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Where your Dynamics 365 data lives and how to reach it
Dataverse
Sales, Customer Service, Field Service and Power Apps store their data in Dataverse. Microsoft documents its tables, relationships and security roles well. So it makes a reliable source for analytics once you understand the option sets and lookups.
Business Central
Business Central keeps its own database. Data comes out through API pages, OData web services, or export tools that write to a data lake. Ledger entry tables carry dimensions, which are what most finance analysis depends on.
Finance and operations apps
You can export Dynamics 365 Finance and Supply Chain Management data to a lake or to Fabric. You can also link many of their tables through Dataverse.
Everything else
Payroll, ecommerce, banking and planning files rarely live in Dynamics. A useful data model admits that and brings them in with clear keys, rather than pretending the ERP holds everything.
Choosing how data leaves Dynamics 365 for analytics
Dynamics 365 data analytics with semantic models: define each measure once
Most reporting arguments come from the same word meaning different things. Gross margin in the sales report excludes freight; in the finance pack it includes it. Both are right by their own logic, so the meeting goes to waste.
A Power BI semantic model fixes this by holding the tables, relationships and measures in one place. Reports connect to it rather than rebuilding the logic each time. We build these models around your chart of accounts and dimensions and document each measure in plain English. We also use certified or promoted labels in the Power BI service so people can tell the approved model from a personal copy.
Row-level security in the model follows the same idea. For example, a regional manager sees their region because the model says so, not because someone filtered a page.
Dynamics 365 data quality checks worth running before any dashboard
- ✓Ledger entries with blank or blocked dimension values.
- ✓Customers and vendors duplicated under slightly different names.
- ✓Items with no category, unit of measure or cost.
- ✓Records whose owner or salesperson has left the company.
- ✓Totals in the model reconciled to the trial balance for each closed period.
- ✓Refresh failures and late loads alerted to a named person, not a shared inbox.
Governance that stays light enough to follow
A named owner per model
One person in the business answers for what each measure means and approves changes to it.
- ✓Measure definitions written down
- ✓Change requests logged
- ✓Owner listed on the model
Workspaces with purpose
Development, test and production workspaces keep draft work away from the people who make decisions on the numbers.
- ✓Deployment pipelines
- ✓Security groups, not individuals
- ✓Sensitivity labels where needed
Retire what nobody opens
Usage metrics show which reports earn their keep. We archive unused ones, so the useful ones are easy to find.
- ✓Quarterly usage check
- ✓Archive before delete
- ✓One home page per audience
Common questions about Dynamics 365 data and analytics
Do we need Microsoft Fabric, or is Power BI enough?
Power BI alone is often enough for smaller companies, as long as data volumes are modest. It can connect straight to Business Central or Dataverse. However, Fabric earns its place when you combine several sources or need history the apps do not keep. It also helps when refresh times keep growing. We look at your volumes and sources before recommending either.
Can Business Central use Synapse Link like Dataverse apps do?
Synapse Link and Link to Fabric are Dataverse features, so they do not apply to Business Central directly. Instead, Business Central data leaves through its APIs or lake export tools. One option is a widely used open-source extension that writes to a data lake or Fabric. The right choice depends on volumes and who will maintain it.
Why do our Power BI numbers not match the trial balance?
Usually because the report reads a different table, applies a different date, or drops entries with missing dimensions. Sometimes someone added a filter to one page and forgot it. We trace each difference back to its cause. Then we build a reconciliation check into the model, so it cannot drift again unnoticed.
Who should own the data model inside our company?
Ideally someone in finance or operations who understands the business meaning, supported by a person with technical skills. Placing ownership only with IT tends to produce correct but unused reports. We help you set up both roles and hand over documentation they can maintain.
Talk to us about your project.
Tell us what you run today and what has to change. A senior consultant replies with a written next step.