- Published 8/2/2022
- 1st Edition
Prepare for Microsoft Exam PL-300 and help demonstrate your real-world ability to deliver actionable insights with Power BI by leveraging available data and domain expertise; to provide meaningful business value through clear data visualizations; to enable others to perform self-service analytics, and to deploy and configure solutions for consumption. Designed for data analysts, business users, and other professionals, this Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified: Power BI Data Analyst Associate level.
Focus on the expertise measured by these objectives:
- Prepare the data
- Model the data
- Visualize and analyze the data
- Deploy and maintain assets
This Microsoft Exam Ref:
- Organizes its coverage by exam objectives
- Features strategic, what-if scenarios to challenge you
- Assumes you are a data analyst, business intelligence professional, report creator, or other professional seeking to validate your skills and knowledge in analyzing data with Power BI
About the Exam
Exam PL-300 focuses on knowledge needed to get data from different data sources; clean, transform, and load data; design and develop data models; create model calculations with DAX; optimize model performance; create reports and dashboards; enhance reports for usability and storytelling; identify patterns and trends; and manage files, datasets, and workspaces.
About Microsoft Certification
Passing this exam fulfills your requirements for the Microsoft Certified: Power BI Data Analyst Associate certification, demonstrating your understanding of data repositories and data processes, and your skills in designing and building scalable data models, cleaning and transforming data, enabling advanced analytic capabilities to provide meaningful business value, and collaborating with key stakeholders to deliver relevant insights based on identified business requirements.
See full details at: microsoft.com/learn
Table of Contents
CHAPTER 1 Prepare the data
CHAPTER 2 Model the data
CHAPTER 3 Visualize and analyze the data
CHAPTER 4 Deploy and maintain assets