Cleaning Data

This section will walk you through the Tableau Desktop and Tableau Prep cleaning functionalities, starting with what is important when assessing data quality. Cleaning in Tableau Desktop will be followed by using the data interpreter, using folders to organize data sources, and finally, cleaning in Tableau Prep.

Cleaning data refers to either removing unwanted data or fixing broken data. This can include processes such as removing duplicates and outliers or fixing incorrect values and formatting. For example, an invoice system may produce a data source with duplicate invoice records in error. For the data source to be usable in Tableau, the duplicate records would have to be removed to ensure that invoices are not double counted, resulting in inflated totals.

Ensuring data is clean before analysis is a key step, as the results of the analysis can only be trusted once the data source is confirmed as accurate and reliable. Every data source is different in terms of...