Data visualization can transform large amounts of business-generated raw data into useful and actionable information nuggets for decision makers.
Many businesses use data visualization and analysis applications to transform large amounts of generated raw data into useful and actionable information nuggets for decision makers. One of the more popular applications in this genre is produced by Tableau Software.
Whether your data is stored in a simple text file, Excel worksheet, or large database, Tableau Software can read it, process it, and then present it in an informative manner which can be read and understood by practically anyone through data visualization. The transformation is relatively intuitive, but the application of certain tips and tricks will make the process smoother.
This how-to tutorial shows you how to connect data to Tableau Software and then transform that data into a simple data visualization with a few mouse clicks.
SEE: Tableau business analytics: Tips and tricks (free PDF) (TechRepublic)
Create your first Tableau Software chart
Modern businesses generate reams and reams of potentially enlightening raw data every day, every week, every month, and every year. That data can exist in many formats, including simple text files, Excel worksheets, and databases. For this example, we will use the public version of the Tableau desktop application to connect to an Excel file. The public version is limited in scope, but otherwise the same as the paid version.
After downloading and installing the Tableau Software desktop application, you should find a new shortcut on your desktop. In Windows 10, you double-click that icon to start the app. You should see something like the screen shown in Figure A.
The first step for any project is to establish a connection to a data source. Click on the Microsoft Excel link listed on the left-hand navigation bar of the Tableau app. You will be presented with a File Explorer dialog box that will allow you to navigate to the folder where your data resides. Click the appropriate file, in our example it includes data on mortality rates by country between 1970 and 2010. Tableau will preview the data as shown in Figure B.
If the data is inconsistent or otherwise "dirty," the built-in data interpreter may help clean it up for better data visualizations.
To start your new chart project, click the Sheet 1 tab at the bottom of the Tableau screen to reveal the visualization creation screen shown in Figure C.
The Tableau app has performed some interpretation of your data to develop a list of Dimensions and Measures. These various pieces are what you will use to create a data visualization.
How you present your data visualization is a function of what your data represents. For example, from the sample data, we could drag the Year data point to the Column box and the Death Rate data point to the Row box, as shown in Figure D. This gives us a simple line graph showing the rate over time, but there is a more effective way to view this data.
What if we take advantage of Tableau's ability to automatically parse data into better formats? If we double-click the Country Name dimension, which is defined as a geographical data point, the software will automatically create a world map, as shown in Figure E. If we then double-click the Death per 100,000 measure, which is defined as a number data point, we will get a much better and more relatable visualization of our data.
To get a good view of your new chart, click the Presentation Mode icon on action bar or just press the F7 function key. All the data construction cards will fall away, and you will be left with a clear view of your data visualization (Figure F).
Press F7 again to return to the data visualization construction worksheet again.
This merely touches the surface of the data visualization possibilities. For example, the next step in our example data visualization would be to add the ability to step through each year of data (1970 – 2010) on our map instead of just showing the total for all 40 years.
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