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)

Chapter 9: Creating Prep Flows in Various Business Scenarios

So far in this book, we've learned a wide variety of capabilities offered by Tableau Prep. In this chapter, we're going to cover creating an end-to-end flow in Tableau Prep. Each recipe will allow you to prepare for a realistic business scenario in which you may use Tableau Prep. In the first recipe, we'll build a data flow that prepares transaction data for a chain of stores, for the purpose of downstream analysis. During this process, we'll prepare the data and perform cleanup actions so that the downstream analysis can leverage a comprehensive and clean dataset. In the second recipe, we'll use Tableau Prep to answer questions. That is, we'll transform the data to answer a specific business question. Both of these recipes mimic real-world scenarios that you are likely to encounter, no matter the industry you work in.

In this chapter, we will cover the following recipes:

  • Creating...