In this post we are going to cover real-world manager scenarios for Microsoft Purview: the questions a hiring manager asks once they know you understand the features, and want to see how you would actually run Purview on a project. These are 7 real Purview interview questions, asked the way they come up on a real project, and the last one is the final-round classic: what does Purview not do, and what do you pair it with?
Manager questions are less about where a setting lives and more about judgment: how you plan a rollout, what you tell a regulator, why the bill went up, and why nobody uses the catalog. Interviewers ask them because this is the day-to-day job of a senior data governance engineer, and because honest answers about the limits are what build trust.
Part 10 of the Real Time Microsoft Purview Interview Questions and Answers series on TechBrothersIT.
- The short answer
- Question 1: You have ninety days to roll out Purview data governance for a mid-size company. What is your plan?
- Question 2: Your data estate is Fabric, Azure Databricks and Snowflake. What does Purview see in each one, and where are the gaps?
- Question 3: The Purview bill doubled last month. How do you find out why and bring it down?
- Question 4: Business users say nobody uses the catalog. How do you get adoption?
- Question 5: A regulator asks you to prove you know where personal data lives and who can access it. What do you show?
- Question 6: A team wants to put Purview data products in front of AI agents and Copilot. What do you check first?
- Scenario 7: In the final round, the hiring manager asks: what does Purview NOT do, and what do you pair it with?
The short answer
Roll out in ninety-day phases around one business question. Know what Purview sees in Fabric, Databricks and Snowflake, watch the governed asset and DGPU meters, and earn adoption with curated data products. Show regulators evidence, check permissions before AI, and be clear that Purview doesn't enforce access at the source.
Keep that in mind. Every question below is one piece of it.
Question 1: You have ninety days to roll out Purview data governance for a mid-size company. What is your plan?
I plan it in three phases of thirty days, built around one business question. Let's walk through them.
Days 1 to 30: foundation.
- Upgrade to the enterprise version, linked to an Azure subscription with pay-as-you-go billing.
- Assign the Purview role groups, and design Data Map domains and collections.
- Scan the sources behind your most important reports.
- Use managed identity and Key Vault for the connections.
Days 31 to 60: the business layer in Unified Catalog.
- Create and publish two or three governance domains, like Finance and Sales.
- Publish them with real owners.
- Add glossary terms.
- Publish the first data products, each with assets and an access policy.
Days 61 to 90: trust and measurement.
- Add data quality rules on those products.
- Turn on health controls and link OKRs.
- Route access requests through the catalog.
- Review the cost in Azure Cost Management every week.
Scanning everything on day one and calling it done. Start with one business question, like the monthly revenue report, prove it end to end, then expand domain by domain.
Question 2: Your data estate is Fabric, Azure Databricks and Snowflake. What does Purview see in each one, and where are the gaps?
Purview gives you one catalog across all three, but what it sees is different in each. Let's start with the comparison:
| What Purview sees | Lineage | Gap | |
|---|---|---|---|
| FABRIC | workspaces, items, lakehouse tables and files | item level; Power BI deeper | no Data Map auto-classification |
| DATABRICKS | Unity Catalog objects, tags, system classifications | column level only from cluster runs | deletes not detected |
| SNOWFLAKE | tables, views, procedures, classification, labels | static, from definitions | no incremental scan; key pair auth |
Now one at a time.
- Fabric. One tenant scan brings in the workspaces and items, with live view. Lineage is item level, with more detail only for Power BI. Lakehouse tables and files are scanned without sub-item lineage, and the Data Map doesn't auto-classify Fabric data.
- Azure Databricks. The Unity Catalog connector brings in catalogs, schemas, tables, views and columns, plus tags. Only system classifications run. Lineage comes from Unity Catalog system tables, and it's column level only for notebooks run on clusters, not SQL warehouses. Deleted objects aren't removed on the next scan.
- Snowflake. Tables, views and stored procedures, with classification and labels. Lineage is static, built from the definitions. There's no incremental scan, and you use key pair authentication, because Snowflake turned off password sign-in for service users.
One more thing about Fabric: labels and DLP for Fabric come from the data security side of Purview, not from the Data Map scan.
One catalog across all three. Deep lineage and access control still live in each platform.
Question 3: The Purview bill doubled last month. How do you find out why and bring it down?
First, know the two data governance meters:
- Governed assets: every asset linked to a data product, a critical data element, a glossary term or a data quality rule, counted once per day.
- DGPUs: processing units for data quality and health management.
Scanning into the Data Map isn't billed under this model.
Then find the driver:
- In Azure Cost Management, break the Purview cost down by meter.
- The Unified Catalog usage monitoring report, in preview, splits usage by governance domain.
- Check the security meters too, like protection policies or insider risk for Fabric, which are pay-as-you-go as well.
The usual causes: a team linked hundreds of assets to new data products, or data quality scans multiplied, with more rules, more runs, bigger tables, or a higher SKU. Health controls also run daily once they're on. Here is what drives each meter and how to cut it:
| Meter | What drives it | How to cut it |
|---|---|---|
| GOVERNED ASSETS | assets linked to products, CDEs, terms, DQ rules, per day | unlink what nobody uses |
| DGPUs | DQ rules, runs, data size, SKU, daily health controls | incremental scans, fewer runs, Basic SKU |
| SECURITY PAYG | protection policies, insider risk for Fabric | scope to what matters |
To bring it down: unlink assets nobody uses, switch to incremental data quality scans, reduce schedules, stay on the Basic SKU where it's enough, and reschedule health controls. Then set a budget alert.
Check the pricing page and calculator. Prices change.
Question 4: Business users say nobody uses the catalog. How do you get adoption?
Usually the problem is that the catalog is thousands of technical tables. Business users don't search for table names. They want answers: where is the trusted sales data, and can I use it?
So let's fix it in three steps.
First, curate. Publish a small number of data products in Unified Catalog for the top business questions, each with:
- An owner.
- A clear description.
- Glossary terms.
- A data quality score.
Mark the good ones as endorsed. Data product search also works in plain language, which is how business users actually search.
Then, put the catalog in the path of work. Make it the way to request access, so people come to it for a reason. Name a data steward in each domain as the go-to person, and link the catalog from the reports people already use.
Finally, measure it. Health controls show missing owners, descriptions and terms, and the classic catalog adoption report shows who actually uses it. Fix the gaps, and report progress as an OKR.
Question 5: A regulator asks you to prove you know where personal data lives and who can access it. What do you show?
You show evidence, one question at a time. Let's go through it in order.
- Where it lives. Data Map scans classify personal data across your sources, and you can filter the catalog by classification, owner and collection. The classification and sensitivity label reports show coverage. For Microsoft 365 data, data explorer and DSPM show where sensitive files sit.
- Who can access. Be honest: Purview doesn't enforce access in your databases. Show the source permissions, like SQL roles, Fabric workspace roles and Unity Catalog grants, plus the access requests and approvals recorded in Unified Catalog.
- Who did access. Audit shows who opened, shared or exported data, and activity explorer shows label and DLP activity.
- How it's protected. Sensitivity labels, DLP policies and their alerts.
- Which rules. Map it to the regulation with an assessment in Compliance Manager, which tracks controls and improvement actions.
Here is the full evidence pack:
| Regulator asks | What you show | From |
|---|---|---|
| WHERE IT LIVES | classified assets, label coverage | Data Map, reports, DSPM |
| WHO CAN ACCESS | source permissions + approved requests | SQL, Fabric, Unity Catalog, Unified Catalog |
| WHO DID ACCESS | opened, shared, exported | Audit, activity explorer |
| HOW PROTECTED | labels, DLP policies, alerts | Information Protection, DLP |
| WHICH RULES | assessment, improvement actions | Compliance Manager |
Regulators want the same evidence again and again, so schedule these reports instead of building them once by hand.
Question 6: A team wants to put Purview data products in front of AI agents and Copilot. What do you check first?
I check four things, in this order.
- Permissions at the source. Copilot and agents return only what the user can already access, so any oversharing becomes an AI answer. And a data product's access policy in Purview doesn't grant or enforce anything at the source.
- Labels. Make sure the sensitive data is labeled. Copilot-generated content inherits the source file's label, and encrypted content is only used when the user has both view and extract rights.
- Guardrails. A DLP policy for the Microsoft 365 Copilot location can block prompts with sensitive information types and stop Copilot processing files with certain labels. DSPM shows how AI apps and agents touch sensitive data, Audit logs each Copilot interaction, and eDiscovery can search the prompts and responses.
- Trust. Check the quality score, the owner and the glossary definitions on the data product before you expose it.
An agent reading a table with a low quality score is still wrong, just faster.
Scenario 7: In the final round, the hiring manager asks: what does Purview NOT do, and what do you pair it with?
Let's go through it one gap at a time.
- It's not an access-control engine for your databases. Data Map labels are metadata only, and the classic SQL access policies retire on October 30, 2027. Pair it with SQL roles, row-level security and masking, Unity Catalog grants, and Fabric workspace roles.
- It doesn't encrypt files in ADLS or columns in SQL, and there's no DLP inside the Data Map. Pair it with Azure encryption and network controls, plus protection policies where they're supported.
- It's not a backup tool, and it doesn't fix data. Back up with Azure Backup. Data quality finds the bad rows, and your pipelines in Data Factory, Fabric or Databricks fix them.
- It's not a SIEM. DLP alerts flow into the Microsoft Defender portal, and Microsoft Sentinel does the wider detection.
- It doesn't grant requested access. Access requests are approved in Purview, but a person or your own automation grants access at the source.
Here is the whole list:
| Purview does NOT | Pair it with |
|---|---|
| ENFORCE DATABASE ACCESS | SQL roles, row-level security, masking, Unity Catalog grants, workspace roles |
| ENCRYPT ADLS OR SQL | Azure encryption, network controls, protection policies |
| BACK UP DATA | Azure Backup |
| FIX BAD DATA | pipelines in Data Factory, Fabric, Databricks |
| ACT AS A SIEM | Defender portal, Microsoft Sentinel |
| GRANT REQUESTED ACCESS | source owners or your own automation |
Saying this shows the manager you know where Purview ends, and that is what makes a governance design work.
Key points to remember
- Roll out in 90-day phases, one business question first
- Know the Fabric, Databricks, Snowflake gaps
- Cost: governed assets per day + DGPUs
- Adoption: curated data products, requests through the catalog
- Purview doesn't enforce access at the source
All 10 parts are listed on the Real Time Microsoft Purview Interview Questions and Answers page on this blog.
Part of the Real Time Microsoft Purview Interview Questions and Answers series on TechBrothersIT. Product names, features and their status (GA or preview) are current as of October 2026. Microsoft changes Purview every month, so check the Microsoft Learn page for anything you quote in an interview.