Tableau Free Tutorial
Introduction to Tableau Tableau Desktop is a data visualization application that lets you analyze virtually any type of structured data and produce highly interactive, beautiful graphs, dashboards, and reports in just minutes. After a quick installation, you can connect to virtually any data source from spreadsheets to data warehouses and display information in multiple graphic perspectives. Designed to be easy to use, you’ll be working faster than ever before.
Tableau Architecture Tableau has a highly scalable, n-tier client-server architecture that serves mobile clients, web clients and desktop-installed software. Tableau Desktop is the authoring and publishing tool that is used to create shared views on Tableau Server
Tableau Server Components The following are the components of Tableau Server Application Server: Application Server processes (wgserver.exe) handle browsing and permissions for the Tableau Server web and mobile interfaces. When a user opens a view in a client device, that user starts a session on Tableau Server. This means that an Application Server thread starts and checks the permissions for that user and that view VizQL Server: Once a view is opened, the client sends a request to the VizQL process (vizqlserver.exe). The VizQL process then sends queries directly to the data source, returning a result set that is rendered as images and presented to the user. Each VizQL Server has its own cache that can be shared across multiple users. Data Server: The Tableau Data Server lets you centrally manage and store Tableau data sources. It also maintains metadata from Tableau Desktop, such as calculations, definitions, and groups.
Tableau Environment Opening and Closing the Application The first thing to understand is how to open and close the application. Open Tableau There are many ways to open Tableau from your desktop computer. Open the application by doing one of the following: Double-click the Tableau icon on your desktop. Select Start > All Programs > Tableau. Double-click a Tableau workbook or bookmark file. Tableau files are typically stored in the My Tableau Repository folder of your My Documents folder. Close Tableau When you are done working in Tableau you should save your work and close the application. Close the application by doing one of the following: • Click the Close icon located in the right corner of the application title bar. Select File > Exit. If your workbook has not been saved, you will be asked whether you want to save it.
Tableau Workspace The Tableau workspace consists of menus, a toolbar, the Data window, cards that contain shelves and legends, and one or more sheets. Sheets can be worksheets or dashboards.
Worksheets contain shelves, which are where you drag data fields to build views. You can change the default layout of the shelves and cards to suit your needs, including resizing, moving, and hiding them. Dashboards contain views, legends, and quick filters. When you first create a dashboard, the Dashboard is empty and all of the worksheets in the workbook are shown in the Dashboard window.
Data Blending Data blending is when you blend data from multiple data sources on a single worksheet. The data is joined on common dimensions. Data Blending does not create row level joins and is not a way to add new dimensions or rows to your data. Data blending should be used when you have related data in multiple data sources that you want to analyze together in a single view. To integrate data, you must first add one of the common dimensions from the primary data source to the view.
For example, when blending Actual and Target sales data, the two data sources may have a Date field in common. The Date field must be used on the sheet. Then when you switch to the secondary data source in the Data window, Tableau automatically links fields that have the same name. If they don’t have the same name, you can define a custom relationship that creates the correct mapping between fields.
Joining Tables Many relational data sources are made up of a collection of tables that are related by specific fields. For example, a data source for a publisher may have a table for authors that contains the first name, last name, phone number, etc. of clients. In addition, there may be another table for titles that contains the price, royalty, and title of published books. In order to analyze these two tables together, to answer questions like, how much was paid in royalties last year for a particular author, you would join the two tables using a common field such as Author ID. That way you can view and use the fields from both tables in your analysis.
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