Summary

It is important to consider data quality before conducting analysis in Tableau. If data has not been assessed for consistency, accuracy, and completeness, then the insights derived from it cannot be trusted.

There are multiple data types for fields in Tableau, including string, numeric, Boolean, geographic, date, and date and time. Fields behave differently depending on data type but also depending on color. Blue fields are discrete, which means that they essentially consist of a finite number of grouping values. Green fields are continuous, which means there is theoretically an infinite number of values that are possible. Fields can also be either dimensions or measures. Dimensions are used to break up views, whereas measures are used to aggregate metrics.

Tableau Desktop offers a wide range of functionality for cleaning, transforming, and combining data to ensure that it is ready for analysis. Fields can be cleaned by renaming, filtering out unneeded values, setting...