Book Image

Learning Alteryx

By : Renato Baruti
Book Image

Learning Alteryx

By: Renato Baruti

Overview of this book

Alteryx, as a leading data blending and advanced data analytics platform, has taken self-service data analytics to the next level. Companies worldwide often find themselves struggling to prepare and blend massive datasets that are time-consuming for analysts. Alteryx solves these problems with a repeatable workflow designed to quickly clean, prepare, blend, and join your data in a seamless manner. This book will set you on a self-service data analytics journey that will help you create efficient workflows using Alteryx, without any coding involved. It will empower you and your organization to take well-informed decisions with the help of deeper business insights from the data.Starting with the fundamentals of using Alteryx such as data preparation and blending, you will delve into the more advanced concepts such as performing predictive analytics. You will also learn how to use Alteryx’s features to share the insights gained with the relevant decision makers. To ensure consistency, we will be using data from the Healthcare domain throughout this book. The knowledge you gain from this book will guide you to solve real-life problems related to Business Intelligence confidently. Whether you are a novice with Alteryx or an experienced data analyst keen to explore Alteryx’s self-service analytics features, this book will be the perfect companion for you.
Table of Contents (17 chapters)
Title Page
About the Author
About the Reviewer
Customer Feedback

Text to columns

Text to columns is a great way to split data apart based on delimiters. This parsing technique will split data into columns or rows based on specified delimiters. You may have used text to columns before in legacy platforms, such as Excel, where the data is split on specified delimiters into multiple columns. This is similar to Alteryx and it is all located in one tool called Text to Columns. Who would have thought? The Text to Columns tool splits the text from one field into separate columns or rows. There are advanced options that can ignore certain delimiters or skip empty fields. We'll explore a few examples on how simple, yet powerful the Text to Columns tool is.

In this section, we will use the U.S. Chronic Disease Indicators.csv file to build out the workflow, along with the resources located in the data folder. Let's go through a few helpful examples using the Text to Columns tool.

Text to Columns Example #1: Split the field, QuestionID into two columns using the underscore...