Accelerate Your Security Copilot Readiness with Our Global Technical Workshop Series
The Security Copilot team delivers free, hands-on virtual technical workshops for practitioners looking to build AI-for-Security expertise across Microsoft Entra, Intune, Purview, and Threat Protection. These sessions help you onboard, configure, and operationalize Security Copilot—including working with agents—in real-world scenarios. Offered year-round across multiple time zones, they’re led by Microsoft engineering experts and focused on 100% technical, scenario-driven learning through demos, labs, and live Q&A. These workshops are ideal for Security Architects & Engineers, SOC Analysts, Identity & Access Management Engineers, Endpoint & Device Admins, Compliance & Risk Practitioners, Partner Technical Consultants and Customer technical teams adopting AI powered defense. Register now! Below is the schedule of global live deliveries as well as recorded versions of all Security Copilot Virtual Workshops. Join a live workshop: Start building Security Copilot skills—choose the product area and time zone that works best for you. Please take note of pre-requisites for each workshop in the registration page. Please note at the moment we are not able to accept participants from Russia, China and North Korea. Security Copilot Virtual Workshop: Copilot in Defender North America time zone July 22, 2026 at 8:00-9:30 AM (PST) - register here August 19, 2026 at 8:00-9:30 AM (PST) - register here September 16, 2026 at 8:00-9:30 AM (PST) - register here Asia Pacific time zone July 23, 2026 - register here August 20, 2026 - register here September 17, 2026 - register here Security Copilot Virtual Workshop: Copilot in Entra North America time zone July 15, 2026 at 8:00-9:30 AM (PST) - register here August 14, 2026 at 8:00-9:30 AM (PST) - register here Asia Pacific time zone June 18, 2026 - register here August 13, 2026 - register here September 10, 2026 - register here Security Copilot Virtual Workshop: Copilot in Intune North America time zone July 1, 2026 at 8:00-9:30 AM (PST) - register here July 29, 2026 at 8:00-9:30 AM (PST) -register here August 26, 2026 at 8:00-9:30 AM (PST) -register here September 23, 2026 at 8:00-9:30 AM (PST) -register here Asia Pacific time zone July 2, 2026 - register here July 30, 2026 -register here August 27, 2026 -register here Security Copilot Virtual Workshop: Copilot in Purview North America time zone July 8, 2026 at 8:00-9:30 AM (PST) - register here August 5, 2026 at 8:00-9:30 AM (PST) -register here September 2, 2026 at 8:00-9:30 AM (PST) -register here Asia Pacific time zone July 9, 2026 -register here August 6, 2026 -register here September 3, 2026 -register here October 1, 2026 -register here Can't join live? No problem! Access the recordings and workshop guides Copilot in Defender workshop recording Workshop guide Copilot in Purview workshop recording Workshop guide Copilot in Entra workshop recording Workshop guide Copilot in Intune workshop recording Workshop guide Learn and Engage with the Microsoft Security Community Log in and follow this Microsoft Security Community Blog and post/ interact in the Microsoft Security Community discussion spaces. Follow = Click the heart in the upper right when you're logged in 🤍 Join the Microsoft Security Community and be notified of upcoming events, product feedback surveys, and more. Get early access to Microsoft Security products and provide feedback to engineers by joining the Microsoft Security Advisors.. Learn about the Microsoft MVP Program. Join the Microsoft Security Community LinkedIn and the Microsoft Entra Community LinkedInSecure AI Workloads in Azure: Join Our Next Azure Decoded Session on April 8th
AI introduces new risks—like prompt injection, data leakage, and model misuse—which means security teams need visibility and guardrails that extend beyond traditional cloud controls. In our next Azure Decoded session, we’ll focus on securing AI workloads in Azure with Microsoft Defender for Cloud. Register now for the Azure Decoded session on April 8th at 12 PM PST. Bringing AI security architecture to life with Azure Decoded In the Lockdown AI workloads with Microsoft Defender for Cloud session, we move from concepts to implementation and show how these protections appear in the platform. We’ll walk through where Microsoft Defender for Cloud fits into an end-to-end AI security strategy—and how discovery, posture management, and runtime protection work together to secure AI workloads built on Azure. You’ll also see how to connect the dots across the workflow—so signals from AI resources, identity, and data controls roll up into actionable recommendations and alerts. Enable and scope the AI workloads protections in Defender for Cloud Use the Data & AI security dashboard to understand coverage and priority risks Review posture findings (CSPM) and translate them into remediation steps Investigate runtime detections (CWP) and see how they map into Microsoft Defender XDR Our goal isn’t theory for theory’s sake. It’s to help you see how AI security shows up in real architecture and real workflows—so you can apply it confidently in your own environment. Who is this session for? We built this session for practitioners who are actively working with AI in Azure, including: Developers building AI applications and agents Security engineers responsible for protecting AI workloads Cloud architects designing enterprise‑ready AI solutions If you’re balancing innovation with security and governance, this session is designed to help you translate AI security concepts into concrete steps in Azure. Before you join: Familiarity with core Azure concepts (subscriptions, resource groups, identity, networking) is helpful. You don’t need to be a machine learning expert—the focus is on securing the cloud resources and workflows that power AI solutions. From AI security concepts to platform protections If you’d like to get the most out of the session, start with the Microsoft Learn module Protect AI workloads with Microsoft Defender for Cloud. It introduces the building blocks of AI workloads in Azure and the security considerations that come with them. In the module, you’ll learn how to: Identify the layers that make up AI workloads in Azure Understand AI-specific risks, including prompt injection, data leakage, and model misuse Use Microsoft Foundry guardrails and observability to monitor and constrain model behavior See how Defender for Cloud, Microsoft Purview, and Microsoft Entra ID work together for defense in depth and governance Think of this as your foundation: it connects AI workload architecture to the controls you’ll configure in Azure, so you can protect inputs and outputs, maintain visibility, and apply governance without slowing delivery. Catch up on the previous Azure Decoded session If you missed the previous Azure Decoded session—or want a refresher—you can watch it on demand on YouTube: ▶️ Watch the previous Azure Decoded session on YouTube It’s a helpful refresher and sets the stage for the April 8 discussion. Turn learning into hands-on skills If you want to move the show, you can do this in your environment. The Microsoft Applied Skills credential, Secure AI Solutions in the Cloud, is a great next step after the Azure Decoded session. You will: Scope and enable protections for AI-related resources and workloads in Azure Validate coverage and prioritize risks using the Data & AI security dashboard Find and remediate posture gaps (CSPM) that increase exposure for AI workloads Investigate runtime detections (CWP) and understand what they mean in the context of AI workload behavior Triage AI-related alerts and incidents in Microsoft Defender XDR and decide on next steps Get started 1️⃣ Register for Azure Decoded: Lock Down AI Workloads with Microsoft Defender for Cloud 2️⃣ Watch the previous Azure Decoded session before April 8th (optional refresher) 3️⃣ Earn the Microsoft Applied Skills: Secure AI Solutions in the Cloud credential to showcase skills. The goal is to leave with something reusable: a practical sequence you can apply to new projects to confirm coverage, reduce posture gaps, and respond quickly when Defender signals suspicious activity tied to AI workloads.How to deploy Microsoft Purview DSPM for AI to secure your AI apps
Microsoft Purview Data Security Posture Management (DSPM for AI) is designed to enhance data security for the following AI applications: Microsoft Copilot experiences, including Microsoft 365 Copilot. Enterprise AI apps, including ChatGPT enterprise integration. Other AI apps, including all other AI applications like ChatGPT consumer, Microsoft Copilot, DeepSeek, and Google Gemini, accessed through the browser. In this blog, we will dive into the different policies and reporting we have to discover, protect and govern these three types of AI applications. Prerequisites Please refer to the prerequisites for DSPM for AI in the Microsoft Learn Docs. Login to the Purview portal To begin, start by logging into Microsoft 365 Purview portal with your admin credentials: In the Microsoft Purview portal, go to the Home page. Find DSPM for AI under solutions. 1. Securing Microsoft 365 Copilot Be sure to check out our blog on How to use the DSPM for AI data assessment report to help you address oversharing concerns when you deploy Microsoft 365 Copilot. Discover potential data security risks in Microsoft 365 Copilot interactions In the Overview tab of DSPM for AI, start with the tasks in “Get Started” and Activate Purview Audit if you have not yet activated it in your tenant to get insights into user interactions with Microsoft Copilot experiences In the Recommendations tab, review the recommendations that are under “Not Started”. Create the following data discovery policy to discover sensitive information in AI interactions by clicking into it. Detect risky interactions in AI apps - This public preview Purview Insider Risk Management policy helps calculate user risk by detecting risky prompts and responses in Microsoft 365 Copilot experiences. Click here to learn more about Risky AI usage policy. With the policies to discover sensitive information in Microsoft Copilot experiences in place, head back to the Reports tab of DSPM for AI to discover any AI interactions that may be risky, with the option to filter to Microsoft Copilot Experiences, and review the following for Microsoft Copilot experiences: Total interactions over time (Microsoft Copilot) Sensitive interactions per AI app Top unethical AI interactions Top sensitivity labels references in Microsoft 365 Copilot Insider Risk severity Insider risk severity per AI app Potential risky AI usage Protect sensitive data in Microsoft 365 Copilot interactions From the Reports tab, click on “View details” for each of the report graphs to view detailed activities in the Activity Explorer. Using available filters, filter the results to view activities from Microsoft Copilot experiences based on different Activity type, AI app category and App type, Scope, which support administrative units for DSPM for AI, and more. Then drill down to each activity to view details including the capability to view prompts and response with the right permissions. To protect the sensitive data in interactions for Microsoft 365 Copilot, review the Not Started policies in the Recommendations tab and create these policies: Information Protection Policy for Sensitivity Labels - This option creates default sensitivity labels and sensitivity label policies. If you've already configured sensitivity labels and their policies, this configuration is skipped. Protect sensitive data referenced in Microsoft 365 Copilot - This guides you through the process of creating a Purview Data Loss Prevention (DLP) policy to restrict the processing of content with specific sensitivity labels in Copilot interactions. Click here to learn more about Data Loss Prevention for Microsoft 365 Copilot. Protect sensitive data referenced in Copilot responses - Sensitivity labels help protect files by controlling user access to data. Microsoft 365 Copilot honors sensitivity labels on files and only shows users files they already have access to in prompts and responses. Use Data assessments to identify potential oversharing risks, including unlabeled files. Stay tuned for an upcoming blog post on using DSPM for AI data assessments! Use Copilot to improve your data security posture - Data Security Posture Management combines deep insights with Security Copilot capabilities to help you identify and address security risks in your org. Once you have created policies from the Recommendations tab, you can go to the Policies tab to review and manage all the policies you have created across your organization to discover and safeguard AI activity in one centralized place, as well as edit the policies or investigate alerts associated with those policies in solution. Note that additional policies not from the Recommendations tab will also appear in the Policies tab when DSPM for AI identifies them as policies to Secure and govern all AI apps. Govern the prompts and responses in Microsoft 365 Copilot interactions Understand and comply with AI regulations by selecting “Guided assistance to AI regulations” in the Recommendations tab and walking through the “Actions to take”. From the Recommendations tab, create a Control unethical behavior in AI Purview Communications Compliance policy to detect sensitive information in prompts and responses and address potentially unethical behavior in Microsoft Copilot experiences and ChatGPT for Enterprise. This policy covers all users and groups in your organization. To retain and/or delete Microsoft 365 Copilot prompts and responses, setup a Data Lifecycle policy by navigating to Microsoft Purview Data Lifecycle Management and find Retention Policies under the Policies header. You can also preserve, collect, analyze, review, and export Microsoft 365 Copilot interactions by creating an eDiscovery case. 2. Securing Enterprise AI apps Please refer to this amazing blog on Unlocking the Power of Microsoft Purview for ChatGPT Enterprise | Microsoft Community Hub for detailed information on how to integrate with ChatGPT for enterprise, the Purview solutions it currently supports through Purview Communication Compliance, Insider Risk Management, eDiscovery, and Data Lifecycle Management. Learn more about the feature also through our public documentation. 3. Securing other AI Microsoft Purview DSPM for AI currently supports the following list of AI sites. Be sure to also check out our blog on the new Microsoft Purview data security controls for the browser & network to secure other AI apps. Discover potential data security risks in prompts sent to other AI apps In the Overview tab of DSPM for AI, go through these three steps in “Get Started” to discover potential data security risk in other AI interactions: Install Microsoft Purview browser extension For Windows users: The Purview extension is not necessary for the enforcement of data loss prevention on the Edge browser but required for Chrome to detect sensitive info pasted or uploaded to AI sites. The extension is also required to detect browsing to other AI sites through an Insider Risk Management policy for both Edge and Chrome browser. Therefore, Purview browser extension is required for both Edge and Chrome in Windows. For MacOS users: The Purview extension is not necessary for the enforcement of data loss prevention on macOS devices, and currently, browsing to other AI sites through Purview Insider Risk Management is not supported on MacOS, therefore, no Purview browser extension is required for MacOS. Extend your insights for data discovery – this one-click collection policy will setup three separate Purview detection policies for other AI apps: Detect sensitive info shared in AI prompts in Edge – a Purview collection policy that detects prompts sent to ChatGPT consumer, Micrsoft Copilot, DeepSeek, and Google Gemini in Microsoft Edge and discovers sensitive information shared in prompt contents. This policy covers all users and groups in your organization in audit mode only. Detect when users visit AI sites – a Purview Insider Risk Management policy that detects when users use a browser to visit AI sites. Detect sensitive info pasted or uploaded to AI sites – a Purview Endpoint Data loss prevention (eDLP) policy that discovers sensitive content pasted or uploaded in Microsoft Edge, Chrome, and Firefox to AI sites. This policy covers all users and groups in your org in audit mode only. With the policies to discover sensitive information in other AI apps in place, head back to the Reports tab of DSPM for AI to discover any AI interactions that may be risky, with the option to filter by Other AI Apps, and review the following for other AI apps: Total interactions over time (other AI apps) Total visits (other AI apps) Sensitive interactions per AI app Insider Risk severity Insider risk severity per AI app Protect sensitive info shared with other AI apps From the Reports tab, click on “View details” for each of the report graphs to view detailed activities in the Activity Explorer. Using available filters, filter the results to view activities based on different Activity type, AI app category and App type, Scope, which support administrative units for DSPM for AI, and more. To protect the sensitive data in interactions for other AI apps, review the Not Started policies in the Recommendations tab and create these policies: Fortify your data security – This will create three policies to manage your data security risks with other AI apps: 1) Block elevated risk users from pasting or uploading sensitive info on AI sites – this will create a Microsoft Purview endpoint data loss prevention (eDLP) policy that uses adaptive protection to give a warn-with-override to elevated risk users attempting to paste or upload sensitive information to other AI apps in Edge, Chrome, and Firefox. This policy covers all users and groups in your org in test mode. Learn more about adaptive protection in Data loss prevention. 2) Block elevated risk users from submitting prompts to AI apps in Microsoft Edge – this will create a Microsoft Purview browser data loss prevention (DLP) policy, and using adaptive protection, this policy will block elevated, moderate, and minor risk users attempting to put information in other AI apps using Microsoft Edge. This integration is built-in to Microsoft Edge. Learn more about adaptive protection in Data loss prevention. 3) Block sensitive info from being sent to AI apps in Microsoft Edge - this will create a Microsoft Purview browser data loss prevention (DLP) policy to detect inline for a selection of common sensitive information types and blocks prompts being sent to AI apps while using Microsoft Edge. This integration is built-in to Microsoft Edge. Once you have created policies from the Recommendations tab, you can go to the Policies tab to review and manage all the policies you have created across your organization to discover and safeguard AI activity in one centralized place, as well as edit the policies or investigate alerts associated with those policies in solution. Note that additional policies not from the Recommendations tab will also appear in the Policies tab when DSPM for AI identifies them as policies to Secure and govern all AI apps. Conclusion Microsoft Purview DSPM for AI can help you discover, protect, and govern the interactions from AI applications in Microsoft Copilot experiences, Enterprise AI apps, and other AI apps. We recommend you review the Reports in DSPM for AI routinely to discover any new interactions that may be of concern, and to create policies to secure and govern those interactions as necessary. We also recommend you utilize the Activity Explorer in DSPM for AI to review different Activity explorer events while users interacting with AI, including the capability to view prompts and response with the right permissions. We will continue to update this blog with new features that become available in DSPM for AI, so be sure to bookmark this page! Follow-up Reading Check out this blog on the details of each recommended policies in DSPM for AI: Microsoft Purview – Data Security Posture Management (DSPM) for AI | Microsoft Community Hub Address oversharing concerns with Microsoft 365 blueprint - aka.ms/Copilot/Oversharing Microsoft Purview data security and compliance protections for Microsoft 365 Copilot and other generative AI apps | Microsoft Learn Considerations for deploying Microsoft Purview AI Hub and data security and compliance protections for Microsoft 365 Copilot and Microsoft Copilot | Microsoft Learn Commonly used properties in Copilot audit logs - Audit logs for Copilot and AI activities | Microsoft Learn Supported AI sites by Microsoft Purview for data security and compliance protections | Microsoft Learn Where Copilot usage data is stored and how you can audit it - Microsoft 365 Copilot data protection and auditing architecture | Microsoft Learn Downloadable whitepaper: Data Security for AI Adoption | Microsoft Public roadmap for DSPM for AI - Microsoft 365 Roadmap | Microsoft 365AI Security in Azure with Microsoft Defender for Cloud: Learn the How, Join the Session
As organizations accelerate AI adoption, securing AI workloads has become a top priority. Unlike traditional cloud applications, AI systems introduce new risks—such as prompt injection, data leakage, and model misuse—that require a more integrated approach to security and governance. To help developers and security teams understand and address these challenges, we are hosting Azure Decoded: Kickstart AI Security with Microsoft Defender for Cloud, a live session on March 18 th at 12 PM PST focused on securing AI workloads built with Microsoft Foundry and Azure AI services. From AI Security Concepts to Platform Protections A strong foundation for this session starts with the Microsoft Learn module Understand how Microsoft Defender for Cloud supports AI security and governance in Azure. This training introduces how AI workloads are structured in Azure and why they require a different security model than traditional applications. In the module, learners explore: The layers that make up AI workloads in Azure Security risks unique to AI, including prompt injection, data leakage, and model misuse How Microsoft Foundry provides guardrails and observability for AI models How Microsoft Defender for Cloud works with Microsoft Purview and Microsoft Entra ID to deliver a unified, defense‑in‑depth security and governance strategy for AI Together, these services help organizations protect model inputs and outputs, maintain visibility, and enforce governance across AI workloads in Azure. Bringing AI Security Architecture to Life with Azure Decoded The Azure Decoded: Kickstart AI Security with Microsoft Defender for Cloud session on March 18 th builds on these concepts by connecting them to real‑world architecture and platform decisions. Attendees learn how Microsoft Defender for Cloud fits into a broader AI security strategy and how Microsoft Foundry helps apply guardrails, visibility, and governance across AI workloads. This session is designed for: Developers building AI applications and agents on Azure Security engineers responsible for protecting AI workloads Cloud architects designing enterprise‑ready AI solutions By combining conceptual understanding with platform‑level security discussions, the session helps teams design AI solutions that are not only innovative—but also secure, governed, and trustworthy. Be sure to register so you do not miss out. Start Your AI Security Journey AI security is evolving quickly, and it requires both architectural understanding and practical platform knowledge. Start by exploring how Microsoft Defender for Cloud supports AI security and governance in Azure, then join the Azure Decoded session to see how these principles come together in real‑world AI workloads.Advance Your SOC Skills with the Power of Microsoft Sentinel data lake and graph
Microsoft Sentinel has evolved beyond a traditional SIEM into a unified, AI-ready security platform that brings data, analytics, intelligence, and automation together. At the core are Microsoft Sentinel data lake and Microsoft Sentinel graph: data lake enables long-term retention and high-scale analytics, and graph adds entity relationships to speed investigations. We have updated skilling to reflect these changes, so defenders can build the right hands-on skills faster. 1. Learn How to Run High‑Scale Searches with data lake: Search Jobs in Microsoft Sentinel Unit: Use Search Jobs in Microsoft Sentinel What learners will gain This foundational data lake–aligned unit teaches defenders how to run scheduled and large-scale search jobs across massive volumes of security data. It demonstrates how Sentinel’s decoupled compute and storage architecture enables fast, cost-effective queries over long-term retained logs. Practical example Example scenario: Investigating a legacy compromised account A SOC analyst receives a tip that an identity compromised 18 months ago may still be used for periodic access. With data lake–backed search jobs, they can run a query against multi-year sign‑in logs to uncover: When the account was last used What resources were accessed Whether anomalous sign-in patterns (e.g., impossible travel) appear This type of long-term, high-volume search wasn’t feasible in traditional SIEM architectures. 2. Hunt Using Data Lake–Backed Search Jobs Unit: Hunt with Search Jobs (Defender Portal tab) What learners will gain This unit teaches practitioners how to perform deep, data lake–powered threat hunts using the unified Defender portal. Learners apply KQL across long-term datasets to uncover attacker behaviors that unfold gradually or attempt to evade short retention windows. Practical example Example scenario: Detecting low‑and‑slow lateral movement A threat actor has accessed an environment but only touches a machine once every few weeks, blending into normal activity. Using data lake–powered search jobs, a hunter can: Query historical RDP or failed login events spanning 12–24 months Identify patterns of sporadic connections between key servers Highlight dormant periods and anomalies in connection timing This enables detection of advanced persistent threat (APT) behavior that short-term analytics would miss. 3. Query Logs Across the Analytics & Data Lake Tiers Unit: Query logs in Microsoft Sentinel What learners will gain Learners build skills in querying logs across Sentinel’s analytics and data lake tiers using KQL, gaining understanding of data architecture, table types, and best practices for summarization and visualization. Practical example Example scenario: Investigating abnormal OAuth app creation A detection triggers on suspicious OAuth app usage. An analyst uses log query skills learned in this module to: Query Azure activity logs to identify when the OAuth app was created Review audit logs to determine which identity performed the action Correlate multi‑month activity to check if the app has been used to read mail or exfiltrate data This real-world workflow aligns directly with how data lake and analytics-tier logs work together. 4. Investigate Incidents with Graph-Enhanced Context Unit: Investigate incidents What learners will gain This unit introduces the Incident Graph, powered by Microsoft Sentinel graph, which visually maps relationships across entities and alerts to accelerate investigations. Practical example Example scenario: Email compromise spreading to device malware A SOC analyst is reviewing an incident where: A user clicked a phishing email The user’s device later showed anomalous registry changes Lateral movement signals appeared two days later With graph-powered investigation, the analyst can see all signals connected as a single attack chain, enabling them to quickly determine: Where the attack originated Which devices and identities were affected How the attacker moved laterally Whether privilege escalation occurred Graph compresses hours of manual correlation into minutes. 5. Explore Advanced Hunting with Graph Intelligence Unit: Explore Advanced Hunting What learners will gain This unit shows how graph-enhanced Advanced Hunting queries unlock richer insights by enabling entity-aware pivoting across identity, endpoint, SaaS, and cloud signals. Practical example Example scenario: Identifying a compromised identity via graph pivots A hunter suspects a specific user account has been compromised. Using graph‑powered hunting, they can: Query for all devices the user has logged into View all alerts connected to those devices Pivot into cloud app activity associated with the user Visualize relationships between the user, devices, and resources This exposes an attack path that would otherwise require multiple disconnected queries. Why These New Units Matter These updated units get defenders ready for modern security operations: Data Lake enables high-scale, long-term analytics for multi-year investigations, while Graph adds context to reveal attack chains faster. Together, they provide unified data and structured relationships that Security Copilot relies on. Start Learning Today Microsoft Sentinel is moving quickly—make sure your SOC skills keep pace. Jump into the refreshed Microsoft Learn units to sharpen investigations with graph intelligence, unlock data lake–powered analytics at scale, and start applying AI-ready techniques immediately.Ignite your future with new security skills during Microsoft Ignite 2025
Ignite your future with new security skills during Microsoft Ignite 2025 AI and cloud technologies are reshaping every industry. Organizations need professionals who can secure AI solutions, modernize infrastructure, and drive innovation responsibly. Ignite brings together experts, learning, and credentials to help you get skilled for the future. Take on the Secure and Govern AI with Confidence Challenge Start your journey with the Azure Skilling Microsoft Challenge. These curated challenges help you practice real-world scenarios and earn recognition for your skills. One of the challenges featured is the Secure and Govern AI with Confidence challenge. This challenge helps you: Implement AI governance frameworks. Configure responsible AI guardrails in Azure AI Foundry. Apply security best practices for AI workloads. Special Offer: Be among the first 5,000 participants to complete this challenge and receive a discounted certification exam voucher—a perfect way to validate your skills and accelerate your career. Completing this challenge earns you a badge and prepares you for advanced credentials—ideal for anyone looking to lead in AI security. Join the challenge today! Validate Your Expertise with this new Microsoft Applied Skill. Applied Skills assessments are scenario-based, so you demonstrate practical expertise—not just theory. Earn the Secure AI Solutions in the Cloud credential—a job-ready validation of your ability to: Configure security for AI services using Microsoft Defender for Cloud. Implement governance and guardrails in Azure AI Foundry. Protect sensitive data and ensure compliance across AI workloads. This applied skill is designed for professionals who want to lead in AI security, accelerate career growth, and stand out in a competitive market. To learn how to prepare and take the applied skill, visit here. Your Next Steps: Security Plans Ignite isn’t just about live sessions—it’s about giving you on-demand digital content and curated learning paths so you can keep building skills long after the event ends. With 15 curated security plans that discuss topics such as controlling access with Microsoft Entra and securing your organization’s data, find what is relevant to you on Microsoft Ignite: Keep the momentum going page.Step-by-Step Guide: Integrating Microsoft Purview with Azure Databricks and Microsoft Fabric
Co-Authored By: aryananmol, laurenkirkwood and mmanley This article provides practical guidance on setup, cost considerations, and integration steps for Azure Databricks and Microsoft Fabric to help organizations plan for building a strong data governance framework. It outlines how Microsoft Purview can unify governance efforts across cloud platforms, enabling consistent policy enforcement, metadata management, and lineage tracking. The content is tailored for architects and data leaders seeking to execute governance in scalable, hybrid environments. Note: this article focuses mainly on Data Governance features for Microsoft Purview. Why Microsoft Purview Microsoft Purview enables organizations to discover, catalog, and manage data across environments with clarity and control. Automated scanning and classification build a unified view of your data estate enriched with metadata, lineage, and sensitivity labels, and the Unified Catalog gives business-friendly search and governance constructs like domains, data products, glossary terms, and data quality. Note: Microsoft Purview Unified Catalog is being rolled out globally, with availability across multiple Microsoft Entra tenant regions; this page lists supported regions, availability dates, and deployment plans for the Unified Catalog service: Unified Catalog Supported Regions. Understanding Data Governance Features Cost in Purview Under the classic model: Data Map (Classic), users pay for an “always-on” Data Map capacity and scanning compute. In the new model, those infrastructure costs are subsumed into the consumption meters – meaning there are no direct charges for metadata storage or scanning jobs when using the Unified Catalog (Enterprise tier). Essentially, Microsoft stopped billing separately for the underlying data map and scan vCore-hours once you opt into the new model or start fresh with it. You only incur charges when you govern assets or run data processing tasks. This makes costs more predictable and tied to governance value: you can scan as much as needed to populate the catalog without worrying about scan fees and then pay only for the assets you actively manage (“govern”) and any data quality processes you execute. In summary, Purview Enterprise’s pricing is usage-based and divided into two primary areas: (1) Governed Assets and (2) Data Processing (DGPUs). Plan for Governance Microsoft Purview’s data governance framework is built on two core components: Data Map and Unified Catalog. The Data Map acts as the technical foundation, storing metadata about assets discovered through scans across your data estate. It inventories sources and organizes them into collections and domains for technical administration. The Unified Catalog sits on top as the business-facing layer, leveraging the Data Map’s metadata to create a curated marketplace of data products, glossary terms, and governance domains for data consumers and stewards. Before onboarding sources, align Unified Catalog (business-facing) and Data Map (technical inventory) and define roles, domains, and collections so ownership and access boundaries are clear. Here is a documentation that covers roles and permissions in Purview: Permissions in the Microsoft Purview portal | Microsoft Learn. The imageabove helps understand therelationship between the primary data governance solutions, Unified Catalog and Data Map, and the permissions granted by the roles for each solution. Considerations and Steps for Setting up Purview Steps for Setting up Purview: Step 1: Create a Purview Account. In the Azure Portal, use the search bar at the top to navigate to Microsoft Purview Accounts. Once there, click “Create”. This will take you to the following screen: Step 2: Click Next: Configuration and follow the Wizard, completing the necessary fields, including information on Networking, Configurations, and Tags. Then click Review + Create to create your Purview account. Consideration: Private networking: Use Private Endpoints to secure Unified Catalog/Data Map access and scan traffic; follow the new platform private endpoints guidance in the Microsoft Purview portal or migrate classic endpoints. Once your Purview Account is created, you’ll want to set up and manage your organization’s governance strategy to ensure that your data is classified and managed according to the specific lifecycle guidelines you set. Note: Follow the steps in this guide to set up Microsoft Purview Data Lifecycle Management: Data retention policy, labeling, and records management. Data Map Best Practices Design your collections hierarchy to align with organizational strategy—such as by geography, business function, or data domain. Register each data source only once per Purview account to avoid conflicting access controls. If multiple teams consume the same source, register it at a parent collection and create scans under subcollections for visibility. The imageaboveillustrates a recommended approach for structuring your Purview DataMap. Why Collection Structure Matters A well-structured Data Map strategy, including a clearly defined hierarchy of collections and domains, is critical because the Data Map serves as the metadata backbone for Microsoft Purview. It underpins the Unified Catalog, enabling consistent governance, role-based access control, and discoverability across the enterprise. Designing this hierarchy thoughtfully ensures scalability, simplifies permissions management, and provides a solid foundation for implementing enterprise-wide data governance. Purview Integration with Azure Databricks Databricks Workspace Structure In Azure Databricks, each region supports a single Unity Catalog metastore, which is shared across all workspaces within that region. This centralized architecture enables consistent data governance, simplifies access control, and facilitates seamless data sharing across teams. As an administrator, you can scan one workspace in the region using Microsoft Purview to discover and classify data managed by Unity Catalog, since the metastore governs all associated workspaces in a region. If your organization operates across multiple regions and utilizes cross-region data sharing, please review the consideration and workaround outlined below to ensure proper configuration and governance. Follow pre-requisite requirements here, before you register your workspace: Prerequisites to Connect and manage Azure Databricks Unity Catalog in Microsoft Purview. Steps to Register Databricks Workspace Step 1: In the Microsoft Purview portal, navigate to the Data Map section from the left-hand menu. Select Data Sources. Click on Register to begin the process of adding your Databricks workspace. Step 2: Note: There are two Databricks data sources, please review documentation here to review differences in capability: Connect to and manage Azure Databricks Unity Catalog in Microsoft Purview | Microsoft Learn. You can choose either source based on your organization’s needs. Recommended is “Azure Databricks Unity Catalog”: Step 3: Register your workspace. Here are the steps to register your data source: Steps to Register an Azure Databricks workspace in Microsoft Purview. Step 4: Initiate scan for your workspace, follow steps here: Steps to scan Azure Databricks to automatically identify assets. Once you have entered the required information test your connection and click continue to set up scheduled scan trigger. Step 5: For Scan trigger, choose whether to set up a schedule or run the scan once according to your business needs. Step 6: From the left pane, select Data Map and select your data source for your workspace. You can view a list of existing scans on that data source under Recent scans, or you can view all scans on the Scans tab. Review further options here: Manage and Review your Scans. You can review your scanned data sources, history and details here: Navigate to scan run history for a given scan. Limitation: The “Azure Databricks Unity Catalog” data source in Microsoft Purview does not currently support connection via Managed Vnet. As a workaround, the product team recommends using the “Azure Databricks Unity Catalog” source in combination with a Self-hosted Integration Runtime (SHIR) to enable scanning and metadata ingestion. You can find setup guidance here: Create and manage SHIR in Microsoft Purview Choose the right integration runtime configuration Scoped scan support for Unity Catalog is expected to enter private preview soon. You can sign up here: https://aka.ms/dbxpreview. Considerations: If you have delta-shared Databricks-to-Databricks workspaces, you may have duplication in your data assets if you are scanning both Workspaces. The workaround for this scenario is as you add tables/data assets to a Data Product for Governance in Microsoft Purview, you can identify the duplicated tables/data assets using their Fully Qualified Name (FQN). To make identification easier: Look for the keyword “sharing” in the FQN, which indicates a Delta-Shared table. You can also apply tags to these tables for quicker filtering and selection. The screenshot highlights how the FQN appears in the interface, helping you confidently identify and manage your data assets. Purview Integration with Microsoft Fabric Understanding Fabric Integration: Connect Cross-Tenant: This refers to integrating Microsoft Fabric resources across different Microsoft Entra tenants. It enables organizations to share data, reports, and workloads securely between separate tenants, often used in multi-organization collaborations or partner ecosystems. Key considerations include authentication, data governance, and compliance with cross-tenant policies. Connect In-Same-Tenant: This involves connecting Fabric resources within the same Microsoft Entra tenant. It simplifies integration by leveraging shared identity and governance models, allowing seamless access to data, reports, and pipelines across different workspaces or departments under the same organizational umbrella. Requirements: An Azure account with an active subscription. Create an account for free. An active Microsoft Purview account. Authentication is supported via: Managed Identity. Delegated Authentication and Service Principal. Steps to Register Fabric Tenant Step 1: In the Microsoft Purview portal, navigate to the Data Map section from the left-hand menu. Select Data Sources. Click on Register to begin the process of adding your Fabric Tenant (which also includes PowerBI). Step 2: Add in Data Source Name, keep Tenant ID as default (auto-populated). Microsoft Fabric and Microsoft Purview should be in the same tenant. Step 3: Enter in Scan name, enable/disable scanning for personal workspaces. You will notice under Credentials automatically created identity for authenticating Purview account. Note: If your Purview is behind Private Network, follow the guidelines here: Connect to your Microsoft Fabric tenant in same tenant as Microsoft Purview. Step 4: From your Microsoft Fabric, open Settings, Click on Tenant Settings and enable “Service Principals can access read-only admin APIs”, “Enhanced admin API responses within detailed metadata” and “Enhance Admin API responses with DAX and Mashup Expressions” within Admin API Settings section. Step 5: You will need to create a group, add the Purviews' managed identity to the group and add the group under “Service Principals can access read-only admin APIs” section of your tenant settings inside Microsoft Fabric Step 6: Test your connection and setup scope for your scan. Select the required workspaces, click continue and automate a scan trigger. Step 7: From the left pane, select Data Map and select your data source for your workspace. You can view a list of existing scans on that data source under Recent scans, or you can view all scans on the Scans tab. Review further options here: Manage and Review your Scans. You can review your scanned data sources, history and details here: Navigate to scan run history for a given scan. Why Customers Love Purview Kern County unified its approach to securing and governing data with Microsoft Purview, ensuring consistent compliance and streamlined data management across departments. EY accelerated secure AI development by leveraging the Microsoft Purview SDK, enabling robust data governance and privacy controls for advanced analytics and AI initiatives. Prince William County Public Schools created a more cyber-safe classroom environment with Microsoft Purview, protecting sensitive student information while supporting digital learning. FSA (Food Standards Agency) helps keep the UK food supply safe using Microsoft Purview Records Management, ensuring regulatory compliance and safeguarding critical data assets. Conclusion Purview’s Unified Catalog centralizes governance across Discovery, Catalog Management, and Health Management. The Governance features in Purview allow organizations to confidently answer critical questions: What data do we have? Where did it come from? Who is responsible for it? Is it secure and compliant? Can we trust its quality? Microsoft Purview, when integrated with Azure Databricks and Microsoft Fabric, provides a unified approach to cataloging, classifying, and governing data across diverse environments. By leveraging Purview’s Unified Catalog, Data Map, and advanced governance features, organizations can achieve end-to-end visibility, enforce consistent policies, and improve data quality. You might ask, why does data quality matter? Well, in today’s world, data is the new gold. References Microsoft Purview | Microsoft Learn Pricing - Microsoft Purview | Microsoft Azure Use Microsoft Purview to Govern Microsoft Fabric Connect to and manage Azure Databricks Unity Catalog in Microsoft PurviewUnlocking Developer Innovation with Microsoft Sentinel data lake
Introduction Microsoft Sentinel is evolving rapidly, transforming to be both an industry-leading SIEM and an AI-ready platform that empowers agentic defense across the security ecosystem. In our recent webinar: Introduction to Sentinel data lake for Developers, we explored how developers can leverage Sentinel’s unified data lake, extensible architecture, and integrated tools to build innovative security solutions. This post summarizes the key takeaways and actionable insights for developers looking to harness the full power of Sentinel. The Sentinel Platform: A Foundation for Agentic Security Unified Data and Context Sentinel centralizes security data cost-effectively, supporting massive volumes and diverse data types. This unified approach enables advanced analytics, graph-enabled context, and AI-ready data access—all essential for modern security operations. Developers can visualize relationships across assets, activities, and threats, mapping incidents and hunting scenarios with unprecedented clarity. Extensible and Open Platform Sentinel’s open architecture simplifies onboarding and data integration. Out-of-the-box connectors and codeless connector creation make it easy to bring in third-party data. Developers can quickly package and publish agents that leverage the centralized data lake and MCP server, distributing solutions through Microsoft Security Store for maximum reach. The Microsoft Security Store is a storefront for security professionals to discover, buy, and deploy vetted security SaaS solutions and AI agents from our ecosystem partners. These offerings integrate natively with Microsoft Security products—including the Sentinel platform, Defender, and Entra, to deliver end‑to‑end protection. By combining curated, deploy‑ready solutions with intelligent, AI‑assisted workflows, the Store reduces integration friction and speeds time‑to‑value for critical tasks like triage, threat hunting, and access management. Advanced Analytics and AI Integration With support for KQL, Spark, and ML tools, Sentinel separates storage and compute, enabling scalable analytics and semantic search. Jupyter Notebooks hosted in on-demand Spark environments allow for rich data engineering and machine learning directly on the data lake. Security Copilot agents, seamlessly integrated with Sentinel, deliver autonomous and adaptive automation, enhancing both security and IT operations. Developer Scenarios: Unlocking New Possibilities The webinar showcased several developer scenarios enabled by Sentinel’s platform components: Threat Investigations Over Extended Timelines: Query historical data to uncover slow-moving attacks and persistent threats. Behavioral Baselining: Model normal behavior using months of sign-in logs to detect anomalies. Alert Enrichment: Correlate alerts with firewall and NetFlow data to improve accuracy and reduce false positives. Retrospective Threat Hunting: React to new indicators of compromise by running historical queries across the data lake. ML-Powered Insights: Build machine learning models for anomaly detection, alert enrichment, and predictive analytics. These scenarios demonstrate how developers can leverage Sentinel’s data lake, graph capabilities, and integrated analytics to deliver powerful security solutions. End-to-End Developer Journey The following steps outline a potential workflow for developers to ingest and analyze their data within the Sentinel platform. Data Sources: Identify high-value data sources from your environment to integrate with Microsoft Security data. The journey begins with your unique view of the customer’s digital estate. This is data you have in your platform today. Bringing this data into Sentinel helps customers make sense of their entire security landscape at once. Data Ingestion: Import third-party data into the Sentinel data lake for secure, scalable analytics. As customer data flows from various platforms into Sentinel, it is centralized and normalized, providing a unified foundation for advanced analysis and threat detection across the customer’s digital environment. Sentinel data lake and Graph: Run Jupyter Notebook jobs for deep insights, combining contributed and first-party data. Once data resides in the Sentinel data lake, developers can leverage its graph capabilities to model relationships and uncover patterns, empowering customers with comprehensive insights into security events and trends. Agent Creation: Build Security Copilot agents that interact with Sentinel data using natural language prompts. These agents make the customer’s ingested data actionable, allowing users to ask questions or automate tasks, and helping teams quickly respond to threats or investigate incidents using their own enterprise data. Solution Packaging: Package and distribute solutions via the Microsoft Security Store, reaching customers at scale. By packaging these solutions, developers enable customers to seamlessly deploy advanced analytics and automation tools that harness their data journey— from ingestion to actionable insights—across their entire security estate. Conclusion Microsoft Sentinel’s data lake and platform capabilities open new horizons for developers. By centralizing data, enabling advanced analytics, and providing extensible tools, Sentinel empowers you to build solutions that address today’s security challenges and anticipate tomorrow’s threats. Explore the resources below, join the community, and start innovating with Sentinel today! App Assure: For assistance with developing a Sentinel Codeless Connector Framework (CCF) connector, you can contact AzureSentinelPartner@microsoft.com. Microsoft Security Community: aka.ms/communitychoice Next Steps: Resources and Links Ready to dive deeper? Explore these resources to get started: Get Educated! Sentinel data lake general availability announcement Sentinel data lake official documentation Connect Sentinel to Defender Portal Onboarding to Sentinel data lake Integration scenarios (e.g. hunt | jupyter) KQL queries Jupyter notebooks (link) as jobs (link) VS Code Extension Sentinel graph Sentinel MCP server Security Copilot agents Microsoft Security Store Take Action! Bring your data into Sentinel Build a composite solution Explore Security Copilot agents Publish to Microsoft Security Store List existing SaaS apps in Security Store
How to practice SC-200 content on an empty tenant
Hello, I am following the SC 200 course on Microsoft Learn. It is great and everything but my m365 business tenant is empty. I don't have VMs, logs, user activity or anything. I learned some KQL and microsoft provides some datasets for practice. Are there any such data I can load on my tenant for threat hunting and other SC-200 related practices or is there an isolated simulation environment I can use for learning?Announcing a New Microsoft Security Virtual Training Day
We’re thrilled to announce a brand-new opportunity for learning and growth: Microsoft Virtual Training Day: Strength Cloud Security with Microsoft Defender for Cloud! This free, online event is designed to empower professionals with the skills and knowledge needed to thrive in today’s digital landscape. During this training, you’ll be able to: Learn how to increase cloud security using Microsoft Defender for Cloud and how to deploy security across your DevOps workflows. Discover how to detect risks, maintain compliance, and protect hybrid and multicloud environments. Find out how to defend servers, containers, storage, and databases using built-in security. Chat with Microsoft experts—ask questions and get answers on real-world security challenges. Here’s what you can expect: Part 1 Part 2 Introduction Introduction What a comprehensive cloud-native application protection platform looks like Comprehensive workload protection (part 1) Break: 10 minutes Break: 10 minutes Starting with proactive security Comprehensive workload protection (part 2) Break: 10 minutes Automating responses Operationalizing Posture Management Closing question and answer Closing question and answer Why Attend this Virtual Training Day? Microsoft Virtual Training Days offer a host of benefits: Flexible Learning: Attend from anywhere, at your own pace. Expert Instruction: Gain insights from industry leaders and certified professionals. Certification Opportunities: Many sessions prepare you for Microsoft certifications. Networking: Connect with peers and professionals across industries. Free Resources: Access downloadable materials and follow-up learning paths. Earn a voucher: Upon completion of the event, the exam is offered at a 50% discount off the exam rate. Don't miss out on this opportunity. Go and registertoday! For more information on all things security, please visit our Security Hub.
