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)

Using Tableau Prep for ad hoc data analysis

In this recipe, you'll learn how to leverage Tableau Prep Builder to perform ad hoc data analysis. In most scenarios, getting insights from your data would involve the creation of a data pipeline and then connecting a data visualization tool to the output of that pipeline to perform your analysis. However, with Tableau Prep Builder, you can perform basic ad hoc analysis on your data from within the tool itself.

Getting ready

Open the Tableau Prep Superstore flow to follow along with the steps outlined.

How to do it…

Ad hoc analysis typically starts with a business question to be answered with the use of your data. Let's assume the question posed for the Superstore data is: Which is the top category of products that consumers order with same-day delivery?

Following these steps, you'll be able to use Tableau Prep to answer this question without the need for additional reporting tools:

  1. In Tableau...