Book Image

Power Query Cookbook

By : Andrea Janicijevic
Book Image

Power Query Cookbook

By: Andrea Janicijevic

Overview of this book

Power Query is a data preparation tool that enables data engineers and business users to connect, reshape, enrich, and transform their data to facilitate relevant business insights and analysis. With Power Query's wide range of features, you can perform no-code transformations and complex M code functions at the same time to get the most out of your data. This Power Query book will help you to connect to data sources, achieve intuitive transformations, and get to grips with preparation practices. Starting with a general overview of Power Query and what it can do, the book advances to cover more complex topics such as M code and performance optimization. You'll learn how to extend these capabilities by gradually stepping away from the Power Query GUI and into the M programming language. Additionally, the book also shows you how to use Power Query Online within Power BI Dataflows. By the end of the book, you'll be able to leverage your source data, understand your data better, and enrich it with a full stack of no-code and custom features that you'll learn to design by yourself for your business requirements.
Table of Contents (12 chapters)

Chapter 8: Adding Value to Your Data

You have the chance to connect to your data and create and transform it as you want thanks to a wide range of options explored in the previous chapters. Moreover, Power Query offers the chance to add data and enrich it with additional columns or define some functions to retrieve data. By adding columns, you can define your own customized logic in a few steps and leverage the UI or M code expressions, which represents the language behind the scenes of Power Query. M code expressions can be used to build functions and define input values and programmatically retrieve a defined output in order to simplify the entire transformation process.

In this chapter, you will explore how you can add data as new columns based on a pattern or a logic of existing data enriching it with valuable information and using a set of transformations.

In this chapter, we will cover the following recipes:

  • Adding columns from examples
  • Adding conditional columns...