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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

Use query parameters

As we discussed in Chapter 3, Data Preparation in Power Query Editor, in the Understanding query parameters section, query parameters are one of the most valuable features of Power Query that can help us in many scenarios. The following sections explain some of them.

Parameterizing connections

It is best to parameterize all data source connections, especially if we have different environments. The parameterized connections become handy when configuring the deployment pipelines.

Restricting the row counts in development for large tables

Sometimes, we deal with large tables with several million rows, which can be time-consuming in development. Imagine a scenario in which we transform the data in Power Query Editor and then load it into the data model. If the table in the source system is large, it takes a long time to load the data into the data model, decreasing our productivity. In most cases, we do not need to load all the data into the data model...

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