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The Definitive Guide to Power Query (M)

The Definitive Guide to Power Query (M)

By : Greg Deckler, Rick de Groot, Melissa de Korte
4.8 (39)
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The Definitive Guide to Power Query (M)

The Definitive Guide to Power Query (M)

4.8 (39)
By: Greg Deckler, Rick de Groot, Melissa de Korte

Overview of this book

Data transformation is a critical step in building data models and business intelligence reports. Power Query is an invaluable tool for anyone who wants to master data transformation, and this book will equip you with the knowledge and skills to make the most of it. The Definitive Guide to Power Query (M) will help you build a solid foundation in the Power Query M language. As you progress through the chapters, you'll learn how to use that knowledge to implement advanced concepts and data transformations. This will set the stage for an uncompromisingly thorough exploration of the Power Query M Language. You'll also get to grips with optimizing performance, handling errors, and implementing efficient data processing techniques. As this is a hands-on guide, the practical examples in the chapters will help you gain the skills to apply Power Query to real-world problems and improve your data analysis capabilities. By the end of this book, you will be able to leverage all of Power Query's remarkable capabilities for data transformation.
Table of Contents (19 chapters)
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17
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18
Index

Working with Nested Structures

Nested structures are very common and refer to the hierarchical organization of data, where a table, record, or list is contained within another. This provides an efficient way to organize relationships and hierarchies and store arrays of values. Common data sources supporting nested structures include relational databases, JSON, and XML. In addition, there is a wide range of M functions that yield structured values. Getting a good grasp on how to handle these structures is crucial; it unlocks a wealth of possibilities.

This chapter covers common functions for working with nested structures in the Power Query M language. These functions allow you to extract specific elements from nested tables, lists, and records, filter and transform nested data, and create new structures based on existing ones. It aims to equip you with the necessary knowledge to apply these transformations in your own workflows. The main topics covered in this chapter are:

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