Microsoft Fabric Analytics Engineer Associate study guide hands-on practice and expert tips for acing the DP-600 certification exam
(2026)

Nonfiction

Book

Call Numbers:
TEST/005.74/DP-600/BONK,B

0 Holds on 1 Copy

Availability

Locations Call Number Status
Test collection TEST/005.74/DP-600/BONK,B Due: 11/19/2026

Details

PUBLISHED
Santa Rosa, California : O'Reilly Media, 2026
©2026
EDITION
First edition
DESCRIPTION

xvii, 368 pages : illustrations ; 24 cm

ISBN/ISSN
9798341634817, 9798341634817
LANGUAGE
English
NOTES

Includes index

Introduction to Microsoft Fabric and the certification content -- Part 1, Preparing data. Getting data ; Transforming data ; Querying and analyzing data -- Part II, Implementing and managing semantic models. Designing and building semantic models ; Optimizing enterprise-scale semantic models -- Part III, Maintaining a data and analytics solution. Implementing security and governance ; Maintaining the analytics development lifecycle ; Question bank

"Data drives modern business. The Microsoft Fabric Analytics Engineer Associate (DP-600) certification proves you understand the tools and technologies needed to turn that data into value. This comprehensive guide covers everything you need to know to design and implement enterprise-grade analytics solutions, and ace your certification exam. Drawing on their extensive experience working with Microsoft Fabric and Power BI, Brian Bønk and Valerie Junk take you through preparing and transforming data, securing and managing analytics assets, and building and optimizing semantic models. You'll learn to work with data warehouses and lakehouses, ensuring data is structured and ready for analysis. You'll also discover how to query and analyze data using SQL, KQL, and DAX, which are essential skills for anyone working with Fabric. Whether you're preparing for the exam or just looking to expand your Fabric expertise, this book gives you the foundation to succeed. Prepare and enrich data for analysis. Work with, secure, and maintain analytics assets. Implement, manage, and optimize semantic models. Utilize data warehouses and lakehouses. Handle workspace access control and item-level access control"-- Provided by publisher

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