On May 23rd, Microsoft Fabric was released to public preview. Fabric weaves together a number of underlying technologies with a unified UI, a single, serverless compute pool, a single, shared copy of all data and compatibility with Microsoft’s operational database technologies, including Azure SQL Database, Cosmos DB, and the ever-enduring SQL Server!
And now that Microsoft has combined many of its separate analytics services into one, mixing open source and long-established Microsoft technologies into single SaaS platform, it's time to get up to speed on Fabric and the many data analytics concepts it encapsulates.
That's what this session is for. We'll being by covering the basics of OneLake, Apache Parquet and Delta Lake, which are Fabric's central data store technologies. From there, we will branch out into the rigors of Apache Spark, Fabric data pipelines, data lakehouses and data warehouses, and their tie-ins with Power BI. We'll touch on streaming data and data science/machine learning and we'll finish up by discussing Fabric's planned/future capabilities.
If you've been waiting for data analytics, business intelligence and data science to "come to you," you've bargained well, and the now time has come. Get to this session to see what it's all about.
You will learn:
- Basic analytics concepts, including data lakes, columnar storage and dimensional analysis
- How Fabric combines elements of Azure services like Synapse Analytics, Data Factory, Event Hubs, Stream Analytics and Data Explorer with Power BI and open source technologies, and makes them all easier to use
- How analysts, data engineers and data scientists can collaborate on the same data, using their own toolchains and skillsets
- The economics of unified, SaaS-based analytics vs. specialized, PaaS-based solutions