Tableau can connect to a variety of data sources, like text files, Excel sheets, and relational databases. Unlike Excel or other spreadsheet tools, with Tableau, the underlying data are not modified. Instead, the data are visually represented in charts. However, data are often not optimized for visual analysis, and it takes some careful cleaning and transformation to get them ready.
The underlying dataset is equally, if not more, important than any visualizations built in Tableau. Datasets can be dirty. That is, they may contain missing data, logical anomalies, improperly coded variables, and typos. Although exploring a dataset in Tableau can help uncover data integrity issues, it is a wise first step to clean your data before developing any visualizations in Tableau.
Clean data before even establishing a connection to your dataset in Tableau. The best way to clean data is with a systematic, reproducible process. Excel is a comfortable tool for most people, and it can be a good tool for diagnosing issues, but it is less than favorable when it comes to cleaning data for visualization. Tableau Prep allows you to design – and document – a workflow that optimizes your data for working in Tableau.
Watch this video to learn more: Tableau Prep explained in under 10 minutes!
Tableau Prep Builder is available to those who a) have a free one-year license through the Tableau for Students program, b) have a free one-year license through the Tableau for Teaching program, and c) have been assigned a Creator license with Tableau Online.