Tableau:Creating Interactive Data Visualizations
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Preface

With increasing interest for data visualization across the media, businesses are looking to design constructive dashboards that captivate the interest as well as liaise data. Tableau makes data available to everyone, and is a great way of dispensing enterprise dashboards across the business. Tableau is an extensive toolkit that lets you create high quality data visualizations effectively.

What this learning path covers

Module 1, Tableau Dashboard, introduces you to the theory and practice of delivering dashboards using Tableau through a step-by-step process of creating the building blocks of a dashboard. We then proceed towards the designing principles of putting the dashboard items together. You will learn how to summarize data as a way of conveying key messages on your dashboard along with the introduction to calculations. This module will facilitate structured investigation of data using guided analysis in Tableau. We will also focus on the graphical presentation of data using sparklines, KPIs, maps, and so on. Towards the end of the module, we will look at theming and adding more details to the dashboard by providing examples of more advanced features of Tableau.

Module 2, Data Visualization with Tableau, acquaints you with Tableau's user interface and creates perspicacious visualizations. In this module we start off by connecting various data sources, including text, Excel, as well as data sources on a Server. We move on further to create univariate, bivariate, and multivariate charts. This module will also help you create maps by setting geographic variables, placing markers, and overlaying demographic data. We will create new fields using predefined functions, calculate percentages, apply the if-then logic, discretize and aggregate data, manipulate text, and so on. You will be able to modify visualizations by adding information, changing the default marker size and shape settings. Finally, we not only learn to export images and data from the workbook and share them on the Web, but we also explore some of the advanced features of Tableau, such as customizing marker shapes, adding various selectors, and creating animated visualizations.

Module 3, Creating data stories with Tableau Public, provides guidelines on how to pursue an enthralling, rich story with data that will enlighten others. By the end of this module, we will create an ideal example of a dashboard that focuses on an issue that impacts everyone. We begin with an overview of the functions of Tableau Public along with its installation. Furthermore, you will be familiarized with various features in Tableau Public, such as cards, shelves, and ShowMe. This module will teach you how to format source data and explain some basic data modeling, such as Dimensions, Measures, and Joins. Topics such as Visualization, Calculation and Dashboard designing, which are studied in the previous modules, will be covered in detail. Finally, the module will explain how to build filters with their use in dashboards and familiarize you with the various methods to embed data visualization in blog posts, websites, and offline documents

What you need for this learning path

You need the following in order to work with Tableau:

  • Tableau Version 8.2
  • Windows Live login ID and password
  • Microsoft Excel
  • Internet access

Users only need to download the Tableau Public client. The technical specifications for Tableau Public mirror those of Tableau Desktop Personal and are listed on the Tableau website at http://www.tableau.com/products/desktop. According to Tableau system requirements, PC users require the following minimum specifications:

  • Microsoft Windows Vista SP2 or newer (32-bit and 64-bit)
  • Microsoft Server 2008 R2 or newer (32-bit and 64-bit)
  • Intel Pentium 4 or AMD Opteron processor or newer (SSE2 or newer required)
  • 2 GB memory
  • 750 megabytes minimum free disk space

Who this learning path is for

Data scientists who have just started using Tableau and want to build on the skills using practical examples. Familiarity with previous versions of Tableau will be helpful, but not necessary.

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