Book Image

Tableau Prep Cookbook

By : Hendrik Kleine
Book Image

Tableau Prep Cookbook

By: Hendrik Kleine

Overview of this book

Tableau Prep is a tool in the Tableau software suite, created specifically to develop data pipelines. This book will describe, in detail, a variety of scenarios that you can apply in your environment for developing, publishing, and maintaining complex Extract, Transform and Load (ETL) data pipelines. The book starts by showing you how to set up Tableau Prep Builder. You’ll learn how to obtain data from various data sources, including files, databases, and Tableau Extracts. Next, the book demonstrates how to perform data cleaning and data aggregation in Tableau Prep Builder. You’ll also gain an understanding of Tableau Prep Builder and how you can leverage it to create data pipelines that prepare your data for downstream analytics processes, including reporting and dashboard creation in Tableau. As part of a Tableau Prep flow, you’ll also explore how to use R and Python to implement data science components inside a data pipeline. In the final chapter, you’ll apply the knowledge you’ve gained to build two use cases from scratch, including a data flow for a retail store to prepare a robust dataset using multiple disparate sources and a data flow for a call center to perform ad hoc data analysis. By the end of this book, you’ll be able to create, run, and publish Tableau Prep flows and implement solutions to common problems in data pipelines.
Table of Contents (11 chapters)

Creating regular expressions in calculations

In this chapter, we've seen how to extract substrings already. In this brief recipe, we're going to explore another method of doing so, using regular expressions. Regular expressions, also referred to as regex, allow you to define a complex search pattern to locate, and in our case extract, substrings. A look at the inner workings of regex is beyond the scope of this book, but a quick web search will reveal numerous sources including example regex statements. In Tableau Prep, you can leverage such statements in a REGEX function.

Getting ready

To follow along with this recipe, download the Sample Files 7.6 folder from this book's GitHub repository. There, you'll find the Missed Chats.csv Excel file. In this file, we find a log of users who have visited our company website and attempted to contact us via live chat when no agent was available to respond. At that point, they submitted their details in a contact form...