Book Image

Learn Power Query

By : Linda Foulkes, Warren Sparrow
Book Image

Learn Power Query

By: Linda Foulkes, Warren Sparrow

Overview of this book

<p>Power Query is a data connection technology that allows you to connect, combine, and refine data from multiple sources to meet your business analysis requirements. With this Power Query book, you’ll be empowered to work with a variety of data sources to create interactive reports and dashboards using Excel and Power BI. </p><p>You’ll start by learning how to access Power Query across different versions of Excel and install the Power BI engine. After you've explored Power Pivot, you’ll see why Excel users find it challenging to clean data in Power Pivot and learn how Power Query can help to tackle the problem. The book will show you how to transform data using the Query Editor and write functions in Power Query. A dedicated section will focus on functions such as IF, Index, and Modulo, and creating parameters to alter query paths in a table. You’ll also work with dashboards, get to grips with multi-dimensional reporting, and create automated reports. As you advance, you'll cover the M formula language in Power Query, delve into the basic M syntax, and write the M query language with the help of examples such as loading all library functions offline in Excel and Power BI. Finally, the book will demonstrate the difference between M and DAX and show how results are produced in M. </p><p>By the end of this book, you’ll be ready to create impressive dashboards and multi-dimensional reports in Power Query and turn data into valuable insights.</p>
Table of Contents (17 chapters)
Free Chapter
1
Section 1: Overview of Power Pivot and Power Query
6
Section 2: Power Query Data Transformations
11
Section 3: Learning M

Summary

We started this chapter by following some steps. The first step was to retrieve data before we edited it created the applied steps. We then imported a table so that we could build relationships between the tables. We created calculated columns and measures before creating our interactive dashboard. After publishing the content, we then shared our dashboards and datasets in a variety of different ways. Although this might look like it is very complicated, the reality is that if you follow these steps, it is a little time-consuming but a relatively simple process.

In this chapter, we connected data, and although we connected data from a folder, we could have used the same process to connect data from the web, a portal, or a SQL server as well. We used transform tools to make sure that only specific file formats were included, as well as making sure that extensions would always be in lowercase as Power BI is case sensitive. We created a relationship between different tables...