A D365 Finance and Operations reporting issue I had recently:
How do I report on all published WBS activities by their related projects?
Well, the activities table (smmactivities) doesn’t have a project id field.
If you are here for that specific question, the necessary table relationships are:
But I was interested in the process of doing this more than the specific reporting task. A basic way to do this could be to dump those tables into excel, then use a bunch of vlookups to add the associated project data to the activity rows.
Nothing wrong with that, but the final product would be a bit clunky…the whole smmActivities table, with a few extra columns. You could then delete or hide the unnecessary columns, but if you need to create the report again you’ll have to redo those same operations. If you need to add some attribute, you’ll have to do more vlookups (or xlookups, or index matches, whatever your preferred Excel operation). Is there a better way?
Introducing Power Query
Power Query is a tool to get and transform data in excel. In the example below, I exported the 4 desired tables, pointed to them as data sources, joined them together in Power Query, and then used Power Query to clean up my reporting output.
Here’s a video of that effort:
Reasons to Use Power Query
A Better Way to Get Data
Power Query can connect to other tables in your excel file (like in my example above). Power Query can also be used to connect to other external data sources. In a more sophisticated reporting example, there is probably a way I could connect directly to a D365 data entity. I’ll look into that more in the future.
A Better Way to Transform Data
I found Power Query to be a really pleasant experience for transforming data. A frequent D365 data migration issue is you’re given some legacy file, with some legacy file headers, which needs to be formatted into a D365 structure of columns and headers.
Instead of hacking away at the source data, which would be my first excel instinct. Power Query lets you add columns or rename headers programmatically…making it simple to redo the changes if you later get a NEW file of legacy data that also needs to be transformed.
I particularly like that Power Query shows a list of “applied steps”, which makes it easy to follow the transformations that take place between the original and transformed data.
My first-time user experience is that Power Query is a great tool, and I can see it becoming an integral part of improving D365 data migration projects.