D365 Data Management Framework Import Worksheet Template
A Dynamics 365 data migration succeeds or fails on discipline: load sequence, row counts reconciled to source and a clean record of errors. This worksheet gives you the tracking table most project managers build by hand, with an error rate calculated per entity.
| Seq | Entity | Legal entity | Source format | Skip staging | Rows in file | Rows in error | Error rate | Run date | Status | Owner | |
|---|---|---|---|---|---|---|---|---|---|---|---|
0% | |||||||||||
0.7% | |||||||||||
0.2% | |||||||||||
0% | |||||||||||
1.4% | |||||||||||
0.8% |
Track each data project execution, not just the final load. Record the data project name and execution id in your notes column outside this table when you export. Keep a separate log of mapping and defaulting decisions for each entity.
Automated reconciliation for your D365 migration
We can review your load plan and discuss automated source-to-D365 reconciliation. Optional, the worksheet stands alone.
Optional. The tool and every export work without this. No spam.
How to use the worksheet
Add one row per entity load in sequence order. After each execution in Data management, record row counts from the source file and the number of rows in error from the execution summary. The error rate column and the overall rate update automatically. Export to Excel to share with the project team or attach to cutover sign-off.
- One row per entity per legal entity
- Lower sequence numbers load first
- Record the owner who signs off each load
- Re-run counts after every correction pass
How DMF imports work
In the Data management framework, a data project holds entities, each with a source format and a sequence. Files are first loaded into staging tables, validated, and then copied to target tables. Staging gives you an error view before data lands in the live tables, which is why skipping staging should be limited to cases you have tested. You can also set parameters such as the number of tasks for parallel processing on large entities.
Reconciliation after the load
Row counts are not the end of reconciliation. Compare business totals: on-hand quantity and value, open order value, count of active BOMs, vendor and customer counts. Record deviations and the decision on each. For cutover rehearsal, store the timings for each entity so you can build a realistic downtime plan from measured data.
Common mistakes
Frequent failures include loading dependent entities before their parents, ignoring warnings that become errors later, loading in the wrong legal entity, and fixing errors in the target instead of the source so the next rehearsal repeats them. Treat the source file as the master and correct there.
Frequently Asked Questions
What is the Data management framework in D365?
It is the built-in toolset for importing and exporting data through data entities. You create data projects, add entities with a source format, upload files, and run import or export jobs. Data lands in staging tables first, then moves to target tables after validation.
How do I choose the load order?
Use the dependency order of the data: organization and calendars, product and units, resources and routes, BOMs, then partners and open transactions. Within a data project, set sequence numbers on entities so parents load before children.
Should I skip staging?
Only for tested, high-volume loads where you accept less visibility into errors. Staging gives you an error view and the chance to correct and re-run. Most teams keep staging on for rehearsals and decide on exceptions with evidence.
What error rate is acceptable?
For master data cutover the target is zero unresolved errors or explicit, signed-off exclusions. Early rehearsals often show a few percent, which is normal, as long as each error category is understood and the rate falls with every pass.
If you want help automating the checks and reconciliation between your legacy ERP and D365 data, we can scope that with you.
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