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Communicating Data with Tableau by Ben Jones

By Ben Jones

Transcend spreadsheets and tables and layout a knowledge presentation that truly makes an impression. This functional advisor indicates you the way to take advantage of Tableau software program to transform uncooked info into compelling information visualizations that supply perception or permit audience to discover the knowledge for themselves.

Ideal for analysts, engineers, retailers, reporters, and researchers, this publication describes the rules of speaking information and takes you on an in-depth journey of universal visualization equipment. You'll how you can craft articulate and artistic information visualizations with Tableau computing device 8.1 and Tableau Public 8.1.

•Present comparisons of the way a lot and the way many
•Use mixed facts resources to create ratios and rates
•Create charts to depict proportions and percentages
•Visualize measures of suggest, median, and mode
•Lean tips on how to care for version and uncertainty
•Communicate a number of amounts within the related view
•Show how amounts and occasions switch over time
•Use maps to speak positional data
•Build dashboards to mix a number of visualizations

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Extra resources for Communicating Data with Tableau

Sample text

The toolbar In addition to the components just listed, both the Sheet view and the Dashboard view include a toolbar and menu items at the top, by de‐ fault. The toolbar includes the all-important Undo (left arrow) and Redo (right arrow) controls in the upper left, which allow users to step backward and forward in the current session from the time the work‐ book was opened to the most recent step taken. Also included in the toolbar are controls to Save, Connect to Data, Sort, Group, Show La‐ bels, Toggle to Presentation Mode, and change the Fit of the sheets, among a few other icons.

Connecting to Data | 21 Dimensions can be further grouped into strings, dates, and geographic fields (which generate latitude and longitude Measures based on in‐ ternal lookup tables native to Tableau). Measures can be either discrete or continuous (more about this later). To illustrate the difference between the different data types in Tableau, let’s consider a very simple data table: the population and surface area of the boroughs of New York, as shown in Figure 2-4. Figure 2-4. Data table showing population and area in New York boroughs In this simple data set, Tableau interprets each column as a distinct field, and uses the column headers (the values in the first row) as the field names.

While the visualiza‐ tion types are the same, the method to create them in Tableau can be different. A Tale of Two Formats Let’s consider an example of the same data structured two ways. Figure 3-12 shows the raw data for rat sightings as captured by the 311 call center in New York on the lefthand side, and a pivot table of this data set by borough on the righthand side. Figure 3-12. Data at the incident level and aggregate level If your data is at the aggregate level (like the Excel pivot table on the righthand side of Figure 3-12), you will deal with it in Tableau similar to the garbage collection data.

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