Book Image

Tableau 2019.x Cookbook

By : Dmitry Anoshin, Teodora Matic, Slaven Bogdanovic, Tania Lincoln, Dmitrii Shirokov
Book Image

Tableau 2019.x Cookbook

By: Dmitry Anoshin, Teodora Matic, Slaven Bogdanovic, Tania Lincoln, Dmitrii Shirokov

Overview of this book

Tableau has been one of the most popular business intelligence solutions in recent times, thanks to its powerful and interactive data visualization capabilities. Tableau 2019.x Cookbook is full of useful recipes from industry experts, who will help you master Tableau skills and learn each aspect of Tableau's ecosystem. This book is enriched with features such as Tableau extracts, Tableau advanced calculations, geospatial analysis, and building dashboards. It will guide you with exciting data manipulation, storytelling, advanced filtering, expert visualization, and forecasting techniques using real-world examples. From basic functionalities of Tableau to complex deployment on Linux, you will cover it all. Moreover, you will learn advanced features of Tableau using R, Python, and various APIs. You will learn how to prepare data for analysis using the latest Tableau Prep. In the concluding chapters, you will learn how Tableau fits the modern world of analytics and works with modern data platforms such as Snowflake and Redshift. In addition, you will learn about the best practices of integrating Tableau with ETL using Matillion ETL. By the end of the book, you will be ready to tackle business intelligence challenges using Tableau's features.
Table of Contents (18 chapters)

Introduction

Let's understand this situation better through the following example. In one of our projects, a customer had a Cloud Data Warehouse and uses Matillion to load it. The customer was using Tableau as a primary BI tool.

Let's look at the ideal ELT, which is shown in the following screenshot:

There are two individual processes here. The green one is Matillion, that is scheduled via Matillion Scheduler. The orange one is Tableau and it is scheduled via Tableau Server. Usually, we assume that ETL is done at 6 am and we scheduled Tableau extracts and dashboards a bit later. In our example, it is 7 am. In addition, we are using tabcmd and schedule Tableau Reports via Windows Task Scheduler.

As you might guess, the marketing data source isn't the most reliable. Let's consider a scenario, where SFTP was delayed files delivery.

As a result, the ELT job...