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Tableau Prep Cookbook

By : Kleine

4.7 (10)

Tableau Prep Cookbook

4.7 (10)

By: 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.

Preface

Preface

Who this book is for

What this book covers

To get the most out of this book

Download the example code files

Download the color images

Conventions used

Get in touch

Reviews

Chapter 1: Getting Started with Tableau Prep

Chapter 1: Getting Started with Tableau Prep

Technical requirements

Installing Tableau Prep Builder

Checking out the user interface

Using Tableau Prep for ad hoc data analysis

Preparing data for generic BI tools

Preparing data for Tableau Desktop ad hoc analysis

Free Chapter

Chapter 2: Extract and Load Processes

Chapter 2: Extract and Load Processes

Technical requirements

Connecting to text and Excel files

Connecting to PDF files

Connecting to SAS, SPSS, and R files

Connecting to on-premises databases

Connecting to cloud databases

Connecting to Tableau extracts

Connecting to JDBC or ODBC data sources

Writing data to CSV and Hyper files

Writing data to databases

Setting up an incremental refresh

Publishing a flow to Tableau Server

Chapter 3: Cleaning Transformations

Chapter 3: Cleaning Transformations

Technical requirements

Renaming columns

Filtering your dataset

Changing data types

Auto-validating data

Validating data with a custom reference list

Splitting fields with multiple values

Chapter 4: Data Aggregation

Chapter 4: Data Aggregation

Technical requirements

Determining granularity

Aggregating values

Using fixed LOD calculations for grouping data

Grouping data

Chapter 5: Combining Data

Chapter 5: Combining Data

Technical requirements

Combining data with Union

Combining data ingest and Union actions

Combining datasets using an inner join

Combining datasets using a left or right join

Expanding datasets using a full outer join

Expanding datasets using a not inner join

Chapter 6: Pivoting Data

Chapter 6: Pivoting Data

Technical requirements

Pivoting columns to rows

Pivoting columns to rows using wildcards

Pivoting rows to columns

Chapter 7: Creating Powerful Calculations

Chapter 7: Creating Powerful Calculations

Technical requirements

Creating calculated fields

Creating conditional calculations

Extracting substrings

Changing date formats with calculations

Creating relative temporal calculations

Creating regular expressions in calculations

Chapter 8: Data Science in Tableau Prep Builder

Chapter 8: Data Science in Tableau Prep Builder

Technical requirements

Preparing Tableau Prep to work with R

Embedding R code in a Tableau Prep flow

Forecasting time series using R

Preparing Tableau Prep to work with Python

Embedding Python code in a Tableau Prep flow

Chapter 9: Creating Prep Flows in Various Business Scenarios

Chapter 9: Creating Prep Flows in Various Business Scenarios

Technical requirements

Creating a flow for transaction analytics

Creating a call center flow for instant analysis

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Connecting to SAS, SPSS, and R files

In this recipe, we'll connect to a statistical file. Tableau Prep offers fantastic integration with popular statistical files from SAS (.sas7bdat), SPSS (.sav), and R (.rdata, .rda).

I advocate the use of open file formats such as CSV or commonly used standards such as Excel. However, if you are unable to obtain your data in such a format from your data science partner, this connector may offer a solution.

Getting ready

In this recipe, we'll connect to an R file using the statistical file connector. In order to follow along, download the Sample Files 2.3 folder from the book's GitHub repository.

How to do it…

To get started, ensure you have the sample RData file available on your computer. From the Tableau Prep home screen follow these steps:

Click the Connect to Data button and select Statistical file.
From the browse file window, locate and open our statistical file named December 2016 Sales.Rdata.
And with just these few steps, Tableau Prep Builder has added the statistical file source to a new flow:

Figure 2.18 – Flow with a statistical file connection

Figure 2.18 – Flow with a statistical file connection

Most options in the bottom pane are identical to those when processing Excel files. However, there is a small but important feature absent. You cannot alter the data type of the fields in the statistical file connection step. In order to do this, you have to use a cleaning step, which we'll discuss in Chapter 3, Cleaning Transformations:

Figure 2.19 – Data types cannot be altered directly in the statistical file connection step

Figure 2.19 – Data types cannot be altered directly in the statistical file connection step

In this recipe, you have learned how to add Tableau Prep to a data science workflow by connecting to data produced by popular statistics applications.

How it works…

Tableau Prep unpacks statistical files when you connect to them and, from that moment on, allows you to leverage them like any other connection.

There's more…

There are some limitations when it comes to connecting to statistical files. If you run into any connection issues, I recommend you refer to the following section of the Tableau documentation online: https://help.tableau.com/current/pro/desktop/en-us/examples_statfile.htm.

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