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Expert Data Modeling with Power BI, Second Edition

You're reading from   Expert Data Modeling with Power BI, Second Edition Enrich and optimize your data models to get the best out of Power BI for reporting and business needs

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Product type Paperback
Published in Apr 2023
Publisher Packt
ISBN-13 9781803246246
Length 698 pages
Edition 2nd Edition
Languages
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Author (1):
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Soheil Bakhshi Soheil Bakhshi
Author Profile Icon Soheil Bakhshi
Soheil Bakhshi
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Toc

Table of Contents (22) Chapters Close

Preface 1. Section I: Data Modeling in Power BI
2. Introduction to Data Modeling in Power BI FREE CHAPTER 3. Data Analysis eXpressions and Data Modeling 4. Section II: Data Preparation in Query Editor
5. Data Preparation in Power Query Editor 6. Getting Data from Various Sources 7. Common Data Preparation Steps 8. Star Schema Preparation in Power Query Editor 9. Data Preparation Common Best Practices 10. Section III: Data Modeling
11. Data Modeling Components 12. Star Schema and Data Modeling Common Best Practices 13. Section IV: Advanced Data Modeling
14. Advanced Data Modeling Techniques 15. Row-Level and Object-Level Security 16. Dealing with More Advanced Data Warehousing Concepts in Power BI 17. Introduction to Dataflows 18. DirectQuery Connections to Power BI Datasets and Analysis Services in Composite Models 19. New Options, Features, and DAX Functions 20. Other Books You May Enjoy
21. Index

Duplicating and referencing queries

Duplicating and referencing queries are somehow similar. We duplicate a query when we need to have all the transformation steps we already took on the original query. At the same time, we want to change those steps or add more transformation steps. In that case, we must change the original query’s nature, translating it so that it has a different meaning from a business point of view. But when we reference a query, we are referencing the final results of the query. Therefore, we do not get the transformation steps in the new query (the referencing query). Referencing a query is a common way to break down the transformation activities. This is the preferred way of preparing the data for most Extract, Transformation, and Load (ETL) experts and data warehousing professionals. In that sense, we can do the following:

  • We have base queries connected to the source system that resembles the Extract part of the ETL process.
  • We reference...
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