This course focuses on preparing integrated datasets for analytics, reporting, and business intelligence workloads within Microsoft Fabric. Learners explore how data engineers structure datasets so they can be efficiently queried, modeled, and used by analytics tools such as Power BI and SQL endpoints. The course introduces key concepts that transform integrated datasets into analytics-ready data assets, including dataset structure, modeling considerations, and query workflows. Learners examine how Lakehouse tables and Fabric Warehouses support analytical workloads and how structured datasets enable reliable reporting and decision-making. Through practical scenarios and guided demonstrations, learners develop an understanding of how data engineers prepare datasets for analytical consumption, ensuring that datasets are reliable, accessible, and optimized for downstream analytics tools. The course concludes with a portfolio project in which learners prepare and validate an analytics-ready dataset within a Fabric environment.
What you'll learn
understand how to structure datasets for analytics
learn about Lakehouse tables and Fabric Warehouses
gain skills in preparing datasets for analytical tools like Power BI and SQL
develop a portfolio project involving dataset preparation
Course objectives
to teach methods for structuring and modeling datasets
to ensure learners can create reliable and accessible datasets for analytics