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)

Combining data with Union

Data is typically produced by multiple systems and certain systems may produce similar data that needs to be combined vertically. That is, the rows need to be stacked on top of one another. A use case we'll use in this recipe is combining sales data from two different sales systems, in order to get the total sales dataset prepared. This is a typical scenario you may encounter when your organization is operating multiple systems, is migrating from one system to another, is maintaining legacy systems, or is integrating systems from a partner or acquired company. In this recipe, we'll combine multiple datasets using Union.

Getting ready

To follow along with this recipe, download the Sample Files 5.1 folder from this book's GitHub repository.

How to do it…

Start by opening Tableau Prep and perform the following steps:

  1. Connect to the DataExport_NOV_Sales.csv text file in order to create a brand-new flow with a data connection...