One of the easiest and most direct ways to track user engagement and measure BI adoption is through the built-in usage analysis offered within many BI platforms like Power BI, Tableau, Qlik and others. These reports provide insight into how users interact with the platform, what content they consume, and the overall usage trends.
While many BI tools have this in-built functionality, the level of detail they provide varies significantly.
For instance, Tableau offers quite sophisticated usage tracking features through its built-in monitoring capabilities. Administrators can measure user engagement, content consumption, and system performance. Other popular BI platforms like Looker, QlikView, and MicroStrategy also provide their own built-in usage analysis capabilities. They allow pretty much the same scope of insights: user activity, content usage, and system performance.
Meanwhile, one of the most popular tools - Power BI - provides quite limited analytics with their Usage Metrics Report - it allows users to identify who has viewed their reports, when they were accessed, and which pages and platforms were used. However, they provide only 1 month (3 in the old version) of historical data, which is not enough to understand usage trends and build a strong data strategy.
At the same time, if the built-in analysis was as good as it seems from the outside, all our BI environments would be in perfect order and BI adoption reaching sky levels. Yet, it doesn't happen. And the limitations are to blame.
All inbuilt usage analysis functions have their own restrictions. Different dimensions for analysis, not aligned data structures, and different timeframes don't allow deep analysis, especially if a company has a multi-tool BI environment. This can be a challenge for organizations that require long-term historical data for trend analysis, user behaviour patterns, or security purposes.
Customization - or rather the lack of it - comes as another restriction. While the built-in usage analysis features provide fast insights, they may have predefined metrics, visualizations, or groupings. This can limit the depth of analysis or the ability to tailor the reports to specific organizational requirements. Businesses aiming for advanced analytics management or requiring specific metrics will be bound hand and foot.