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

Chapter 3. Data Preparation and Blending

The processes of data preparation, blending, and joining are the most powerful capabilities of Alteryx. Data analysts have found themselves struggling to get the best results from their data using Microsoft Excel or other legacy tools. With Alteryx, you’ll embark on a journey of self-service data analytics, and build quick and reliable datasets for business decision-making. In this chapter, you will prep and cleanse data from spreadsheets, cloud applications, and other sources. This will be the foundation for an analytic dataset.

The journey will continue in this chapter; you'll tailor data to your needs by filtering and combining data with other sources and joining them together. This chapter will cover the following topics:

  • Data preparation
  • Data cleansing
  • Filtering
  • Join and union