Microsoft Power BI Data Analyst Exam Guide

Microsoft Power BI is the world's leading business intelligence application, essential for transforming complex organizational data into clear, actionable reports and visual dashboards. This book is a practical guide that teaches you how to create a Power BI report from start to finish, and create compelling and insightful reports and dashboards. This comprehensive guide is your practical, start-to-finish roadmap to prepare you for the official PL-300 Microsoft Certified: Power BI Data Analyst Associate exam.

You will build a thorough understanding of the end-to-end data lifecycle, starting by architecting robust solutions with foundational dimensional modelling and optimal star schema design, combined with understanding licensing models.You will build the high-performance semantic model by defining proper relationships and writing powerful analytical DAX queries, including CALCULATE and context switching. The guide then teaches you how to design compelling and insightful reports before concluding with the necessary skills to ensure scalability with aggregation tables and incremental refresh, manage security, and deploy to the Power BI service app.

Upon completion, you will possess a professional, complete understanding of the entire Power BI process. This resource provides the technical competency and confidence needed to successfully attempt the PL-300 certification exam, and use proper security and configure the Power BI service.

WHAT YOU WILL LEARN

● Power BI components, data warehousing, and licensing models.

● Use Power Query to prepare data using M-code.

● Create scalable Power BI semantic models.

● Write powerful analytical DAX queries utilizing CALCULATE and context switching.

● Design effective and interactive Power BI reports.

● Publish reports and manage Power BI workspaces.

● Implement and setup Power BI security.

WHO THIS BOOK IS FOR

This book is ideal for anyone aiming to create insightful reports and analyze data using Power BI. It targets data analysts, data engineers, and professionals in fields like finance, accounting, and supply chain who work directly with data.