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 relative temporal calculations

There are many analytics scenarios where you may want to calculate a date-related field based on a relative date, such as today or this year. Such calculations can make your Tableau Prep flow more dynamic and each time the flow is run, Tableau Prep will evaluate the data against the current date or time period. In this recipe, we'll perform a calculation using today's date as a relative anchor. That is, if you execute the flow on July 4, our calculation will use July 4 as a relative point in time. If you execute the same flow the next day, Tableau Prep will automatically adjust to July 5. In this recipe, we'll calculate the age of support tickets for a company's helpdesk, relative to today, that is, how long a support ticket has been open.

Getting ready

To follow along with this recipe, download the Sample Files 7.5 folder from this book's GitHub repository. There, you'll find the Support Requests Extract.csv...