<img src="https://secure.leadforensics.com/133892.png" alt="" style="display:none;">

Have you been trying to get a massive data file into D365 and found out that 150,000 records were imported successfully but about 600 errored out?

Then you start thinking, “ugh, I'll have to go over each one of those records and figure out why D365 rejected them. Why isn’t there a way to generate a file with all the errors and the records we tried to import?!” 

Well, guess what? There is a way to do it. Get your Chrome browser ready, a “vlookup” and… voila!

Let’s do it!

First, download this cool Chrome extension called Table Browser Caller for D365FO (I know, I'm using Chrome, but unfortunately this is not available for Edge or Internet Explorer).

Once installed, configure the Table Browser Caller to point to as many environments as you wish. Once you’ve selected your environment and the right company, click on Table list. (If you know the name of the table you are looking for, just past it in the search bar and hit enter.)

y1 y2
The table that holds the staging errors for all the Data Management jobs is called "DMFStagingValidationLog".

This table might not be exposed on the table list, so just go ahead and type the name on the Table Browser Caller search bar and hit enter.


We'll focus on the four table fields below:

  • ErrorMessage: Contains the import error for each record.
  • Execution ID: A Data Management Import job generates a Job ID each time it is used. This ID can be found under the Job History form (navigate to the Data Management workspace, open the Data Project and click Job History).
  • Staging Table Name: This is the second table we'll need to extract in order to match the error message with the staged record. The "StagingTableName" will change based on the entity used for the import.
  • Staging RecID: Identifies the staged record. Will be used to “vlookup" primary key to match an error message with its staged record.

Use the column "ExecutionID" to filter the Job ID you're looking for.





In our example, the "StagingTableName" is "VendInvoiceJournalLineStaging," as we are trying to import AP Invoices via an AP Invoice journal.

Using the Table Browser Caller, open the staging table and use the "ExecutionID" table field to filter on a specific executed job. Then use the "RecID" table field to match the record with its error message.




So there you have it, with the help of the D365 Table Browser, you can export all the staging data error messages and their associated records. Happy exporting!

Next read: Is it that easy to enter an order in Business Central from Outlook?  Yep.


Discuss this post

Recommended posts

Data analytics have drastically changed the nature of competition across multiple industries, according to 47% of respondents in a recent McKinsey Global Survey. Companies leveraging analytics saw the most overall revenue growth in the survey.
Back in 2017, Gartner reported less than 10% of enterprise Internet of Things (IoT) projects involved an artificial intelligence (AI) component. At the same time, they also predicted that this percentage would leap to over 80% by 2022. Today, industries are so frequently using these technologies in tandem that some people are asking a somewhat contrarian question, “Can you have IoT without AI?”
It’s a common question: Does my company need to use Microsoft Dynamics 365 solutions across our entire operation to see tangible results? In short no, not necessarily. You can benefit from running just a few of your operations on Microsoft. Microsoft Dynamics business applications are designed to address specific business issues while working in conjunction with other solutions.
The Purchasing Managers Index (PMI) – a widely recognized leading economic indicator – registered at 47.2% in December, below the 50% that indicates the manufacturing sector is expanding. It was the lowest reading since June 2009. 
Data has been a very hot topic among clients lately. Specifically, I keep getting asked: "How can I create a strategy and plan around my data?" Most people I talk to are working for companies that collect data at every turn of the supply chain. This data might come from heavy equipment machinery or e-commerce metrics or financial growth numbers—the point is, it's usually contextually diverse and there's a lot of it.
right-arrow share search phone phone-filled menu filter envelope envelope-filled close checkmark caret-down arrow-up arrow-right arrow-left arrow-down