I previously explained in a blog post what thin reports are and why we should care about them. I also explained Report Level Measures in another blog post. In this post, I try to raise some real-world challenges we face when developing thin reports. I also provide a solution to those challenges.
Report Level Measure Related Challenges
Creating and using Report Level Measures is relatively easy, but there are some challenges that we face from time to time, such as:
- Distinguishing Report Level Measures from Dataset Level Measures
- Report Level Measure dependencies
Determining Report Level Measures from Dataset Level Measures
One of the challenges that Power BI Developers face is creating many report level measures. Unfortunately, Power BI Desktop currently uses the same iconography for both types of measures, making it hard to distinguish the actual measures created within the dataset from the report level measures. It gets even more challenging if we need to write technical documentation for an existing thin report. We have to open the PBIX file of the thin report in the Power BI Desktop and click every single measure. If the expression bar appears, the selected measure is a report level measure; otherwise, it is a dataset level measure.
So unless we use third-party tools, which I explain in this post, we must go through the manual process.
Report Level Measure dependencies
Another pain point related to the previous challenge is finding the dependencies between the report level measures. It is crucial to be aware of the interdependencies when doing impact analysis. We need to understand how a change in a report level measure impacts other report level measures. Again, Power BI Desktop does not currently have any options supporting that, so we have to click every measure and read through the DAX expressions to identify the dependencies or use the third-party tools to save development time.
Dataset and Thin Reports Dependency Challenges
The other challenges are even more difficult to overcome relate to interdependencies between datasets and thin reports. Power BI Service provides a lineage view that shows the dependencies between a dataset and its connected thin reports. But the challenges can get more complex to overcome manually. The following are some real-world examples of more complex situations:
- What if we need to analyse the impact of changes in a dataset measure on all report level measures of the connected thin reports?
- How do we analyse the impact of changes on a dataset measure on all connected thin reports, including the visuals, filters, etc…?
- What if we need to tune the performance and we want to find a list of all unused tables or unused fields?
As you can see, the situation can get pretty complex, so manual operations are virtually impossible.
But there is a third party tool we can use which provides heaps of capabilities with a couple of clicks.
Continue reading “Thin Reports, Real-world Challenges”
