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The Definitive Guide to Power Query (M)

You're reading from   The Definitive Guide to Power Query (M) Mastering complex data transformation with Power Query

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Product type Paperback
Published in Mar 2024
Publisher Packt
ISBN-13 9781835089729
Length 758 pages
Edition 1st Edition
Languages
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Authors (3):
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Greg Deckler Greg Deckler
Author Profile Icon Greg Deckler
Greg Deckler
Melissa de Korte Melissa de Korte
Author Profile Icon Melissa de Korte
Melissa de Korte
Rick de Groot Rick de Groot
Author Profile Icon Rick de Groot
Rick de Groot
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Table of Contents (19) Chapters Close

Preface 1. Introducing M FREE CHAPTER 2. Working with Power Query/M 3. Accessing and Combining Data 4. Understanding Values and Expressions 5. Understanding Data Types 6. Structured Values 7. Conceptualizing M 8. Working with Nested Structures 9. Parameters and Custom Functions 10. Dealing with Dates, Times, and Durations 11. Comparers, Replacers, Combiners, and Splitters 12. Handling Errors and Debugging 13. Iteration and Recursion 14. Troublesome Data Patterns 15. Optimizing Performance 16. Enabling Extensions 17. Other Books You May Enjoy
18. Index

The formula firewall

When working with queries, combining different data sources is common. It’s likely that after some fiddling you run into an error that prevents you from combining your data. This error is the result of the formula firewall that Power Query has, also known as the data privacy firewall. So, what exactly is the formula firewall, and how can you work with it?

What is the formula firewall?

The formula firewall is a Power Query feature that prevents accidental data transfer between sources. This feature is particularly important when dealing with sensitive information. It was designed because of query folding. Query folding allows Power Query to convert data transformations into a data source query that a data source can execute directly.

Imagine a situation where you’re working with two queries in Power Query. Query1 holds sensitive information, like social security numbers. Using an inner join, you aim to use this data to extract relevant...

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