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

Using Power BI to collect and connect data

There are a number of steps that we need to follow to create a dashboard. The first step is to collect and connect the data we have to the data model so that we can then move on to the next step.

We will use our sales data from different stores based in the UK. The reality is that these files could be online, on a SQL server, or on a website, but you could also have downloaded the files locally, as with this example. The only difference in the steps would be when you get the data. This example shows connecting to a folder, but if your data is somewhere else, you can refer to Chapter 4, Connecting to Various Data Sources Using Get & Transform, to see how to get data from various sources into Power BI Desktop. The files for this example can be found in the GitHub repository.

In the following screenshot, we have the ZIP code of the store, the product that was sold, and how the person paid for the goods, and the last column (column H...