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Tableau 2019.x Cookbook

Tableau 2019.x Cookbook

By : Dmitry Anoshin, Rintaro Sugimura, Matic, Bogdanovic, Lincoln, Shirokov
3.4 (5)
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Tableau 2019.x Cookbook

Tableau 2019.x Cookbook

3.4 (5)
By: Dmitry Anoshin, Rintaro Sugimura, Matic, Bogdanovic, Lincoln, 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)
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Introduction

By now, you have learned how to create individual tables and charts from your data. In this chapter, we will learn how to bring them all together in a dashboard. Dashboards are a powerful way to present visualizations that come from multiple worksheets, and even multiple data sources, in one view. We will learn how to create a dashboard, customize its visual style and layout, and implement advanced functionalities, such as actions and parameter filters. After completing the recipes in this chapter, we will be well equipped to start creating our own dashboards.

We will be using two datasets that describe the results of a consumer survey, on internet use in Serbia, and we will view the satisfaction of users with various aspects of service from various internet providers. The Internet_satisfaction.csv dataset contains only internet users, and holds information on the...

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