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Authorized users
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Can lend chapters, not whole ebooks
Title
Pro DAX and data modeling in Power BI : creating the perfect semantic layer to drive your dashboard analytics / Adam Aspin.
Edition
[First edition].
ISBN
9781484289952 (electronic bk.)
1484289951 (electronic bk.)
9781484289945
1484289943
Published
New York, NY : Apress, [2022]
Language
English
Description
1 online resource (xxiii, 465 pages) : illustrations
Item Number
10.1007/978-1-4842-8995-2 doi
Call Number
HD30.213
Dewey Decimal Classification
658.4/038011
Summary
Develop powerful data models that bind data from disparate sources into a coherent whole. Then extend your data models using DAX-the query language that underpins Power BI-to create reusable measures to deliver finely-crafted custom calculations in your dashboards. This book starts off teaching you how to define and enhance the core structures of your data model to make it a true semantic layer that transforms complex data into familiar business terms. You'll learn how to create calculated columns to solve basic analytical challenges. Then you'll move up to mastering DAX measures to finely slice and dice your data. The book also shows how to handle temporal analysis in Power BI using a Date dimension. You will see how DAX Time Intelligence functions can simplify your analysis of data over time. Finally, the book shows how to extend DAX to filter and calculate datasets and develop DAX table functions and variables to handle complex queries.
Note
Includes index.
Access Note
Access limited to authorized users.
Available in Other Form
Print version: 9781484289945
1. Using Power BI Desktop to Create a Data Model
2. Extending The Data Model
3. The Semantic Layer
4. Calculated Columns
5. Calculating Across Tables
6. DAX Logical Functions
7. Date and Time Calculations in Columns
8. Introduction to Measures
9. Filtering Measures
10. CALCULATE() Modifiers
11. The Filter() Function
12. Iterators
13. Creating and Applying a Date Dimension
14. Time Intelligence
15. DAX Variables
16. Table Functions
17. Extending the Data Model
18. Evaluation Context
Appendix A: Sample Data.
