make a decision.

End Users of Business Intelligence

But the staff down under them will need to slice and dice the data, look at trends to make decisions. They don’t just need the summaries at high level. They actually need the detail. And reports, scorecards, and dashboards fall short if they are only summarized data, and you can't get down to the specific transactions.

To go back to IT and ask for that detail is time consuming and difficult to implement and consumes a lot of core IT resources, and hence the key staff are largely unsupported. And then when they go to IT for such reporting, for custom reports, what often happens is they ask a question which is somewhat hard to interpret. So some information comes back, but it takes a while and at best, it might be the right data or might cause another question which goes back to the loop and then it becomes hard to work with.

Changes in Business Intelligence Delivery Over the Past 12 Months

In the past 12 months, business intelligence (BI) delivery has evolved rapidly, focusing on AI-driven automation, self-service capabilities, and seamless integration into workflows. These changes address challenges like data silos and user adoption, enabling faster, more inclusive decision-making. Key trends include enhanced AI integration, real-time analytics, and a shift toward democratized and embedded BI solutions.

• AI-Powered Automation and Insights

  AI and machine learning have become central to BI, automating data preparation, cleansing, and analysis to reduce manual effort. Tools now offer predictive and prescriptive analytics, forecasting trends and suggesting actions, with platforms like ThoughtSpot integrating large language models (LLMs) for natural language queries. This has made BI more proactive, delivering personalized insights based on user roles and behavior.

• Self-Service BI and Data Democratization

  Self-service BI tools have expanded, enabling non-technical users to generate reports and insights without IT dependency. Platforms like Tableau and Power BI now feature intuitive dashboards and natural language processing (NLP), allowing users to query data in plain language. This democratization has increased data accessibility across organizations, fostering a data-driven culture.

• Embedded Analytics in Workflows

  Embedded analytics, integrating BI software into web-based applications, has surged, with the market projected to grow significantly. This approach delivers insights within users’ existing workflows, reducing the need to switch platforms. Companies like InetSoft emphasize seamless integration for real-time decision-making.

• Real-Time Analytics and Monitoring

  BI delivery has shifted toward real-time data processing, driven by cloud-based solutions and faster infrastructure. Tools like EventsAir and Qlik enable instant KPI monitoring and pattern recognition, allowing businesses to respond swiftly to market changes. This is critical for industries requiring agility, such as retail and healthcare.

• Enhanced Data Governance and Security

  With increased data volumes and regulatory pressures (e.g., GDPR, CCPA), BI platforms have prioritized robust governance and security. Features like role-based access controls, encryption, and active metadata management ensure data integrity and compliance. Vendors like Snowflake and Databricks have introduced cost-optimizing features to manage cloud data efficiently.

• Data Storytelling and Visualization

  BI tools now emphasize data storytelling, transforming complex data into compelling visual narratives. Platforms like Tableau’s 2022.4 update introduced features like Data Change Radar and Explain the Viz to make insights more actionable. This trend enhances stakeholder engagement and decision-making clarity.

• Cloud and Hybrid BI Adoption

  Cloud-based BI has seen a boom, with 91% of banking and insurance firms adopting cloud solutions in 2023. Hybrid and multi-cloud setups offer scalability and flexibility, supported by vendors like Microsoft Azure and Salesforce. This shift reduces infrastructure costs and supports remote work environments.

• Collaborative BI and Partner Ecosystems

  Collaborative BI tools facilitate team-based decision-making by enabling real-time sharing of insights. Partner ecosystems, like Salesforce AppExchange or Atlassian Marketplace, integrate BI with other enterprise tools, enhancing interoperability. This fosters innovation and expands market reach for BI solutions.

These changes reflect a shift from static, centralized BI to dynamic, user-focused systems that integrate seamlessly with business processes. By leveraging AI, cloud technology, and self-service tools, enterprises can overcome traditional BI challenges and drive faster, more informed decisions. Platforms like InetSoft, Tableau, and Qlik are at the forefront, aligning BI delivery with modern business needs.

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