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


This chapter provided a variety of parsing methods that will help you parse out data in no time. With the Text to Columns tool, you learned about splitting the data from one field into columns or rows. This is a great way to identify segments of the data for analysis. The DateTime tool was a real force in converting date/time formats to string formats, and vice versa converting string formats to date/time formats. This tool is very handy if dates and times need to be cleaned up quickly. If you're looking for more robust parsing, then the RegEx tool is where a variety of regular expressions can be applied and the Match output method was the desired output. The tools and methods applied in this chapter will provide you with a foundation for parsing data with a variety of specifications.

In the next chapter, you will learn about the reporting tools and how to implement them in your workflow to create custom data-driven reports.