Data properties

1. Data properties

Welcome back! I'm Sara and I will be your instructor for this chapter where you'll get to know more about managing your data and the different data connections available in Tableau. It's important to set yourself up for a smooth analysis. Preparing and managing your data will ensure your data can be rightly interpreted by Tableau and the end users of your dashboard.

2. Managing data

Usually, Tableau does a pretty good job of figuring out which fields go where and how they can be used in your data visualizations. Sometimes, however, you might want to correct mistakes or add additional information that will make Tableau even more effective. There are a number of things you can do to achieve this. You can change a field from a dimension to a measure or the other way around. You can change column names and aliases or data types. Finally, you can also change the default properties of a field to save time. Let's take a closer look.

3. Dimension vs. measures

When you connect to a new data source, Tableau assigns each field in the data source as dimension or measure. Dimensions contain qualitative values, like names, dates, or geographical data. Measures contain numeric, quantitative values, like price, duration, or age. Usually Tableau gets it right, but not always. A common example of a column that might need an adjustment would be a numeric value that is an ID. Tableau automatically places columns containing only numeric values in the Measure section. However, if the column contains ID's or Serial Numbers, aggregating them would be meaningless and the field should be moved to the dimensions section instead.

4. Column names and aliases

Communication of the data's value begins with its columns names. In Tableau, you can update column names without writing back to the source data files. On top of renaming columns, you can also alias values within the column to make sure the value names are more meaningful for analysis.

5. Data types

Data types characterize the data values. There are seven data types in Tableau; string, number, date, date and time, boolean, geographic, and cluster or mixed values.

6. Data types

Once a dataset gets uploaded in Tableau, the underlying data fields are shown in the Data Source page. Usually, Tableau gets them right but sometimes you'll need to make changes.

7. Data types

As you can see in the example, Tableau identified Country and City as geographic fields. Tableau can recognize a variety of Geographic roles going from country and city to zip code and state. The software will automatically assign coordinates to those places. Frequently, column names have application-specific titles that don't conform to common titles for location description. For example, the software you export your data from could use the term region to describe the country column. In these cases Tableau won't be able to recognize the field as a geographic field, meaning you'll have to change the column name and manually assign the geographic role. More on that later.

8. Default properties

Assigning Default Properties to newly calculated fields or to source data allows the analyst to have the characteristics consistently shown each time the value is brought onto the canvas. You have different options under the Default Properties menu. You can change the default aggregation, comments, number formatting, color, shape, and totals. A common example is to format Sales and Profit values to consistently show as currency with no decimal places.

9. Let's practice!

Time for some practice!

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