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 6: Pivoting Data

You may encounter a scenario where analyzing data is complicated by the way the data is structured. For example, you may prefer to have columns as rows or vice versa. For example, you may have a column in your dataset with a true/false value for each product category. However, your data visualization would be easier to achieve if you had a single column for the product category, with the row value indicating the category name. In this chapter, you'll learn how to pivot your data from columns to rows and vice versa. The goal of pivoting is to ensure your data has the optimal shape required for your downstream analytics goals, for example, creating a dashboard in Tableau Desktop. Mastering the pivot functionality is an essential tool in your data transformation skillset.

In this chapter, you'll find the following recipes to help you pivot your data for analytics:

  • Pivoting columns to rows
  • Pivoting columns to rows using wildcards
  • Pivoting...