Choosing Analytics Data Stores in Fabric

With multiple data storage paradigms available, choosing the right architecture is critical for any modern data project. This text-only course helps you navigate the options in Fabric, ensuring you select the optimal store for your analytical workloads. You will learn to confidently evaluate and compare different analytical data stores, aligning them with business requirements, data structures, and team capabilities. By understanding the core mechanics of each store type, you will design efficient, scalable, and cost-effective data solutions. What you'll learn: Understand the foundational architecture of Fabric, including OneLake and Delta Lake integration; Evaluate the differences between Lakehouse, Warehouse, and Eventhouse storage options; Analyze data formats, query languages like T-SQL and KQL, and write patterns to match workloads; Map business scenarios to the most efficient and cost-effective data store; Apply modern data architecture principles, such as the Medallion architecture, to organize your data; Configure basic security and access control patterns across different storage types. The course begins with essential terminology and the concept of a unified data lake, before guiding you through detailed comparisons of structured, semi-structured, and real-time streaming data stores. You will then explore practical decision-making frameworks to select the right storage option for real-world scenarios. This course is designed for beginner data analysts, database administrators, and aspiring data architects; no prior experience with Fabric is required. Start reading today to master the art of data store selection and optimize your analytical workloads.