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

Turning data with the unpivot and pivot tools

Transforming data means to shape data by renaming tables or columns or making the data presentable for analysis. You will master the use of the Pivot and Unpivot tools to transform tabular data into an accepted tabular format. After using these tools, we will delete any unnecessary columns and rename column headers, and name queries. We will take note of the applied steps and learn how to refresh data sources in Power Query. These steps are all necessary to get the data prepared for further analysis or reporting.

Data is presented in many forms for many different reasons. Some could be made visually appealing, such as a simple financial budget report with financial years as rows and months as column headers, while others could be more complex and used for analysis using PivotTables and/or storing data in a data storage application such as Power BI. Always envisage the aim of the dataset you are working with and prepare the data prior...