Decision Guide for Selecting an Analytical Data Store in Microsoft Fabric
Learn how to select an analytical data store in Microsoft Fabric based on your workload's data volumes, data type requirements, compute engine preferences, data ingestion patterns, data transformation needs, query patterns, and other factors.Microsoft Fabric for those who know nothing about Fabric
This is not any regular blog, don't click on this blog if you don't want to get convinced, if you are curious, click and see. You will end up falling in love with Microsoft Fabric. Yes, that's because you will love it when you get to know what it is.Approaches to Integrating Azure Databricks with Microsoft Fabric: The Better Together Story!
Azure Databricks and Microsoft Fabric can be combined to create a unified and scalable analytics ecosystem. This document outlines eight distinct integration approaches, each accompanied by step-by-step implementation guidance and key design considerations. These methods are not prescriptive—your cloud architecture team can choose the integration strategy that best aligns with your organization’s governance model, workload requirements and platform preferences. Whether you prioritize centralized orchestration, direct data access, or seamless reporting, the flexibility of these options allows you to tailor the solution to your specific needs.
Elevating care management analytics with Copilot for Power BI
Healthcare data solutions care management analytics capability offers a comprehensive template using the medallion Lakehouse architecture to unify and analyze diverse data sets of meaningful insights. This enables enhanced care coordination, improved patient outcomes, and scalable, sustainable insights. As the healthcare industry faces rising costs and growing demand for personalized care, data and AI are becoming critical tools. Copilot for Power BI leads this shift, blending AI-driven insights with advanced visualization to revolutionize care delivery. What is Copilot for Power BI? Copilot is an AI-powered assistant embedded directly into Power BI, Microsoft's interactive data visualization platform. By leveraging natural language processing and machine learning, Copilot helps users interact with their data more intuitively whether by asking questions in plain English, generating complex calculations, or uncovering patterns that might otherwise go unnoticed. Copilot for Power BI is embedded within healthcare data solutions, allowing care management—one of its core capabilities—to harness these AI-driven insights. In the context of care management analytics, this means turning a sea of clinical, claims, and operational data into actionable insights without needing to write a single line of code. This empowers teams across all technical levels to gain value from data. Driving better outcomes through intelligent insights in care management analytics The Care Management Analytics solution, built on the Healthcare data solutions platform, leverages Power BI with Copilot embedded directly within it. Here’s how Copilot for Power BI is revolutionizing care management: Enhancing decision-making with AI Traditionally, deriving insights from healthcare data required technical expertise and hours of analysis. Copilot simplifies this by allowing care managers and clinicians to ask questions like “Analyze which medical conditions have the highest cost and prevalence in low-income regions.” The AI interprets these queries and responds with visualizations, trends, and predictions—empowering faster, data-driven decisions. Proactive care planning By analyzing historical and real-time data, Copilot helps identify at-risk patients before complications arise. This enables care teams to intervene earlier, design more personalized care plans, and ultimately improve outcomes while reducing unnecessary hospitalizations. Operational efficiency From staffing models to resource allocation, Copilot provides visibility into operational metrics that can drive significant efficiency gains. Healthcare leaders can quickly identify bottlenecks, monitor key performance indicators (KPIs) and simulate “what-if” scenarios, enabling more i nformed, data-backed decisions on care delivery models. Reducing costs without compromising quality Cost containment is a constant challenge in healthcare. By highlighting areas of high spend and correlating them with clinical outcomes, Copilot empowers organizations to optimize care pathways and eliminate inefficiencies ensuring patients receive the right care at the right time, without waste. Democratizing data access Perhaps one of the most transformative aspects of Copilot is how it democratizes access to analytics. Non-technical users from care coordinators to nurse managers can interact with dashboards, explore data, and generate insights independently. This cultural shift encourages a more data-literate workforce and fosters collaboration across teams. Real-world impact Consider a healthcare system leveraging Power BI and Copilot to manage chronic disease populations more effectively. By combining claims data, social determinants of health (SDoH) indicators, and patient-reported outcomes, care teams can gain a comprehensive view of patient needs- enabling more coordinated care and proactively identifying care gaps. With these insights, organizations can launch targeted outreach initiatives that reduce avoidable emergency department (ED) visits, improve medication adherence, and ultimately enhance outcomes. The future is here The integration of Copilot for Power BI marks a pivotal moment for healthcare analytics. It bridges the gap between data and action, bringing AI to the frontlines of care. As the industry continues to embrace value-based care models, tools like Copilot will be essential in achieving the triple aim: better care, lower costs, and improved patient experience. Copilot is more than a tool — it is a strategic partner in you care transformation journey. Deployment of care management analytics Showcasing how a Population Health Director uncovers actionable insights through Copilot Note: To fully leverage the capabilities of the solution, please follow the deployment steps provided and use the sample data included with the Healthcare Data Solution. For more information on care management analytics, please review our detailed documentation and get started with transforming your healthcare data landscape today Overview of care management analytics - Microsoft Cloud for Healthcare | Microsoft Learn Deploy and analyze using Care management analytics - Training | Microsoft Learn. Medical device disclaimer: Microsoft products and services (1) are not designed, intended or made available as a medical device, and (2) are not designed or intended to be a substitute for professional medical advice, diagnosis, treatment, or judgment and should not be used to replace or as a substitute for professional medical advice, diagnosis, treatment, or judgment. Customers/partners are responsible for ensuring solutions comply with applicable laws and regulations.
Upgrade performance, availability and security with new features in Azure Database for PostgreSQL
At Microsoft Build 2025 the Postgres on Azure team is announcing an exciting set of improvements and features for Azure Database for PostgreSQL. One area we are always focused on is the enterprise. This week we are delighted to announce improvements across the enterprise pillars of Performance, Availability and Security. In addition, we're improving Integration of Postgres workloads with services like ADF and Fabric. Here's a quick tour of the enterprise enhancements to Azure Database for PostgreSQL being announced this week. Performance and scale SSD v2 with HA support - Public Preview The public preview of zone-redundant high availability (HA) support for the Premium SSD v2 storage tier with Azure Database for PostgreSQL flexible server is now available. You can now enable High Availability with zone redundancy using Azure Premium SSD v2 when deploying flexible server, helping you achieve a Recovery Point Objective (RPO) of zero for mission-critical workloads. Premium SSD v2 offers sub-millisecond latency and outstanding performance at a low cost, making it ideal for IO-intensive, enterprise-grade workloads. With this update, you can significantly boost the price-performance of your PostgreSQL deployments on Azure and improve availability with reduced downtime during HA failover. The key benefits of SSD v2 include: Flexible disk sizing from 1 GiB to 64 TiB, with 1-GiB increment support Independent performance configuration: scale up to 80,000 IOPS and 1,200 MBps throughput without needing to provision larger disks To learn more about how to upgrade and best practices, visit: Premium SSDv2 PostgreSQL 17 Major Version Upgrade – Public Preview PostgreSQL version 17 brings a host of performance improvements, including a more efficient VACUUM process, faster sequential scans via streaming IO, and optimized query execution. Now, with the public preview of in-place major version upgrades to PostgreSQL 17 there is an easier path to v17 for your existing flexible server workloads. With this release, you can upgrade from earlier versions (14, 15, or 16) to PostgreSQL 17 without the need to migrate data or change server endpoints, simplifying the upgrade process and minimizing downtime. Azure’s in-place upgrade capability offers a native, low-disruption upgrade path directly from the Azure Portal or CLI. For upgrade steps and best practices, check out our detailed blog post. Availability Long-Term Backup (LTR) for Azure Database for PostgreSQL flexible server - Generally Available Long-term backups are essential for organizations with regulatory, compliance, and audit-driven requirements, especially in industries like finance and healthcare. Certifications such as HIPAA often mandate data retention periods up to 10 years, far exceeding the default 35-day retention limit provided by point-in-time restore (PITR) capabilities. Long-term backup for Azure Database for PostgreSQL flexible server, powered by Azure Backup is now generally available. With this release, you can now benefit from: Policy-driven, one-click enablement of long-term backups Resilient data retention across Azure Storage tiers Consumption-based pricing with no egress charges Support for restoring backups well beyond community-supported PostgreSQL versions This LTR capability uses a logical backup approach based on pg_dump and pg_restore, offering a flexible, open-source format that enhances portability and ensures your data can be restored across a variety of environments including Azure VMs, on-premises, or even other cloud providers. Learn more about long term retention: Backup and restore - Azure Database for PostgreSQL flexible server Azure Databases for PostgreSQL flexible server Resiliency Solution accelerator When it comes to ensuring business continuity, your database infrastructure is the most critical component. In addition to product documentation, it is important to have access to opinionated solution architecture, industry-proven recommended practices, and deployable infra-as-code that you can learn and customize to ensure an automated production-ready resilient infrastructure for your data. The Azure Database for PostgreSQL Resiliency Solution Accelerator is now available, providing a set of deployable architectures to ensure business continuity, minimize downtime, and protect data integrity during planned and unplanned events. In additional to architecture and recommended practices, a customizable Terraform deployment workflow is provided. Learn more: Azure Database for PostgreSQL Resiliency Solution Accelerator Security Automatic Customer Managed Key (CMK) version updates - Generally Available Azure Database for PostgreSQL flexible server data is fully encrypted, supporting both Service Managed and Customer Managed encryption keys (CMK). Automatic version updates for CMK (also known as “versionless keys”) is now generally available. This change simplifies the key lifecycle management by allowing PostgreSQL to automatically adopt new keys without needing manual updates. Combined with Azure Key Vault's auto-rotation feature this significantly reduces the management overhead of encryption key maintenance. Learn more about automatic CMK version updates. Azure confidential computing SKUs for flexible server - Public Preview Azure confidential computing enables secure sensitive and regulated data, preventing unwanted access of data in-use, by cloud providers, administrators, or external users. With the public preview of Azure confidential SKUs for Azure Database for PostgreSQL flexible server you can now select from a range of Confidential Computing VM sizes to run your PostgreSQL workloads in a hardware-based trusted execution environment (TEE). Azure confidential computing encrypts data in TEE, processing data in a verified environment, enabling you to securely process workloads while meeting compliance and regulatory demands. Learn more about confidential computing with the Azure Database for flexible server. Integration Entra Authentication for Azure Data Factory & Azure Synapse - Generally Available In an era of bring-your-own-device and cloud-enabled apps it is increasingly important for enterprises to maintain central control an identity-based security perimeter. With integrated Entra ID support, Azure Database for PostgreSQL flexible server allows you to bring your database workloads within this perimeter. But how do you securely connect to other services? Entra ID authentication is now supported in the Azure Data Factory and Azure Synapse connectors for Azure Database for PostgreSQL. This feature enables seamless, secure connectivity using Service Principal (key or certificate) and both User-Assigned and System-Assigned Managed Identities, streamlining access to your data pipelines and analytics workloads. Learn more about How to Connect from Azure Data Factory and Synapse Analytics to Azure Database for PostgreSQL. Fabric Data Factory – Upsert Method & Script Activity - Generally Available The Microsoft Fabric has become to go-to data analytics platform with services and tools for every data lifecycle state. To improve customization and fine-grained control over processing of PostgreSQL data, the Upsert Method and custom Script Activity are now generally available in Fabric Data Factory when using Azure Database for PostgreSQL as a source or sink. Upsert Method enables intelligent insert-or-update logic for PostgreSQL, making it easier to handle incremental data loads and change data capture (CDC) scenarios without complex workarounds. Script Activity allows you to embed and execute your own SQL scripts directly within pipelines—ideal for advanced transformations, procedural logic, and fine-grained control over data operations. These capabilities offer enhanced flexibility for building robust, enterprise-grade data workflows, simplifying your ETL processes. Connect to VS Code from the Azure Portal - Public Preview With the exciting announcement of a revamped VS Code PostgreSQL extension preview this week, we're adding a new connection option to the Azure Portal to connect to your flexible server with VS Code, creating a more unified and efficient developer experience. Here's why it matters: One Click Connectivity: No manual connection strings or configuration needed. Faster Onboarding: Go from provisioning a database in Azure to exploring and managing it in VS Code within seconds. Integrated Workflow: Manage infrastructure and development from a single, cohesive environment. Productivity: Connect directly from the Portal to leverage VS Code extension features like query editing, result views, and schema browsing. Where to learn more The Build 2025 announcements this week are just the latest in a compelling set of features delivered by the Azure Database for PostgreSQL team and build on our latest set of monthly feature updates (see: April 2025 Recap: Azure Database for PostgreSQL Flexible Server). Follow the Azure Database for PostgreSQL Blog where you'll see many of the latest updates from Build, including What's New with PostgreSQL @Build, and New Generative AI Features in Azure Database for PostgreSQL.Microsoft Fabric & AI Learning Hackathon Informational AMA: What will you build?
The Microsoft Fabric & AI Learning Hackathon is underway and we're excited to learn about your project ideas and questions! Join us for an interactive session where we'll look at recent announcements from the European Microsoft Fabric Community Conference, share tips and best practices for competing in the Hackathon, provide technical and informational support, and connect you with expert resources to support ongoing development of your Hackathon project! An AMA is a live text-based online event similar to an “Ask Me Anything” on Reddit. This AMA gives you the opportunity to connect with Microsoft product experts who will be on hand to answer your questions and listen to feedback. The AMA takes place entirely in the comments below. There is no additional video or audio link as this is text-based. Check out this blog post for the official announcement about the Hackathon and check out the Fabric Hackathon website for all the details about the Hackathon. Feel free to post your questions anytime in the comments below beforehand, if it fits your schedule or time zone better, though questions will not be answered until the live hour.What’s New in Kusto – Build 2023 !
We are excited to share the latest features and improvements in Kusto that promise to make your data analysis experience more seamless and productive than ever before. We have been busy working with our customers over the last few months to bring exciting new GA & Preview features to Build 2023, with a raft of improvements and innovations.
Fabric Data Agents: Unlocking the Power of Agents as a Steppingstone for a Modern Data Platform
What Are Fabric Data Agents? Fabric Data Agents are intelligent, AI-powered assistants embedded within Microsoft Fabric, a unified data platform that integrates data ingestion, processing, transformation, and analytics. These agents act as intermediaries between users and data, enabling seamless interaction through natural language queries in the form of Q&A applications. Whether it's retrieving insights, analyzing trends, or generating visualizations, Fabric Data Agents simplify complex data tasks, making advanced analytics accessible to everyone—from data scientists to business analysts to executive teams. How Do They Work? At the center of Fabric Data Agents is OneLake, a unified and governed data lake that joins data from various sources, including on-premises systems, cloud platforms, and third-party databases. OneLake ensures that all data is stored in a common, open format, simplifying data management and enabling agents to access a comprehensive view of the organization's data. Through Fabric’s Data Ingestion capabilities, such as Fabric Data Factory, OneLake Shortcuts, and Fabric Database Mirroring, Fabric Data Agents are designed to connect with over 200 data sources, ensuring seamless integration across an organization's data estate. This connectivity allows them to pull data from diverse systems and provide a unified analytics experience. Here's how Fabric Data Agents work: Natural Language Processing: Using advanced NLP techniques, Fabric Data Agents enable users to interact with data through conversational queries. For example, users can ask questions like, "What are the top-performing investment portfolios this quarter?" and receive precise answers, grounded on enterprise data. AI-powered Insights: The agents process queries, reason over data, and deliver actionable insights, using Azure OpenAI models, all while maintaining data security and compliance. Customization: Fabric data agents are highly customizable. Users can provide custom instructions and examples to tailor their behavior to specific scenarios. Fabric Data Agents allow users to provide example SQL queries, which can be used to influence the agent’s behavior. They also can integrate with Azure AI Agent Service or Microsoft Copilot Studio, where organizations can tailor agents to specific use cases, such as risk assessment or fraud detection. Security and Compliance: Fabric Data Agents are built with enterprise-grade security features, including inheriting Identity Passthrough/On-Behalf-Of (OBO) authentication. This ensures that business users only access data they are authorized to view, keeping strict compliance with regulations like GDPR and CCPA across geographies and user roles. Integration with Azure: Fabric Data Agents are deeply integrated with Azure services, such as Azure AI Agent Service and Azure OpenAI Service. Practically, organizations can publish Fabric Data Agents to custom Copilots using these services and use the APIs in various custom AI applications. This integration ensures scalability, high availability, and performance and exceptional customer experience. Why Should Financial Services Companies Use Fabric Data Agents? The financial services industry faces unique challenges, including stringent regulatory requirements, the need for real-time decision-making, and empowering users to interact with an AI application in a Q&A fashion over enterprise data. Fabric Data Agents address these challenges head-on through: Enhanced Efficiency: Automate repetitive tasks, freeing up valuable time for employees to focus on strategic initiatives. Improved Compliance: Use robust data governance features to ensure compliance with regulations like GDPR and CCPA. Data-Driven Decisions: Gain deeper insights into customer behavior, market trends, and operational performance. Scalability: Seamlessly scale analytics capabilities to meet the demands of a growing organization, without really investing in building custom AI applications which require deep expertise. Integration with Azure: Fabric Data Agents are natively designed to integrate across Microsoft’s ecosystem, providing a comprehensive end-to-end solution for a Modern Data Platform. How different are Fabric Data Agents from Copilot Studio Agents? Fabric Data Agents and Copilot Studio Agents serve distinct purposes within Microsoft's ecosystem: Fabric Data Agents are tailored for data science workflows. They integrate AI capabilities to interact with organizational data, providing analytics insights. They focus on data processing and analysis using the medallion architecture (bronze, silver, and gold layers) and support integration with the Lakehouse, Data Warehouse, KQL Databases and Semantic Models. Copilot Studio Agents, on the other hand, are customizable AI-powered assistants designed for specific tasks. Built within Copilot Studio, they can connect to various enterprise data sources like OneLake, AI Search, SharePoint, OneDrive, and Dynamics 365. These agents are versatile, enabling businesses to automate workflows, analyze data, and provide contextual responses by using APIs and built-in connectors. What are the technical requirements for using Fabric Data Agents? A paid F64 or higher Fabric capacity resource Fabric data agent tenant settingsis enabled. Copilot tenant switchis enabled. Cross-geo processing for AIis enabled. Cross-geo storing for AIis enabled. At least one of these: Fabric Data Warehouse, Fabric Lakehouse, one or more Power BI semantic models, or a KQL database with data. Power BI semantic models via XMLA endpoints tenant switchis enabled for Power BI semantic model data sources. Final Thoughts In a data-driven world, Fabric Data Agents are poised to redefine how financial services organizations operate and innovate. By simplifying complex data processes, enabling actionable insights, and fostering collaboration across teams, these intelligent agents empower organizations to unlock the true potential of their data. Paired with the robust capabilities of Microsoft Fabric and Azure, financial institutions can confidently navigate industry challenges, drive growth, and deliver superior customer experiences. Adopting Fabric Data Agents is not just an upgrade—it's a transformative step towards building a resilient and future-ready business. The time to embrace the data revolution is now. Learn how to create Fabric Data Agents
