Data Loss Prevention (DLP) in Microsoft 365 Business Premium is a set of compliance features designed to identify, monitor, and protect sensitive information across your organisation’s data. It helps prevent accidental or inappropriate sharing of sensitive data via Exchange Online email, SharePoint Online sites, OneDrive for Business, and other services[1][1]. By defining DLP policies, administrators can ensure that content such as financial data, personally identifiable information (PII), or health records is not leaked outside the organisation improperly. Below we explore DLP in depth – including pre-built vs. custom policies, sensitive information types and classifiers, policy actions (block/audit/notify/encrypt), user override options, implementation steps, best practices with real-world scenarios, and common pitfalls with troubleshooting tips.

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Key Features of DLP in Microsoft 365 Business Premium

• Broad Protection Scope: Microsoft 365 DLP can monitor and protect sensitive data across multiple locations – including Exchange email, SharePoint and OneDrive documents, and Teams chats[1][1]. This ensures a unified approach to prevent data leaks across cloud services.
• Content Analysis: DLP uses deep content analysis (not just simple text matching) to detect sensitive information. It can recognize content via keywords, pattern matching (regex), internal functions (e.g. credit card checksum), and even machine learning for complex content[1][2]. For example, DLP can identify a string of digits as a credit card number by pattern and checksum validation, distinguishing it from a random number sequence[2].
• Integrated Policy Enforcement: DLP policies are enforced in real-time where users work. For instance, when a user composes an email in Outlook or shares a file in SharePoint that contains sensitive data, DLP can immediately warn the user or block the action before data is sent[2][2]. This in-context enforcement helps educate users and prevent mistakes without heavy IT intervention.
• Built-in Templates & Custom Rules: Microsoft provides ready-to-use DLP policy templates for common regulations and data types (financial info, health info, privacy/PII, etc.), and also allows fully custom policy creation to meet organisational specifics[2][2]. We detail these options further below.
• User Notifications (Policy Tips): DLP can inform users via policy tips (in Outlook, Word, etc.) when they attempt an action that violates a DLP policy[2]. These appear as a gentle warning banner or pop-up, explaining the policy (e.g. “This content may contain sensitive info like credit card numbers”) and guiding the user on next steps before a violation occurs[2]. Policy tips raise awareness and let users correct issues themselves, or even report false positives if the detection is mistaken[2].
• Administrative Alerts & Reporting: All DLP incidents are logged. Admins can configure incident reports and alerts – for example, send an email to compliance officers whenever a DLP rule is triggered[3][3]. Microsoft 365 provides an Activity Explorer and DLP alerts dashboard for reviewing events, seeing which content was blocked or overridden, and auditing user justifications[1][1]. This helps monitor compliance and refine policies continuously.
• Flexible Actions: DLP policies can take various protective actions automatically when sensitive data is detected. These include blocking the action, blocking with user override, just logging (audit), notifying users/admins, and even encrypting content or quarantining it in secure locations[1][3]. These actions are configurable per policy rule, as discussed later.
• Integration with Labels & Classification: DLP in Microsoft Purview integrates with Sensitivity Labels (from Microsoft Information Protection) and supports Trainable Classifiers (machine learning-based content classification). This means DLP can also enforce rules based on sensitivity labels applied to documents (e.g. “Highly Confidential” labels)[4], and it can leverage classifiers to detect content types that are not easily identified by fixed patterns.

M365 Business Premium Licensing: Business Premium includes the core DLP capabilities similar to Office 365 E3[5]. This covers DLP for Exchange, SharePoint, OneDrive, and Teams. Advanced features like endpoint DLP or advanced analytics are generally part of higher-tier (E5) licenses, although Business Premium organisations can still use trainable classifiers and other Purview features in preview or with add-ons[1][5]. For most small-to-midsize business needs, Business Premium provides robust DLP protections.

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Pre-Built DLP Policy Templates vs. Custom Policies

Microsoft 365 offers a range of pre-built DLP policy templates to help you get started quickly, as well as the flexibility to create fully custom DLP policies. Here’s a comparison of both approaches:

Policy Type	Description & Use Cases	Pros	Cons
Pre-Built Templates	Microsoft provides ready-to-use DLP templates addressing common regulatory and industry scenarios. For example: U.S. Financial Data – detects info like credit card and bank account numbers (PCI-DSS).   U.S. Health Insurance Act (HIPAA) – detects health and medical identifiers.   EU GDPR – detects national ID numbers, passport numbers, etc.   Many others cover financial, medical, privacy, and more for various countries. Each template includes predefined sensitive information types, default conditions, and recommended actions tailored to that scenario. Administrators can select a template and adjust it as needed.	Quick Start: Fast to deploy compliance policies without deep expertise – just choose relevant template(s).   Best Practices: Encodes Microsoft’s recommended patterns, e.g., thresholds and actions, for that data type or law.   Customisable: You can modify any template – add/remove sensitive info types, tweak rules, or change actions to fit your organisation.	Broad Defaults: May be overly inclusive or not perfectly tuned, leading to false positives.   Limited Scope: Each template is focused on a specific regulation – may require multiple policies or significant tweaking for broader needs.   Globalization: Many templates are region-specific – ensure alignment with your jurisdiction and data types.
Custom Policies	You can build a DLP policy from scratch or customise a template. This involves defining your own rules, conditions, and actions to suit unique requirements – e.g., detecting proprietary project codes or internal-only data. You select the sensitive info types, patterns, or labels and configure rule logic manually. Microsoft also supports importing policies from external sources or partners.	Highly Tailored: Address specific business needs or unique sensitive data not covered by templates.   Flexible Conditions: Combine conditions in ways templates can’t – e.g., requiring multiple data types together.   Scoped Enforcement: Target policies to specific departments or projects using policy targeting.	More Effort & Expertise: Requires deep understanding of DLP components and thorough setup/testing.   No Starting Guidance: Creation from scratch can be error-prone without built-in thresholds or examples.   Maintenance: Needs ongoing tuning as data changes; no Microsoft baseline – fully managed by admin team.

Using Templates vs Custom: In practice, you can mix both approaches. A common best practice is to start with a template close to your needs, then customise it[2][2]. For example, if you need to protect customer financial data, use the “U.S. Financial Data” template and then add an extra condition for a specific account number format your company uses. On the other hand, if your requirement doesn’t fit any template (say you need to detect a confidential project codename in documents), you would create a custom policy from scratch targeting that. Microsoft 365 also lets you import policies (XML files) from third parties or other tenants if available, which is another way to get pre-built logic and then adjust it[2].

In the Microsoft Purview compliance portal’s DLP Policy creation wizard, templates are organised by categories (Financial, Medical, Privacy, etc.) and regions. The admin simply selects a template (e.g. “U.S. Financial Data”) and the wizard pre-populates the policy with corresponding rules (like detecting Credit Card Number, ABA Routing, SWIFT code, etc. shared outside the organisation) and actions (perhaps notify user or block if too many instances)[3][3]. You can then review and modify those settings in the wizard’s subsequent steps before saving the policy.

Summary: Pre-built DLP templates are great for quick deployment and covering standard sensitive data, while custom DLP policies offer flexibility for specialised needs. Often, organisations will use a combination – e.g. enabling a few template-based policies for general compliance (like GDPR or PCI-DSS) and additional custom rules for their particular business secrets.

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Sensitive Information Types (SITs) and Trainable Classifiers

At the core of any DLP policy is the definition of what sensitive information to look for. Microsoft’s DLP uses two key concepts for this: Sensitive Information Types (SITs) and Trainable Classifiers.

Sensitive Information Types (SITs)

A Sensitive Information Type is a defined pattern or descriptor of sensitive data that DLP can detect. Microsoft 365 comes with a large catalog of built-in SITs covering common data like: credit card numbers, Social Security numbers (US SSN), driver’s license numbers, bank account details, passport numbers, health record identifiers, and many more (including country-specific ones)[6][6]. Each SIT definition typically includes:

• Pattern/Format: for example, a credit card number SIT looks for a 16-digit pattern matching known card issuer formats and passes a Luhn check (checksum) to reduce false matches[2]. A Social Security Number SIT might look for 9 digits in the pattern AAA-GG-SSSS with certain exclusions.
  
• Keywords/proximity: some SITs also incorporate keywords that often appear near the sensitive data. For instance, a SIT for medical insurance number might trigger more confidently if words like “Insurance” or “Policy #” are nearby.
  
• Confidence Levels: SIT detection can produce a confidence score. Microsoft defines low, medium, high confidence thresholds depending on how many matches or supporting evidence is found. For example, finding a 16-digit number alone might be low confidence (could be a random number), but 16 digits + the word “Visa” nearby and a valid checksum = high confidence of a credit card. DLP policies can be tuned to act only on certain confidence levels.

Using SITs in Policies: When creating DLP rules, an admin will select which sensitive info types to monitor. You can choose from the library of built-in types – e.g., add “Credit Card Number” and “SWIFT Code” to a rule that aims to protect financial data[6]. You can also adjust instance counts (how many occurrences trigger the rule) – for example, allow an email with one credit card number but if it contains 5 or more, then treat it as an incident[5].

Custom Sensitive Info Types: If you have specialized data not covered by built-ins, Microsoft Purview allows creation of custom SITs. A custom SIT can be defined using a combination of:

• Patterns or Regex: e.g., define a regex pattern for an employee ID format or a product code.
  
• Keywords: specify words that often accompany the data.
  
• Validation functions: optionally, use functions like Luhn checksum or keyword validation provided by Microsoft if applicable. For example, you might create a custom SIT for “Project X Code” that looks for strings like “PROJX-[digits]” and perhaps requires the keyword “Project X” nearby to confirm context.

Creating custom SITs requires some knowledge of regular expressions and content structure, but it greatly extends DLP’s reach. Once defined and published, custom SITs become available just like built-in ones for use in DLP policies.

Trainable Classifiers

Trainable Classifiers are a more advanced feature where machine learning is used to recognize conceptual or context-based content that isn’t easily identified by a fixed pattern. Microsoft Purview includes some pre-trained classifiers (for example, categories like “Resumes”, “Source Code”, or “Sensitive Finance” documents), and also allows admins to train their own classifier with sample data[7].

A trainable classifier works by learning from examples:

• The admin provides two sets of documents: positive examples (which are definitely of the target category) and negative examples (which are similar in context but not of the target category)[7][7]. For instance, if training a classifier to detect “HR Resumes”, you’d feed it many resume documents as positives, and maybe other HR documents (policies, cover letters, etc.) as negatives.
  
• Microsoft’s system will analyze the textual patterns, structure, and terms common to the positive set and distinct from the negative set, thereby learning what constitutes a “Resume” in general (for example, presence of sections like Education, Work Experience, and certain formatting).
  
• Training Requirement: You need a substantial number of samples – typically at least 50 well-chosen positive samples and at least 150 negatives to get started, though more (hundreds) will yield better accuracy[7]. The system will process up to 2,000 samples if provided, to build the model.

After training, you test the classifier on a fresh set of documents to ensure it correctly identifies relevant content. Once satisfied, the classifier can be published and used in DLP policies just like an SIT. Instead of specifying a pattern, you would configure a rule like “if content is classified as Resume Documents (classifier) with high confidence, then apply these actions.”

When to use classifiers: Use trainable classifiers when the sensitive content cannot be easily captured by regex or keywords. For example, distinguishing a source code file from any other text file – there’s no fixed pattern for “source code” but a machine learning classifier can recognize code syntax structures. Another example is identifying documents that look like contracts or CVs; these might not have unique keywords but have overall similarities that a classifier can learn. Note: Trainable classifiers are more commonly associated with broader Purview content classification (for labeling or retention); in DLP they are an emerging capability (Microsoft announced support for using trainable classifiers in DLP policies in recent updates).

Sensitive Info Type vs Classifier: In summary, SITs are rule-based (pattern matching) and are great for well-defined data like ID numbers, whereas classifiers are ML-based and suited for identifying categories of documents or free-form content. DLP can leverage both: for example, a DLP policy might trigger on either a specific SIT or a match to a classifier (or both conditions).

To implement these:

• Identifying SITs: In the compliance portal under Data Classification, you can view all Sensitive Info Types. Microsoft provides definitions and even testing tools where you can input a sample string to see if it triggers a given SIT pattern. This helps admins understand what each SIT looks for. Identify which ones align with your needs (financial, personal data, etc.) and note any gaps where you may need custom SITs.
  
• Training Classifiers: Under Data Classification > Classifiers, you can create a new trainable classifier. Provide the example documents (often by uploading them to SharePoint or Exchange as indicated) and follow the training wizard[7][7]. This process can take time (hours to days) to build the model. Once ready, test it and then use it by adding a condition in a DLP policy rule: “Content is a match for classifier X.”

Example: Suppose your organisation wants to prevent leaked source code files via OneDrive or Email. There’s no single pattern for “source code” (it’s not like a credit card number), but you can train a classifier on a set of known code files. After training, you include that classifier in a DLP policy rule targeting OneDrive and Exchange. If a user tries to share a file that the classifier deems to look like source code, the DLP policy can trigger (warn the user or block it). Meanwhile, simple patterns like API keys or passwords within text can be handled by SITs or regex in the same policy.

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DLP Policy Actions and User Override Options

When a DLP policy identifies sensitive information, it can take several types of actions. These actions determine what happens to the content or user’s attempt. The main actions are: Audit (allow and log), Notify (policy tip or email), Block (with or without override), and Encrypt. Here we explain each and how they function, including the ability for users to override certain blocks:

• Audit Only (No visible action): The policy can be set to allow the activity but log it silently. In this case, if content matches a DLP rule, the user’s action (sending email or sharing file) is not prevented and they might not even know it triggered. However, the incident is recorded in the compliance logs and available in DLP reports for admin review[1]. Admins might use this in a “test” or monitoring mode – for example, run a policy in audit mode first to gauge how often it would trigger, before deciding to enforce stricter actions. Audit mode ensures no disruption to business while still gathering data.
• Notify (User Notification and/or Admin Alert): DLP can notify the user, the admin, or both when a policy rule is hit:
  • User Notification (Policy Tip): The user sees a policy tip in the app (such as Outlook, OWA, Word, Excel, etc.) warning them of the policy. For example, in Outlook, a yellow bar might appear above the send button: “This email contains sensitive info (Credit Card Number).”[2]. The tip can be informational or include options depending on policy settings (e.g. Report a false positive, Learn More about the policy, or instructions to remove the sensitive data)[2]. Policy tips do not stop the user by themselves; they are just advisory unless combined with a Block action. However, a strong warning often causes users to correct the issue (e.g., remove the credit card number or apply encryption).
    
  • Admin Notification (Incident Report): The policy can send an incident report email to specified addresses (like IT/security team) whenever it triggers[2]. This email typically contains details of what was detected (e.g., “An email from Alice to external recipient was blocked for containing 3 credit card numbers”) so that compliance officers can follow up. Admin notifications can be configured to trigger on every event or also based on severity or thresholds (for instance, only notify if there were more than 5 instances, or if the data is highly sensitive)[3][3].

  Use cases: Notify-only is useful when you don’t want to outright block content but want to raise awareness. For example, you might simply warn users and notify IT whenever someone shares something that looks like personal data, to educate rather than punish. It’s also essential during policy tuning phase – run the policy in Notify (or test mode with notifications) to gather feedback from users on false positives.

• Block: This action prevents the content from being shared or sent. If an email triggers a “block” rule, it will not be delivered to the recipient; if a file is in SharePoint/OneDrive, block can mean preventing external sharing or access. The user will typically be informed that the action is blocked by policy. There are two sub-options for blocking:
  • Block with Override: In this mode, the user is blocked initially, but is given the option to override the block with a justification[1]. For example, a policy tip might say “This content is blocked by DLP policy. Override: If this is a legitimate business need, you may override and send the content by providing a justification.” The user might click “Override” and enter a reason (like “Approved by manager for client submission”). The system logs the user’s decision and justification, and then allows the content to go through[1]. This balances security with flexibility – it lets users proceed when absolutely necessary (preventing business workflow stoppage), but creates an audit trail and accountability. Admins can later review these override incidents to see if they were valid or need further policy tuning.

  Example: If a sales person must send a client’s passport copy to an airline (which violates a “no passport externally” policy), they could override with “Passport needed for booking flight, approved by policy X exemption.” This would let the email send, but security knows it happened and why.

  • Block (No Override): This is a strict block with no user override permitted. The content simply is not allowed under any circumstance. The user will get a notification that the action is blocked and they cannot bypass it. For instance, you may decide that any email containing more than 10 credit card numbers is automatically forbidden to send externally, period. In such cases, the policy tip might inform “This message was blocked and cannot be sent as it contains prohibited sensitive information” with no override option. The user must remove the data or contact admin.

  According to Microsoft’s guidance, DLP can show a policy tip explaining the block, and in the override case, capture the user’s justification if they choose to bypass[1]. All block events (with or without override) are logged to the audit log by default[1].

• Encrypt: For email scenarios, a DLP policy can automatically apply encryption to the message as an action (this uses Microsoft Purview Message Encryption, previously known as Azure RMS). Instead of blocking an outgoing email, you might choose to encrypt the email and attachments so that only the intended recipients (who likely need to authenticate) can read it[8][8]. In the DLP policy configuration, this is often phrased as “Restrict access or encrypt the content in Microsoft 365 locations” – essentially wrapping the content with rights management protection[8]. For example, if an email contains client account numbers, you might allow it to be sent but enforce encryption such that if the email is forwarded or intercepted, unauthorized parties cannot read it.

  Additionally, for documents in SharePoint/OneDrive, and with integration to sensitivity labels, encryption can be applied via sensitivity labeling. However, in many cases the straightforward use is with Exchange email – DLP can trigger the “Encrypt message” action, thereby sending the email via a secure encrypted channel accessible via a web portal by external recipients[8]. Admins will need to have set up or use the default encryption template for this action to function.

• Quarantine/Restrict Access: In some instances (especially for SharePoint/OneDrive files or Teams chats), DLP can quarantine content or restrict who can access it. For example, if a file stored in OneDrive is found to contain sensitive data, DLP could remove external sharing links or move the file to a secure quarantine location, effectively preventing others from accessing it[1]. In Teams, if a user tries to share sensitive info in a message, DLP can prevent that message from being posted to the recipient (so the sensitive info “doesn’t display” to others)[1]. These are variations of block actions in their respective services (quarantine is effectively a form of block for data at rest).

User Override Configuration: When setting up a DLP rule, if you select a Block action, you will have a checkbox option like “Allow people to override and share content” (wording may vary) which corresponds to Block with Override. If enabled, you usually can also require a business justification note on override and optionally can allow or disallow the user to report a false positive through the override dialog. Override justifications are saved and can be reviewed by admins (via Activity Explorer or DLP reports showing “User Override” events)[1][1]. In highly sensitive policies, you’d leave override off (for absolute blocking). For moderately sensitive ones, enabling override strikes a balance.

From a user-experience perspective, override typically happens through the policy tip UI in Office apps: the user clicks something like “Override” or “Resolve” on the policy tip, enters a justification text in a dialog, and then is allowed to proceed. The policy tip then usually changes state – e.g., turns from a warning into a confirmation that the user chose to override [2]. The message is then sent or file shared, but marked in logs.

Important: We recommend using “Block with Override” for initial deployment of strict policies. It educates users that something is wrong but doesn’t completely stop business; it also gives admins insight into how often users feel a need to override (which might indicate the policy is too strict or needs refinement if it’s frequently overridden). Only move to full “Block without override” for scenarios that are never acceptable or after trust in the policy accuracy is established.

Policy Tip Customisation: You can customise the text of notifications both to users and admins. For instance, the policy tip can say “This file appears to contain confidential data. If you believe you must share it, please provide a reason.” and the admin incident email can include instructions for the recipient on what to do when they get such an alert. Customising helps align with your company’s tone and provide helpful guidance to users rather than generic messages[3][3].

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Step-by-Step Guide to Implementing DLP Policies (Email, SharePoint, OneDrive)

Implementing a DLP policy in Microsoft 365 Business Premium involves using the Microsoft Purview Compliance Portal (formerly Security & Compliance Center). Below is a step-by-step walkthrough for creating and effectively deploying a DLP policy, covering configuration for Exchange email, SharePoint, and OneDrive:

Preparation: Ensure you have the appropriate permissions (e.g. Compliance Administrator or Security Administrator role). Go to the Microsoft Purview Compliance portal at https://compliance.microsoft.com and select “Data Loss Prevention” from the left navigation.

Step 1: Start a New DLP Policy

1. Navigate to Policies: In the DLP section, click on “Policies” and then the “+ Create policy” button[4]. This launches the policy creation wizard.
2. Choose a Template or Custom: The wizard will first ask you to choose a policy template category (or a custom option). You have two approaches here:
   • To use a pre-built template, pick a category (e.g. “Financial” or “Privacy”) and then select a specific template. For example, under Financial, you might choose “U.S. Financial Data” if you want to protect things like credit card and bank account info[3]. Each template is briefly described in the UI.
     
   • To create from scratch, choose the “Custom” category and then “Custom (no template)” as the template. (Some UIs also have an explicit “Start from scratch” option.)

   Click Next after selection. (In our example, if we selected U.S. Financial Data, the policy wizard will pre-load some settings for that scenario.)

Step 2: Name and Describe the Policy

3. Policy Name: Provide a descriptive name for the policy, e.g. “DLP – Financial Data Protection (Email)”. Choose a name that reflects its purpose; this helps when you have multiple policies.
   
4. Description: Enter an optional description, e.g. “Blocks or encrypts emails containing financial account numbers sent outside org. Based on U.S. Financial template.” This description is for admin reference.
   
5. Click Next.

(Note: Once created, DLP policy names cannot be easily changed, so double-check the name now[4].)

Step 3: Choose Locations to Apply

6. Select Locations: You will be asked where the policy applies. The available locations include Exchange email, SharePoint sites, OneDrive accounts, Teams chat and channel messages[6]. For Business Premium focusing on email/SP/OD:
   • Toggle Exchange email, SharePoint, and OneDrive to “On” if you want to include them. (Teams chat can be included if needed for chat messages, though the question emphasizes email/SP/OD.)
     
   • You can scope within locations as well. For instance, you might apply to “All SharePoint sites” or select specific sites if only certain sites should be governed by this policy, but generally “All” is chosen for broad protection.
     
   • If this policy should only apply to certain users or groups (via Exchange mailboxes or OneDrives), there is an option to include or exclude specific accounts or conditions (administrative units, etc.)[4]. For an initial policy, you might leave it as all users.

   Click Next after selecting locations.

Step 4: Define Policy Conditions (What to Protect)

7. Choose Information to Protect: If you used a template, at this stage the wizard will show the pre-defined sensitive info types included. For example, the U.S. Financial Data template might list: Credit Card Number, SWIFT Code, ABA Routing Number, etc., with certain thresholds (like 1 instance low count, 10 instances high count)[6][6]. You can usually add or remove sensitive info types here:
   • To add, click “Add an item” and select additional SITs from the catalogue (or even a trainable classifier or keyword dictionary if needed).
     
   • To remove, click the “X” next to any SIT you don’t want.
     
   • If building custom without a template, you’ll have an empty list and need to “Add condition” then choose something like “Content contains sensitive information” and then pick the types. The UI will let you search for built-in types (e.g., type “Passport” or “Credit Card” to find those SIT definitions).
     
   • You can also set the instance count trigger. Templates often define two rules: one for low count and one for high count occurrences of data, which may have different actions (e.g., 1 credit card found = maybe just notify; 10 credit cards = block)[6][6]. Ensure these thresholds align with your tolerance. You may adjust “min count” or confidence level filters here.
8. Add Conditions or Exceptions: Optionally, refine the conditions:
   • You might add a condition like “Only if the content is shared with people outside my organization” if you want to protect against external leaks but not internally. For example, you would then configure: If content contains Credit Card Number and recipient is outside org, then trigger. In the wizard, this is often presented as “Choose if you want to protect content only when shared outside or also internally”. Select “people outside my organization” if your goal is to prevent external leaks[3].
     
   • You can also set exceptions. E.g., Exclude content if it’s shared with a particular domain or if a specific internal user sends it. Exceptions might be used sparingly for business needs or trusted parties.
     
   • If using labels or a classifier, you could add a condition group: e.g., “Content has label Confidential” OR “Content contains these SITs.” The UI supports multiple condition groups with AND/OR logic.

   On the flip side, ensure you’re not over-scoping: if you want to protect both internal and external, leave the default “all sharing” scope.

9. Click Next once conditions are set. The wizard often shows a summary of “What content to look for” and “When to enforce” at this point – review it.

Step 5: Set Actions (What happens on a match)

10. **Select Policy *Actions***: Now determine what to do when content matches the conditions. You will typically see options like:
    • Block access or send (with or without override) – often worded as “Restrict content”. E.g., “Block people from sending email” or “Block people from accessing shared files” depending on location.
      
    • Allow override: a checkbox to allow user to bypass if you want.
      
    • User notifications (policy tips): an option like “Show policy tip to users and allow them to override” or “Show policy tip to inform users”. It’s recommended to enable policy tips for user awareness[3].
      
    • Email notifications: an option to send notification emails. This may have sub-settings: notify user (sender), notify an admin or other specific people. You can input a group or email address for incident reports here.
      
    • Encryption: for email policies, an option “Encrypt the message” might appear (if configured). You may need to select an encryption template (such as “Encrypt with Office 365 Message Encryption”) from a dropdown.
      
    • Allow forwarding: sometimes for email, a setting to disallow forwarding of the email if it contains the info, or to enforce encryption on forward. (In newer interfaces, disallow forward is part of encryption templates).

    For our example (financial data email policy): we might choose “Block email from being sent outside”. The wizard might then ask “do you want to allow overrides?” – if we say Yes, it means block with override; if No, it’s a strict block. Let’s say we allow override for now (check Allow override). And we check the box “Show policy tip to users” so they get warned[3]. We also set “Notify admins”: Yes, send an alert to our compliance email (we enter an address or choose a role group). We might choose not to encrypt in this policy since we’re blocking outright; but if instead of blocking we wanted encryption, we’d select that action.

    In multi-location policies, actions can sometimes be set per location. The wizard might show sections for “Email actions” vs “SharePoint actions”. For SharePoint/OneDrive, “block” usually translates to “restrict external access” (prevent sharing outside or remove external users) since the content is at rest. Configure each as needed.

    Microsoft’s default templates often pre-fill some actions: for low-count detection maybe just notify, for high-count detection block. Make sure to adjust these if your intent differs. For instance, the U.S. Financial Data template might default to “notify user; allow override” for 1-9 instances and “block; allow override; incident report” for 10+ instances[6]. You can tweak those thresholds or actions.

11. Customize Notification Messages (optional): There is typically a link “Customize the policy tip and email text”[3]. Click that to edit the wording:
    • For policy tip: you might type something user-friendly: “Policy Alert: This content may contain financial account data. If not intended, please remove it. If you believe sending is necessary for business, you may override with justification.”
    • For admin email: you can include details or instructions. By default it includes basic info like rule name, user, content title. You could add “Please follow up with the user if this was not expected,” etc.
      
    • You can also decide if the user sees the policy tip in certain contexts (e.g., maybe show it only when they actually violate by clicking send, or show as soon as they type the number – Outlook can do real-time).

    Save those customisations.

12. Set Incident Reporting and Severity: Many wizards have a section for incident reports/alerts. For instance, “Use this severity level for incidents” (Low/Medium/High) and “Send an alert to admins when a rule is matched”[4][4]. Choose a severity (perhaps High for a finance data breach) so it’s flagged clearly in the dashboard. Ensure the toggle for admin alerts is on, and frequency set to every time (or you can set to once per day etc. if flood concern).
    • If available, set the threshold for alerting. In some cases you can say “alert on every event” vs “after 5 events in 1 hour” – depending on how you want to be notified. For simplicity, we do each event.
13. Additional options: If configuring email, you might see a specific setting to block external email forwarding of content or to enforce that external recipients must use the encrypted portal[8][3] – adjust if relevant. In SharePoint DLP, you might see an option like “restrict access to content” which essentially removes permissions for external users on a file if a violation is found.

Click Next after setting all actions and notifications.

Step 6: Review and Turn On

14. Review Settings: The wizard will show a summary of your policy – the locations, conditions, and actions. Carefully review to ensure it matches your intent (e.g., “Apply to: Exchange email (external), Condition: contains Credit Card Number ≥1, Action: Block with Override + notify user & admin” etc.). It’s easy to go back if something is off.
15. Choose Policy Mode: You will be prompted to choose whether to turn the policy on right away, or test it in simulation mode, or keep it off. The options usually are:
    • Test DLP policy (Simulation): Runs the policy as if active but doesn’t actually enforce the block actions. Instead, it logs what would have happened and can still show policy tips to users (if you choose “test with notifications”). This mode is highly recommended for new policies[3]. It allows you to see if your policy triggers correctly and how often, without disrupting business. You can check the DLP reports during testing to adjust sensitivity (for example, if you see too many false positives).
      
    • Turn it on right away (Enforce): Makes the policy active and enforcing immediately after you finish. Only do this if you are confident in the configuration and have possibly tested previously.
      
    • Keep it off for now: Saves the policy in an off state. You can manually turn it on later. This is similar to test mode but without even simulation. You might choose this if you want to create multiple policies first or only enable after a certain date.

    Select Test mode with notifications if available (this will simulate actions but still send out the user tips and admin alerts so you get full insight, without actually blocking content)[3].

16. Submit: Finish the wizard by clicking Submit or Create. The policy will be created in the state you selected (off, test, or on).
17. If in Test Mode, run the policy for a period (a week or two) to gather data. Users will see policy tips but will not be blocked (unless the tip itself convinces them to change behavior). Monitor the DLP reports:
    • Go to Activity Explorer in the compliance portal and filter for DLP events; you’ll see entries of what content would have matched.
      
    • Check the Alerts section to see if any admin notifications came in (they should if configured, even in test mode).
      
    • Review any user feedback – if users report confusion or false positives via the “Report” button on a policy tip, take note.

    Fine-tune the policy as needed: maybe adjust the sensitive info types (add an exception for something causing false alarms, or raise the threshold count if it’s too sensitive).

18. Enable Enforcement: Once satisfied, edit the policy (you can change its mode from test to on). If it was in simulation, you can now switch it to “Turn on” (enforcement mode). Alternatively, you could have initially set it to turn on immediately; in that case, just monitor it closely upon rollout. Communicate to users as needed that certain data (like credit cards, etc.) are now being protected by policy.

Step 7: Ongoing Management

19. User Education: Make sure to inform your users that DLP policies are in effect. For example, send an email or include in security training: “We have deployed policies to protect sensitive data (like credit card numbers, SSNs, etc.). If you try to send such data externally, you may get a warning or block message. This is for our security and compliance.” Include what they should do (e.g., encrypt emails or get approval if they truly need to send).
    
20. Monitor Reports Regularly: After deployment, regularly check the DLP Alerts dashboard and Activity Explorer. Verify that the policy is catching intended incidents and not too many unintended ones. DLP monitoring is an ongoing process – you might discover users trying new ways to send data or needing exceptions.
    
21. Adjust Policies: Based on real-world usage, adjust your DLP rules. For instance, you might need to add an allowed exception for a specific partner domain (if it’s legitimate to share certain data with a vendor, you can exclude that domain in the policy). Or you might tighten rules if users find loopholes.
    
22. Extend to More Areas: If you started with email, consider extending similar protections to SharePoint/OneDrive if not already. The process is similar – a policy can cover multiple locations or you can create separate policies per location if that makes management easier (some admins prefer one combined policy covering all channels for a certain data type; others prefer distinct policies, e.g., one for “Email outbound PII” and another for “SharePoint data at rest PII”).

Illustration – Policy Tip in Action: When configured, the user experience is as follows: Suppose a user tries to send an email with a credit card number to an external recipient. As soon as they enter the 16-digit number and an external address, a policy tip pops up in Outlook warning them (e.g., “This may contain sensitive info: Credit Card Number. Review policy.”)[2]. If the policy is set to block, when they hit send, Outlook will prevent sending and show a message like “Your organization’s policy blocks sending this content” with possibly an Override button. If override is allowed, clicking it prompts the user to type a justification. Upon confirming, the email is sent, and the user’s action is logged (the email might be encrypted automatically if that was configured). Both the user and admin receive notification emails about this incident (user gets “You sent sensitive info and it was allowed due to your override” and admin gets an alert detailing what happened)[3]. If override was not allowed, the user simply cannot send until they remove the sensitive content.

Illustration – SharePoint/OneDrive: If a file containing sensitive data is uploaded to OneDrive and the user attempts to share it with an external user, a similar policy tip might appear in the sharing dialog or they may get an email notification. The sharing can be blocked – the external person will not be able to access the file. The user might see a message in the OneDrive interface like “Sharing link removed – A data loss prevention policy has been applied to this content” (in modern UI). The admin would see an incident logged for this file. The user could have the option to override if enabled (possibly via a checkbox like “I understand the risks, share anyway”).

Following these steps ensures you implement DLP systematically and with caution (using test mode to avoid disruption). Screenshots from the Compliance Center wizard and Outlook policy tips can be found in Microsoft’s documentation for reference[3][3], which visually guide where to click and what messages appear.

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Real-World Scenarios and Best Practices

Real-World Scenarios: DLP policies in M365 Business Premium can address a variety of common business needs. Here are a few scenarios illustrating effective use:

• Scenario 1: Protecting Credit Card and Personal Data in Emails – A retail company wants to ensure employees don’t send customers’ credit card details or personal IDs via email to external addresses. They use the built-in Financial data template to create a policy for Exchange Online. If an email contains a credit card number or social security number and is addressed outside the company, the user is warned and the email is blocked unless they override with a valid business reason. This prevents accidental leakage of PCI or PII data via email[3][3]. Over time, the number of such attempts drops as employees become aware of the policy.
• Scenario 2: Securing Confidential Files in SharePoint/OneDrive – A consulting firm stores client data on SharePoint Online. They implement a DLP policy to detect documents containing phrases like “Project Classified” and client account numbers (using custom SIT for account IDs). The policy applies to SharePoint and OneDrive, and blocks sharing of such documents with anyone outside their domain. A consultant who attempts to share a marked confidential document with a client’s Gmail address gets a notification and the action is prevented. An override is not allowed due to the sensitivity. The admin receives an alert to follow up. This ensures that confidential deliverables aren’t accidentally shared beyond intended channels.
• Scenario 3: Compliance with Health Data Regulations (HIPAA) – A healthcare provider uses a DLP policy based on the HIPAA template to guard ePHI (electronic protected health info). The policy looks for medical record numbers, patient IDs, or health insurance claims numbers in both emails and OneDrive. If a nurse tries to email a patient’s record externally or save it to a personal cloud, the system flags it. In this case, the policy is set to encrypt any outbound email containing patient health info rather than block (since doctors may need to send info to outside specialists). So the email is delivered but only accessible via a secure encrypted message portal[3]. This meets HIPAA requirements by protecting data in transit, while still permitting necessary flow of information in patient care.
• Scenario 4: Intellectual Property (IP) Protection – An engineering firm wants to prevent design documents or source code from leaking. They train a classifier on sample source code files. They also define a custom keyword list for project code names. A DLP policy combines these: if a document matches the “Source Code” classifier or contains project code names and is shared externally, it’s blocked. For email, they additionally use a policy tip allowing override with justification (so if a developer legitimately needs to send code to a vendor, they can, but it’s tracked). This multi-pronged approach catches anything that looks like code or proprietary project info leaving the company, safeguarding intellectual property.
• Scenario 5: Data Privacy (GDPR Personal Data) – A multinational company subject to GDPR defines a policy to detect personal data (SITs like EU National ID, passport numbers, IBANs, etc.). They apply it to all locations – if personal data is being sent to external recipients or shared publicly, the user gets a warning. The policy is initially in audit/notify mode to measure incidents. They find many hits in OneDrive where employees back up contact lists that include customer info. Using reports, they educate those users and adjust the policy. Eventually they enforce blocking for certain info like national IDs, while allowing override for less sensitive fields. This helps build a culture of privacy by design, as users start thinking twice before sharing files with lots of personal data.

Best Practices for Effective DLP:

• Start in “Shadow Mode” (Testing): When introducing a new DLP policy, begin with it in Test/Monitoring mode (no blocking) or with only notifications. This lets you see how often it triggers and whether there are false positives, without disrupting business[3]. Use the test results to fine-tune conditions (e.g., add an exception if a certain internal process constantly triggers the policy benignly). Once refined, switch to enforce mode. This phased approach prevents chaos on day one of DLP enforcement.
• Use Policy Tips to Educate Users: Policy tips are a powerful way to make DLP a collaborative effort with employees. Ensure policy tips are enabled wherever appropriate, and craft clear, friendly tip messages. For example, instead of a cryptic “DLP rule 4 violated,” say “Warning: This file contains SSNs which are not allowed to be shared externally. Please remove them or use encryption.” This helps users learn the policies and the reasons behind them, turning them into allies in protecting data[2]. Additionally, encourage users to utilize the “Report False Positive” option if they believe the policy misfired – this feedback loop can help you improve accuracy.
• Leverage Pre-Built SITs and Templates: Microsoft’s built-in sensitive info types and templates cover a wide range of common needs. Avoid reinventing the wheel – use them as much as possible. Only create custom SITs or rules if you truly have to. The built-ins have undergone refinement (for example, the Credit Card Number SIT will avoid false hits by requiring checksum validation and keywords)[2]. Utilizing these saves time and usually yields reliable detection out-of-the-box.
• Combine Multiple Conditions Carefully: If you have multiple sensitive info types you want to protect in one policy, consider whether they should be in one rule or separate rules. One rule can contain multiple SITs but then the same actions apply to all if any trigger[9][9]. If you need different handling (e.g., maybe block credit cards but only warn on phone numbers), those should be separate rules (or even separate policies). Also use the condition logic (AND/OR) thoughtfully:
  • Use AND if you want a rule to trigger only when multiple criteria are met together (e.g., document has Project code AND marked Confidential).
    
  • Use OR (separate rules) if any one of multiple criteria should trigger (most common case).
    
  • Use exceptions rather than overloading too many NOT conditions in the rule; it’s clearer to manage.
• Define Clear Policy Scope: Align DLP policies with business processes. For instance, if only Finance department deals with bank accounts, you might scope a bank account DLP rule just to Finance’s OneDrive and mail, to avoid impacting others unnecessarily. Conversely, a company-wide policy for customer PII might apply to all users. Metadata-based scoping (such as using Teams or SharePoint site labels, or targeting certain user groups) can improve relevance.
• Set Incident Response Workflow: Ensure that when DLP incidents occur (especially blocks), there is a process to address them. Assign personnel to check DLP alerts daily or have alerts go into a ticketing system. If a user repeatedly triggers DLP or overrides frequently, it might require an educational email or management review. DLP is not “set and forget” – treat it as part of your security operations. Over time, analyze incident trends: which policies fire the most, are they real risks or nuisance triggers? Use that insight to update training or adjust DLP logic.
• Tune for False Positives and Negatives: No DLP is perfect initially. Be on the lookout for false positives (innocuous content flagged) and false negatives (sensitive content getting through). False positives common examples: a 16-digit tracking number being mistaken for a credit card, or a random number that fits the pattern of a national ID. To reduce false positives, you can raise the count threshold, add validating keywords, or adjust confidence level required (e.g., require “High confidence” matches only)[3]. For false negatives, consider if the SIT pattern needs expansion or if users are finding ways around detection (like writing “1234 5678 9012 3456” with spaces – though MS SITs often catch that. If not, you may broaden the regex). It’s a continual tuning process.
• Keep DLP Policies Updated: Revisit your DLP configurations regularly (e.g., quarterly)[5]. As business evolves, new sensitive data types might emerge (e.g., you start collecting biometric IDs), or regulations change. Microsoft also updates the service with new features and SITs – review release notes (e.g., new SITs or classifier improvements) to take advantage. Also, if you notice a policy hasn’t logged any events in months, verify if it’s still needed or if perhaps it’s misconfigured.
• Use Simulation for Impact Analysis: If you plan to tighten a policy (like moving from override -> full block, or adding a new sensitive info type to an existing policy), consider switching it back to Test Mode for a short period with the new settings. This gives you data on how the change would play out. Especially for big scope changes (like applying a policy company-wide rather than to one department), simulation can prevent unintended business halts.
• Combine DLP with Sensitivity Labels: A best practice is to use Sensitivity Labels (from Microsoft Information Protection) to classify highly sensitive documents, and then have DLP rules that reference those labels. For example, label all documents containing trade secrets as “Highly Confidential” (either manually by users or via auto-labeling), then a DLP policy can simply have a condition “If document has label = Highly Confidential and is shared externally, block it.” This approach can be more accurate since labeling incorporates user knowledge and additional context beyond pattern matching. It also means DLP isn’t re-evaluating content from scratch if a label is already applied.
• Monitor User Feedback & Adapt: Pay attention to how users interact with DLP. If they are frequently overriding a particular policy with “false positive” justifications, that indicates a need to adjust that policy or train users better. Conversely, if users never override and always comply, you might try tightening the policy further or maybe you could safely enforce encryption instead of just warning.

By following these best practices, you’ll implement DLP controls that effectively protect data without unduly hampering productivity. A well-tuned DLP system actually becomes almost invisible – catching only genuine policy violations and letting normal work flow uninterrupted – which is the end goal.

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Potential Pitfalls and Troubleshooting Tips

Even with careful planning, you may encounter some challenges when deploying DLP in Microsoft 365. Below we list common pitfalls and how to troubleshoot or avoid them:

Common Pitfalls / Challenges

• Overly Broad Policies (False Positives): A policy that’s too general can trigger on benign content. For example, a policy that flags any 9-digit number as a SSN could halt emails with order numbers or random data that coincidentally have 9 digits. This can frustrate users and lead them to ignore or work around DLP alerts. Best Avoided By: refining your patterns (use built-in SITs with verification, or add context requirements). Also consider using higher instance counts for triggers – e.g., a single credit card number might be legitimate (a customer providing their payment info), but multiple cards likely isn’t; the template addresses this by separate rules for count =1 vs many[6][6]. Leverage that design to reduce noise.
• Too Many Exceptions (False Negatives): The opposite – if you exempt too many conditions to reduce noise, you might inadvertently let sensitive data slip. For instance, excluding all internal emails from DLP might miss a scenario where an insider mistakenly emails a file to a personal Gmail thinking it’s internal. Mitigation: Try using “outside my organization” condition instead of broad exceptions, and be cautious with whitelisting domains or users. Ensure exceptions are narrow and justified. Periodically audit the exceptions list to see if they’re still needed.
• User Workarounds: If users find DLP blocks onerous, they might attempt to circumvent them, e.g., by splitting a number across two messages or using code words for data. While DLP can’t catch everything (especially deliberate misuse), it’s a sign your policy may be too restrictive or not communicated well. Mitigation: Gather feedback from users. If they resort to workarounds to accomplish necessary tasks, consider adjusting the policy to allow those via override (so at least it’s tracked). Also, carry out user training emphasizing that bypassing DLP policies can be a policy violation itself, and encourage using the provided override with justification instead of sneaky methods. DLP is there to protect them and the company, not just to block work.
• Performance and Client Compatibility: Policy tips appear in supported clients (Outlook desktop 2013+, OWA, Office apps). In unsupported clients (or if offline), the block may still occur server-side but the user experience might be confusing. Also, DLP only scans the first few MBs of content for tips (for efficiency) – so extremely large files might not trigger a tip even if they contain an ID at the very end, though the server will catch it on send. Mitigation: Educate users on which clients support real-time tips (e.g., Outlook on the web and latest Outlook desktop do; older mobile apps might not). Also, if you have very large files, consider splitting them or note that DLP might not scan everything for tip purposes (though it will for actual enforcement).
• Endpoint and Offline Gaps: Business Premium’s DLP does not cover endpoints (unless you have add-ons) the same way as cloud. That means if a user has sensitive data and tries to copy it to a USB drive or print it, the default M365 DLP won’t stop that – those are endpoint DLP features available in E5. Users might exploit this gap. Mitigation: Use other measures like BitLocker for USB, device management, and educate employees that copying sensitive files to unauthorized devices is against policy. Microsoft provides an upgrade path to Endpoint DLP if needed, but in absence, focus on cloud channels which are covered.
• Ignoring Alerts: If the security team doesn’t actively review DLP alerts and logs, incidents might go unnoticed. DLP isn’t “blocking everything” – some policies might be notify-only by design. If those notifications aren’t read by someone, the benefit is lost. Mitigation: Set up a clear alert handling process. Even if you have alerts emailed, consider also having a Power Automate or SIEM rule that collects DLP events for analysis. Regularly check the Compliance Center’s Alerts. If volume is high, use filters or thresholds to prioritize (the DLP alert dashboard can highlight highest severity issues).
• Policy Conflicts: If you create multiple DLP policies that overlap (e.g., two policies apply to the same content with different actions), it can be unclear which one wins. Generally, the more restrictive action should win – e.g., if one policy says block and another says allow with notification, the content will be blocked. But it can confuse troubleshooting when an incident shows up under a certain policy. Mitigation: Try to structure policies to minimize overlaps. Perhaps have one global policy per category of data. If overlaps are needed, document the hierarchy (you might rely on Microsoft’s default priority or adjust the order if the portal allows).
• Data Not Being Detected: Sometimes you might find that clearly sensitive data wasn’t caught by DLP. Possible reasons include:
  • The data format didn’t match the SIT’s pattern (e.g., someone wrote a credit card like “4111-1111-1111-1111” with unusual separators and maybe the SIT expected no dashes – though the built-in usually handles common variations).
    
  • The content was embedded in an image or scanned document – OCR is not performed by DLP by default, so an image of a document with SSNs would not trigger.
    
  • The policy location wasn’t correctly configured (maybe OneDrive for that user wasn’t included, etc.).
    
  • The policy was in test mode (logging only) and you expected a block.

  Troubleshooting: Double-check the Content: test the specific content against the SIT’s detection logic (Microsoft’s compliance portal has a “Content explorer” and SIT testing tool). For images, consider using Azure Information Protection scanner or trainable classifier if needed (outside scope of basic DLP). Verify the Policy settings: is that user or site excluded? Is it running in simulation only? Use the DLP incident details in Activity Explorer – it often shows which rule did or didn’t fire and why. If needed, adjust the regex or add that specific string as a keyword to pick it up. For advanced needs like OCR, you may need supplementary tools.

Troubleshooting Tips

• Use the DLP Test Feature: Microsoft provides a way to test how content is evaluated by DLP. In the Compliance Center’s Content Explorer or policy setup, you might find options to test a string against an SIT. There are also PowerShell cmdlets (like Test-DlpPolicy in Exchange Online) that can simulate a DLP policy against given content to see if it would match. This is useful for troubleshooting a rule – e.g., “Why didn’t this trigger?” or “Is my custom regex working?”[1].
• Policy Tips Troubleshooter: If policy tips are not showing up where expected (say in Outlook), Microsoft has a diagnostic and guidance. Common issues: the user’s Outlook might not be in cache mode, or the mail flow rule side of DLP took precedence without the client seeing it. Ensure the DLP policy actually has user notifications enabled, and that the client application is up to date. Try the same scenario in OWA vs Outlook to isolate client-side issues.
• Check the Audit Log: All DLP actions (whether just a tip shown, an override done, or a block) are recorded in the unified audit log. If something odd happens, go to Audit > Search and filter by activities like “DLP rule matched” or “DLP rule overridden”. You can often trace exactly what rule acted on a message and what the outcome was. For instance, if a user claims “I wasn’t able to override”, the audit might show they attempted and perhaps they didn’t meet a condition or the policy disallowed it. The log entry will also show which policy GUID triggered – you can confirm if the correct policy fired.
• Simulate Different License Levels: If certain features (like trainable classifiers or some SITs) aren’t working, it could be a licensing limitation. Business Premium includes most DLP for cloud but not some extras. The interface might still show options (like Device/Endpoint location or advanced classifiers) but they might not function fully. If you suspect this, consult the documentation on licensing to see if that capability is supported[5]. In some cases, a 90-day E5 compliance trial can be activated to test advanced features in your tenant[1].
• Use Microsoft Documentation and Community: Microsoft’s official docs (Purview DLP section) have detailed policy reference and troubleshooting guides. If something is puzzling (like “Emails with exactly 16 digits are always flagged even if not a credit card”), the docs often explain the rationale (maybe a regex pattern or included keyword). They also list all built-in SITs and definitions, which is helpful for troubleshooting patterns. The Microsoft Tech Community forums and blogs are full of Q&A – chances are someone encountered a similar issue (for example, false positives with certain formats) and solutions are posted. Don’t hesitate to search those resources.
• Incremental Rollout: If troubleshooting a really large-scale policy, try applying it to a small pilot group first. For example, scope the policy to just IT department mailboxes for a week. This way, if it misbehaves, impact is limited, and you can gather debug info more easily. Once it’s stable, widen the scope.
• Troubleshoot User Overrides: If you allowed overrides but never see any in logs, it might be that users aren’t noticing they have the option. Ensure the policy tip explicitly tells them they can override if they click a certain link. If overrides are happening but you want to ensure they had proper justification, note that justification texts are recorded – review the incidents; if they left it blank (some older versions didn’t force text), consider requiring it or educating users to fill it in.
• Pitfall: Assuming 100% Prevention: Finally, know the limits – DLP significantly reduces risk but no DLP can guarantee all forms of data loss are stopped. Users can always find ways (e.g., use personal devices to take photos of data, or encrypt data before sending so DLP can’t see it). DLP should be one layer of defense. Combine it with user training, strong access controls, and possibly other tools (like Cloud App Security for shadow IT, etc.) for a more holistic data protection strategy. Set management’s expectation that DLP will catch the common accidental leaks and policy violations, but it’s not magic – vigilant security culture is still needed.

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References and Further Reading

For more detailed information and official guidance, consider these Microsoft resources (which were referenced in compiling this guide):

• Microsoft Learn – Overview of DLP: Learn about data loss prevention[1][1] – an introduction to how DLP works across Microsoft 365, including definitions of policies, locations, and actions.
• Microsoft Learn – DLP Policy Templates: What the DLP policy templates include[6][6] – documentation listing all the out-of-box templates, their included sensitive info types and default rules (useful for deciding which template to start with).
• Microsoft Learn – Create and Deploy a DLP Policy: A step-by-step guide in Microsoft’s documentation for configuring DLP policies, with scenario examples[4][4].
• Tech Community Blog – DLP Step by Step: “Data Loss Prevention Policies [Step by Step Guide]” by a community contributor[9][9] – explains in simple terms the structure of DLP policies (policy > rules > SITs) and provides a walkthrough with screenshots of the process (from 2022 but principles remain similar).
• Microsoft Purview Trainable Classifiers: Get started with trainable classifiers[7][7] – for learning how to create and use trainable classifiers if your DLP needs go beyond built-in patterns.
• Official Microsoft Documentation – Policy Tips and Reports: Articles on customizing and troubleshooting policy tips[2][3], and using the Activity Explorer & alerting dashboard to monitor DLP events[1][1].
• Microsoft 365 Community & FAQs: There are numerous Q&A posts and best-practice nuggets on the Microsoft Community and TechCommunity forums. For example, handling false positives for credit card detection, or guidance on using DLP for GDPR.

By following the guidance in this report and diving into the resources above for specific needs, you can implement DLP policies in Microsoft 365 Business Premium that effectively protect your organisation’s sensitive data across email, SharePoint, and OneDrive. Remember to phase your rollout, educate your users, and continuously refine the policies for optimal results. With DLP in place, you build a safer digital workplace where accidental data leaks are minimized and compliance requirements are met confidently. [5][5]

References

[1] Learn about data loss prevention | Microsoft Learn

[2] Office 365 compliance controls: Data Loss Prevention

[3] Configuring data loss prevention for email from the … – 4sysops

[4] Create and deploy a data loss prevention policy | Microsoft Learn

[5] How to Setup Microsoft 365 Data Loss Prevention: A Comprehensive Guide

[6] What DLP policy templates include | Microsoft Learn

[7] Get started with trainable classifiers | Microsoft Learn

[8] Data loss prevention Exchange conditions and actions reference

[9] Data Loss Prevention Policies [STEP BY STEP GUIDE] | Microsoft …