In the data management workspace, if you don’t see a data entity that you expect to see, try refreshing the entity list. This is particularly the case when a new data entity is created, or a trail environment is first spun up.
“Manual data entry builds character,” –Joel Leichty “Character gives us qualities, but it is in our actions–what we do–that we are happy…or the reverse,” –Aristotle
If you need to paste multiple values into multiple places, WIN+V should be your new best friend. Where regular CTRL+C copies something and CTRL+V pastes that last thing you copied, WIN+V allows you to select from your history if previous items copied.
“Data Violates Integrity Constraints” is an error I encounter too often. If you get this error, perhaps this post will help you push past your failure.
In the scenario below, you try to import excel data through a data entity, but get a failure error.
That’s fine you say, I’m a professional. So you click view execution log to troubleshoot the issue.
If you try to view the staging data, you’ll see no staging data has loaded. If you click on Staging log details, you’ll get a curious error message: The data value violates integrity constraints.
This is curious, because it seems you haven’t loaded any data at all, let alone some data that would have triggered a validation error. You re-check your excel file, and the data you wanted to load seems correct.
So What’s The Problem? How do you fix it?
Frequently, the issue is there are some “blank” rows at the bottom of your excel data that are throwing off the upload. Data Management is trying to prevent you from importing those blank rows. Highlight the row below your data, press CTRL+SHIFT+DOWN and delete all the rows below your data. To be safe, you can do the same thing to the far right to clean up any columns that may be causing trouble as well.
Then, just like wherever else we encounter failure, set it up and try, try again.
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.