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)

Auto-validating data

Data validation can be a time-consuming task where we have to determine whether a value is accurate or not. One of the most typical data validation issues relates to misspelling and labeling the same thing differently. For example, the city of New York might be present in your data more than once, with different labels:

  • New York
  • NY
  • NYC
  • New York, NY
  • New York, New York
  • New York, US
  • And so on…

To make the process of validating data easier, Tableau Prep uses data roles. A data role compares your data against a list of known values or specific patterns. This allows us to quickly identify problematic values in our data and take action to resolve them.

Getting ready

To follow along with this recipe, download the Sample Files 3.4 folder from this book's GitHub repository.

How to do it…

Open up Tableau Prep and connect to the User List.csv file from the Sample Files 3.4 folder and follow the steps: