Microsoft Purview Data Map - Simply Explained

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Hello everyone and welcome to another episode of Microsoft Knowledge Nuggets here on M365,

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FME out Tim and your host, Mirko Peters.

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Think about a normal workday.

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You answer email and outlook, chat in teams, save a file and share point, work from your own one drive

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and open a report built from Azure or Microsoft fabric data.

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Then someone downloads the report, changes a few numbers, and emails a spreadsheet to five people.

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Each app might have solid security.

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The problem is the information moving between them, getting copied, renamed, shared and forgotten.

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By the end of this episode, you will understand

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how Microsoft Perview helps an organization find, understand, protect and manage its data in plain English

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because a secure system can still contain risky data.

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Tell you why data sprawl turns into business risk.

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Imagine you start a company tomorrow.

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At first the data feels easy to manage.

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Sales keeps customer details in one system.

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Finance has its reports.

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HR stores employ you files in another place.

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Marketing has campaign folders.

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Everyone knows where their own work lives.

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Then the company grows.

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A new team starts using a different app.

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Someone builds a database for a project.

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Another team copies the data into a spreadsheet because they need an answer before Friday.

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A business buys another business.

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And now there are old file shares, old reports and old systems that still run somewhere behind the scenes.

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Nothing looks wrong from the outside.

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But the organization slowly turns into an office building with hundreds of locked rooms.

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There are filing cabinets in each room, but many have no clear label.

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Some cabinets contain customer data.

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Some contain old employee records.

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Some contain the latest pricing plan.

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Others contain a copy from two years ago and nobody has a full directory.

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That creates a strange problem.

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People can have secure apps, secure laptops and secure sign-ins

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while the organization still does now know where its most sensitive information lives.

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You wouldn't be probably seen this happen.

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Someone asks, "Oh, where can I find the approved customer numbers for last quarter?"

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All three people send three links.

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Each file looks believable.

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Each report has a different total.

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A meeting starts.

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Not to make a decision, but to work out which number people should trust.

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That is now to be just annoying.

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It slows down the business because people spend time searching, checking, copying and asking

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for access.

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It also creates duplicate work.

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One team builds a report from a data source they trust, while another team builds nearly

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the same report from an older copy.

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No one is trying to cause trouble.

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They are trying to get their work done.

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Let our teams use a simple example.

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A finance analyst needs the current pricing data for a monthly report.

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She searches SharePoint and finds five spreadsheets with almost the same name.

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One comes from sales.

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One comes from finance.

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One lives in an old project folder.

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Another was sent by email six months ago.

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She chooses the file that looks newest.

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Later, the report reaches leadership and someone notices that the prices don't know

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TIEM, yes, match the approved list.

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The analyst did not make the pick the wrong file because she lacked skill.

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She picked it because the organization gave her no clear way to find the right one, see

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who owns it or check where it came from.

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That automata data governance problem.

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And it becomes more serious when sensitive data sits in places people don't know to

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me think about anymore.

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An old project site, a forgotten database, a personal cloud account, a copied customer

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list on a laptop, a report exported from a dashboard and attached to an email thread.

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The data did no time to disappear.

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It just moved outside the view of the people responsible for it.

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That also changes how you think about security.

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Entra ID for example acts like the reception desk for your company.

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It checks who you are and whether you can enter.

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Intune helps manage company devices.

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Defender helps look for threats.

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Those services matter.

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But once a person opens a file, downloads a report or copies data into another app, the

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question changes.

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What information did they take?

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How sensitive is it?

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Where can it go next?

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Is it accurate enough for someone to use?

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This is where many organizations find a gap.

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They protected the building entrance, but they don't know Tim.

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To have a clear view of the papers moving between rooms.

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AI puts even more pressure on that gap.

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An AI tool can only give you a useful answer when it works from data you understand and

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trust.

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If it uses duplicate records, old numbers, or data with no owner, it can produce a very

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confident answer that sends you in the wrong direction.

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The problem is now to know whether people can access data.

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ETA autumn says whether the data deserves their trust.

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Research often puts a price on poor data quality, but you can see the cost without a calculator.

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It appears in misdeed lines, long approval chains, reports that don't know TMT agree and

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leaders who stop trusting the numbers in front of them.

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It also appears after a leak when the first question becomes, "Oh, what information

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actually left?

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AU?"

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If nobody knows where the data lives, that question can take far too long to answer.

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So, the goal is now TMT to lock every file away.

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People still need data to do their jobs.

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The goal is to give the organization a shared view of what it has, what it means, who owns

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it, and how it should be handled.

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Microsoft PerView fits into that picture as a connected control room for data, rather than

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another place where you store it.

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What Microsoft PerView actually is.

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Microsoft PerView helps an organization govern, secure, and manage data wherever that data

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lives.

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That sounds broad because it is.

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The view is now to make a place where you move every document, database, and report.

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It does know to make replace SharePoint, Exchange Online, Azure, or Microsoft Fabric.

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Those services still store and process the information they were built for.

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PerView adds the rules, context, and visibility around that information.

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Many people first hear about PerView during a compliance project, so they assume it out

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to miss, only for legal teams filling out forms.

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That opens too narrow.

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Others see a data catalog and think PerView only helps analysts search for tables and reports.

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It opens also to narrow.

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PerView brings several related jobs into one connected platform.

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It helps teams understand their data, it helps protect sensitive information, it helps keep

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records for the right amount of time, and it helps the right people investigate when something

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looks wrong.

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Picture a large office building from a different angle.

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The apps where people work are the offices, meeting rooms, and storage areas, Outlook handles

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messages, Teams handles conversations, SharePoint holds team files, OneDrive holds personal

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work files, Azure and Fabric call databases, reports, and data used for analysis.

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PerView is the set of information and rules that helps the building run safely.

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It acts like the directory that tells you what exists and who looks after it.

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It acts like the filing rules that explain what belongs in a cabinet, what a folder means,

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and how long the folder must stay.

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It acts like the security signs on a door that tell people, oh, this information is confidential.

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Don't know what made SharePoint outside the company.

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AO it also acts like the records room and the incident desk, where an organization can

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look back at actions, keep evidence when needed, and investigate unusual activity.

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The point is not met, to turn work into paperwork.

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The point is to let people work with data, while the organization applies clear rules around

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that data.

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PerView connects with Microsoft 365, so it can work with information in exchange online,

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SharePoint, OneDrive, Teams, and other Microsoft 365 services.

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It also connects with Azure and Fabric, where many organizations keep and analyze business

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data.

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Depending on the PerView capability and the connector available, it can also work with

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supported data sources outside Microsoft.

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That matters because very few organizations run every system from one company.

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You might have business data in Azure, customer data in a different cloud service, reports

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in Fabric, and documents in SharePoint.

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PerView helps create a clearer view across those places, rather than forcing every team to

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use the same storage system.

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It can also work with information on devices and in apps where people create, copy, share,

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or use company data.

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This is where people often mix up platform security and data protection.

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EntraID manages your digital identity.

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Think of it as the system that checks your name, your sign-in, and whether you can enter a service.

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It helps decide who can open the door.

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PerView focuses on the information once someone is inside.

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For example, a person may have permission to open a customer report.

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That permission can be correct.

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Yet the report might contain private customer details, and the person might try to attach

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it to an email sent outside the company.

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EntraID helps confirm that the person is really that employee.

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PerView helps the organization understand the information in the report and apply handling

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rules when the employee tries to share it.

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Those are different jobs, and you need both.

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You can think of PerView in three connected areas.

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First, data governance.

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This helps people find data, understand what it means, see who owns it, and judge whether

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they can trust it.

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Second, data security.

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This helps identify sensitive information and apply protection when people use or share

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it.

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Third, risk and compliance.

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This helps organizations keep records, review activity, support legal cases, and look into

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behavior or events that need attention.

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These areas overlap because data does no TMRT stay in one neat place.

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A finance table can feed a fabric report.

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That report can become a PowerPoint slide.

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The slide can appear in a Teams chat.

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A copy can then leave in an email.

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Treating each moment as someone else out, Thames problem creates gaps.

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PerView helps teams use a shared set of rules and a shared view of the information, even

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while that information moves through different services.

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But finding a data source and knowing its owner only solves part of the problem.

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A catalog can tell you that a customer list exists.

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It can't outmeteer by itself stop someone from sending that list to a personal email address.

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So the next building block starts with discovery because you can't outmeteer apply sensible protection

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to information your organization has no tim and found or understood.

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First building block, find name and trust data.

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The first job is simple to describe.

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Before you can manage data, you need to know it exists.

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PerView starts with the data map, which acts as a technical inventory of your connected data

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sources, showing the systems, databases, tables, reports, and other data assets your organization

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uses.

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Most of a large warehouse with thousands of boxes, the data map does not amount to take every

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box away and move it into one new warehouse.

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Instead it records what the boxes are, where they sit, what they contain at a high level,

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and how they connect to other boxes.

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That information about data is called metadata.

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Metadata means data about data, a table name, its columns, its owner, where it lives, when

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it changed, and what classifications apply are all examples.

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PerView can collect and organize this information without copying all the underlying customer records

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financial figures or files into PerView itself.

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That separation matters, your Azure database stays in Azure, your fabric data stays in fabric,

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a supported external source stays where it already lives.

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PerView helps people see and understand the information without turning into the new home

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for every piece of data.

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Technical details help IT teams, but most business users do now, TMLD, search for a server

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name.

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They search for something like, "Aew approved pricing data, Aew, Aew monthly customer figures,

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Aew or Aew the report used by finance."

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It outs at albums where the unified catalog comes in.

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The unified catalog gives people a business-friendly place to search for data they can use.

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Instead of asking around, until someone sends a link, you can search for a data product

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with a clear description, a named owner, its approved uses, and the rules around access.

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A data product is simply a useful group of related data put together for a business purpose.

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Imagine the finance team publishes a pricing analytics data product.

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It might include a source table from Azure, a cleaned table in fabric, and the approved

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report people use every month.

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Rather than telling everyone to hunt for the right file, the team can describe the product,

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explain what it covers, and name the people responsible for it.

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That gives users a better starting point.

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The catalog can also use a business glossary, a glossary helps everyone use the same words

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for the same thing.

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For example, does O-Active customer O mean someone who bought something this month, this

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year, or ever?

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If sales, finance, and marketing each use a different meaning, reports will never fully

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agree.

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A plain English definition gives the organization one shared answer.

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Pervue can group these products into governance domains too.

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You might have a finance domain, a sales domain, or a customer domain.

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Each domain helps show which part of the business owns the data, and who should make decisions

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about it.

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Ownership does not mean one person knows every technical detail.

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It means someone accepts responsibility for what the data means, whether it is fit for

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use, and how people should request it.

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Now this next part is where trust enters the picture, finding a table named, "How

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customer pricing, O-O, does now Tim, to prove that it is correct."

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You also need to know where the data came from, and what happened to it along the way.

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Pervue can show data lineage.

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Lineage is the trail behind a number.

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If you see a total in a fabric report, lineage can help show the source table it came from,

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the steps that changed it, and the reports or data products that now use it.

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So if a source field changes, a data team can see which reports may need checking.

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It also gives business users a chance to ask a much better question than, "How can I access

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this?"

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"How?"

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They can ask, "How can I trust this for the decision I need to make?"

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AO Data Quality helps answer that question.

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A data owner can set rules, such as checking whether required fields are empty, whether customer

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IDs exist in the right reference list, or whether values look unusual.

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Pervue can run those checks, produce quality scores, and raise alerts when a rule fails.

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An accessible report is not always a trusted report.

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That difference can save a team from building a decision around incomplete or outdated information.

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You might also see an option to request access through the catalog.

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That request can go to the data owner with a reason for why you need the data and what

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you plan to do with it.

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But the catalog does new, "Termint" replace the access controls in the original system.

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Pervue can guide discovery and approval.

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The source system still controls the actual permission to open the data.

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Once data has a name, an owner, a meaning, and a trail behind it, the organization can

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start handling it with more care.

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Second building block, "classify and protect sensitive information."

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Once people can find trusted data, the next question is how they should handle it.

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You may already know the most familiar part of Pervue.

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In Outlook, Word, Excel, or PowerPoint, you might see label choices such as public, internal,

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confidential, or highly confidential.

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Those labels are not just decoration.

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They tell people what kind of information they are working with, and they can trigger

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protection rules behind the scenes when the organization sets them up that way.

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First Pervue needs to spot sensitive information.

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That could mean payment card details, health records, home addresses, passport numbers,

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passwords, employee details, or a company out, templates, as plans for a product that

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has not launched yet.

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Pervusoft includes many built-in ways to recognize common types of sensitive information,

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and an organization can also create its own rules for information that only matters to them.

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For example, a bank might look for account details, a health care provider might look for

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patient information, a manufacturer might look for its product codes and design documents,

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Pervue can then apply or suggest a sensitivity label based on what it finds.

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A user can also choose a label themselves when they know the document needs special care.

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Think of a sensitivity label as a clear handling instruction attached to the information.

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A label called Confidential might add a header or a watermark to a document.

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It might want someone before they share it outside the organization.

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It might encrypt the file so only approved people can open it.

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It might also limit what recipients can do, such as stopping them from forwarding an

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email or printing a document.

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The exact outcome depends on the policy behind the label.

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That is important, because labels should match how people actually work.

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If every file receives the strongest label, people will either get blocked from normal

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work or stop taking labels seriously.

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A useful label policy gives people simple choices that fit real situations.

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Public means it is safe to share.

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Internal means it stays inside the company.

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Confidential means pause before you send, copy or upload it.

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This brings us to data loss prevention, usually shortened to DLP.

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DLP watches for sensitive information when someone tries to do something risky with it.

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That might mean sending an email outside the organization, copying content to a USB drive,

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uploading a file to personal cloud storage or sharing a document with the wrong group

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of people.

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A sensitivity label and DLP work together, but they do different jobs.

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The label identifies information and describes how it should be handled.

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DLP checks an action as it happens and can warn the person, block the action or record

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it for review.

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Imagine an employee finishing some work at home.

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They have a customer list in an Excel file and they decide to upload it to a personal storage

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account because it feels quicker than using the company R/TMSS approved tools.

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Without protection, the file leaves the company in seconds.

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With the right DLP policy, Perview can recognize the customer information and respond before

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the upload completes.

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The employee may see a message explaining that company customer lists cannot go to personal

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storage.

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Depending on the rule, they might be able to provide a business reason or the upload might

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stop completely.

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That small moment can prevent a much larger problem and it does not always need to feel

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like a hard stop.

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User coaching is one of the more practical parts of Perview.

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A policy tip can explain what triggered the rule and point people toward a safer option.

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Maybe the employee needs to share the file through a protected SharePoint site.

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Maybe they need to remove private fields first.

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Maybe they need approval from the data owner.

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People make mistakes when rules are hidden.

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Clear guidance at the moment.

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Someone shares information, gives them a chance to do the right thing, without turning every

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action into a support ticket.

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Organizations usually begin carefully here.

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They often run policies in a mode that records activity or shows warnings before they block

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anything.

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That lets the team see how often the rule triggers and whether normal work would be affected.

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Then they can adjust the policy based on real use.

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Still, stopping a risky email or upload only covers one kind of risk.

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Sometimes the concern appears in a pattern of actions over time, when an unusual series

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of downloads, copies or messages needs more context than one rule can provide.

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Does?

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Third building block, manage risk, records and investigations.

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Not every data problem happens when someone clicks send.

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Sometimes an organization needs to look back and answer a simple question.

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Who did what?

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When and with which information?

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That is the job of audit.

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An audit log records actions across supported services.

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It can show that someone shared a file, deleted content, changed the setting, searched for information

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or signed in and used a service.

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It does not decide whether that action was good or bad.

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It gives the people responsible a record they can review.

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Imagine a team notices that a confidential folder suddenly has different permissions.

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Instead of guessing, they can look for the actions around that folder.

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Who changed the sharing setting?

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When did it happen that did anyone download files afterward?

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Those details help the team understand the event without relying only on memory or email

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threads.

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Per view also helps manage how long information stays around.

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The organization keeps some information longer than it wants to.

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Old emails, project files, contracts, employee records, meeting notes.

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Some of it needs to stay because of law, company policy or a business reason.

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Other content should disappear after a set time.

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Because keeping everything forever creates more risk and more clutter.

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Retention policies set those rules.

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A policy can tell a service to keep content for a period of time, deleted when that period

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ends or do both in the right order.

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Records management takes this one step further for information that must remain unchanged

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and kept as an official record.

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Think about an approved contract.

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You may need people to read it, but you do not want anyone quietly changing or deleting

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the final version.

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A record rule helps protect that official copy for the required period.

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Then there is e-discovery.

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That name sounds technical, but the idea is straightforward.

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When a legal case, internal review or formal request needs evidence, e-discovery helps

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approve teams search and review business content across places such as email, teams, share

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point and one drive.

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They can collect relevant files and messages into a case, preserve them when required,

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and review them without asking every employee to search their own inbox.

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This does not mean per view turns every conversation into a legal case.

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It means the organization has a controlled process when it genuinely needs to find evidence.

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Some risks also come from unusual behavior rather than one file or one message.

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Inside a risk management can help teams spot patterns that deserve review.

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For example, someone may begin downloading far more files than usual shortly before leaving

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the company or repeatedly copy sensitive data to places that do not fit their normal work.

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A pattern is not proof of bad intent.

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People can have valid reasons for unusual work, so these signals need careful review by the

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right people.

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Per view gives investigators context.

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It does not label someone guilty.

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Communication compliance works in a similar way, where company rules or legal duties require

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it, an organization can set policies that review workplace messages for certain risks.

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That could include harassment, threats, sharing sensitive details or language that breaks

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a regulated industry rule.

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The policy should be clear, limited and handled by authorized reviewers.

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People deserve that care.

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Now, file names and labels only tell part of the story.

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A file called "O" budget finaleau might contain routine figures, or it might contain plans

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that would damage the business if shared.

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During an investigation, teams often need to understand the content and its context, not

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just the name stamped on it.

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Per view can help teams search large sets of files, emails and messages, then narrow their

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review to content that appears related to the case.

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Through AI-supported tools can assist with that sorting and analysis, which saves people

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from opening thousands of items one by one, but the decision still belongs to people.

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Per view does not replace legal advice, human judgment or the security controls in the

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systems where data lives.

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It gives the people responsible better records, better search tools, and more context when

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time matters.

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Next, let out teams follow one piece of customer data and see how these per view parts connect

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as it moves through everyday work.

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How the pieces work together.

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Data can start in a business system, feed a fabric report and appear in a team's discussion.

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Per view adds ownership, meaning, quality checks, labels, sharing rules, retention and an

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audit trail along that path.

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Start small, then build control.

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Start with one risky area.

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Name and owner define the data clearly and test the policy before expanding.