Power BIte: Turning datasets into dataflows

At this point I’ve said “Power BI dataflows enable reuse” enough times that I feel like a broken record[1]. What does this phrase actually mean, and how can you take advantage of dataflows to enable reuse in your Power BI applications?

This Power BIte video is a bit longer than its predecessors, and part of this is because it covers both the problem and the solution.

The problem is that self-service BI applications often start out as one-off efforts, but don’t stay that way. At least in theory, if the problem solved by the application was widespread and well understood, there would be an existing solution already developed and maintained by IT, and business users wouldn’t need to develop their own solutions.

Successful applications have a tendency to grow. For self-service BI, this could mean that more and more functionality gets added to the application, or it could mean that someone copies the relevant portions of the application and uses them as the starting point for a new, different-but-related, application.

Once this happens, there is a natural and gradual process of drift[2] that occurs, as each branch of the application tree grows in its own direction. A predictable consequence of this drift in Power BI applications is that query definitions that start off as common will gradually become out of sync, meaning that “the same data” in two datasets will actually contain different values.

Moving queries that need to be shared across multiple applications from multiple datasets into a single dataflow is a simple and effective solution to this problem. There’s no dedicated tooling for this solution in Power BI today, but the steps are still simple and straightforward.

P.S. This is the first Power BIte video recorded in my home office. After struggling unsuccessfully to get decent audio quality in my office at work, I’m trying out a new environment and some new tools. I know there’s still work to be done, but hopefully this is a step in the right direction. As always, I’d love to know what you think…


 

[1] For my younger readers, this phrase is a reference to when Spotify used to be called “records” and the most common service outage symptom was a repeat of the audio buffer until the user performed a hard reset of the client application. True story.

[2] Is there a better term for this? I feel like there should be an existing body of knowledge that I could reference, but my searching did not yield any promising results. The fact that “Logical Drift” is the name of a band probably isn’t helping.

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