What is Microsoft Fabric? Components and FAQs
Microsoft Fabric and AI
What if there was a team consisting of players like Michael Jordan, LeBron James, Magic Johnson, Larry Bird, Shaquille O’Neal, Kobe Bryant, etc.? Even the thought sounds very exciting, isn’t it?
Now think about the same for your data management — what if there was a way to combine data lake, data analysis, AI, and visualizations? That’s what Microsoft Fabric does.
Understanding the components of Microsoft Fabric
Even before Microsoft Fabric, you could do data transformation and analysis with multiple Microsoft applications like Data Integration with Data Factory, Data Engineering with Spark, Data Warehousing with Synapse DW, Real-time Analytics with Kusto, Data Science with Azure ML, and Business Intelligence with Power BI.
But the magic of Fabric is that you can do all this and add observability to the mix by leveraging three well-known players: Data Factory, Synapse, and Power BI — combined with a new player: Data Activator. If we continue our basketball analogy creating the — “Dream Team”.
Azure Data Factory: For a modern code-free, autonomous ETL data integration experience Data factory is used to ingest, prepare, and transform data from multiple data sources like databases, warehouses, data lakes, lakehouses, real-time data, etc. This is usually done with two primary high-level data factory implements namely data flows (to leverage more than 300 transformations) and data pipelines (to leverage the out-of-the-box rich data orchestration capabilities)
Azure Synapse: Microsoft Fabric uses Synapse environment for Data Engineering, Data Warehousing, Data Science, and Real-time analytics. This enables data engineers to transform data to support analysis based on Spark combined with a SQL-based data warehouse that fully separates compute from storage, enabling independent scaling of both components. For real-time observational data primarily in JSON or Text format with shifting schemas with Kusto Query Language, or KQL. For data science, you can start right from problem identification to gaining insights based on Apache Spark and Python for data preparation to SynapseML for massively scalable machine learning pipeline creation.
Power BI: There is no need to introduce what Power BI is. Even in 2016, they had more than 5 million subscribers — right now the number would have grown exponentially. With Power BI, users can build and scale a data hub across the entire organization with powerful visuals and analytics. Users can understand data, create reports, and share insights using conversational language and connect across multiple Microsoft 365 apps.
- Added value with Co-pilot: Users can simply describe the visuals and insights they’re looking for and Copilot will do the rest. Users can create and tailor reports in seconds, generate and edit DAX calculations, create narrative summaries, and ask questions about their data, all in conversational language.
Data Activator: For real-time stream processing through a system of detection that automatically alerts your team with relevant information. Data activator (currently under preview only) provides real-time data monitoring to coordinate human and automated actions like setting configurable alert conditions that automatically trigger responses across systems like teams, outlook, etc. all in a no-code experience.
“By 2026, 70% of organizations that successfully apply observability will achieve shorter latency for decision making, enabling competitive advantage” in the marketplace. Because of this, there is a great opportunity to build more mature data and analytics capabilities within — and across — your business.
Source: Top Strategic Technology Trends
After reading all this there might be a question in your mind. If all these existed before (excluding Data Activator), how is Microsoft Fabric different from existing platforms like Azure Synapse or Data Factory?
Frequently asked questions about the Microsoft Fabric
1. Is there a direct upgrade/connector to move from Synapse to Fabric?
No, there is no direct upgrade path or connectors that can automatically migrate your data. To move your Synapse workloads onto Fabric, you will need to manually migrate and modify code including but not limited to notebooks, SQL scripts, and pipelines to enable it to run.
2. How does Microsoft Fabric handle data integration from multiple sources?
Microsoft Fabric provides seamless integration with various data sources, including databases, data lakes, cloud services, and even real-time streaming data by storing all the data in OneLake in Delta parquet format. This means users and apps can access data from the same place eliminating the need for import and export.
3. Is it mandatory for Azure Data customers to move to Microsoft Fabric?
No, Microsoft Fabric is not mandatory for customers who have an established Azure Data services footprint. Clients can decide to move their existing data architecture and services to Microsoft Fabric — but given the cost advantage and the efficiency it provides it would be a logical choice to upgrade or at least get the preview.
