Some tools in Power BI to maintain ‘nimbility’

Inspiration for this post:
Data Engineering podcast, episode 46, “An Agile Approach to Master Data Management“, with guest Mark Marinelli, Head of Product at Tamr.

In the previous post, I described some techniques to enable you to quickly and easily document your mix-in data sets that don’t have the full ‘blessing’ that canonical data sets have. If you listen to the podcast (see above) you will hear Mark Marinelli talk about a concept called “right tool set, right mindset, right skill set”. This concept made a lot of sense to me, and the previous two posts talk about the right mindset and the right skill set.

In this final post of this series, I want to show you some of the features you can use to document the non-canonical data you want to use. (Remember, canonical data is the data that has been extensively vetted by a team of experts.) Your data hasn’t gone through this process, but using some of the features available in the Power Query Editor, Power BI, and the Power BI Service, you can align and document your data set such that others can understand where the data came from, how old it is, and how it is structured. A quick note: none of these videos have sound.

Rename fields so that they align with canonical sources

Power Query Editor: Rename a field so that it matches other data sources

Rename and document a step in Applied Steps

Power Query Editor: rename the field and document the step

Document a query in Properties

Power Query Editor: Document your query (data set) using Applied Steps

Rename a field in the Power BI Desktop

Power BI Desktop: rename a field for all the visuals or just one visual

Provide a description for a data set in the Service

Power BI Service: Use the Certification feature to document your dataset