How to Address Common Data Quality Issues Without Code

Use Tableau to Solve Inconsistent Values

Photo by Markus Spiske on Unsplash

Common Data Quality Issues

Before jumping right into how to solve data quality issues we need to know what are the common issues and how to spot them.

1. Missing value: this is the easiest one to identify, simply look at if there are any null values, maybe apply a filter to make them more obvious.
2. Duplicate value: when several rows of data appear to be the same then most likely they have been mistakenly recorded multiple times.
3. Inconsistent value: the string values of the same attributes do not follow the same naming convention, e.g. both LA and “Los Angeles” are present in the City data field.
4. There are also many data quality issues requires certain domain knowledge to identify, hence it is important to do some research on the industry before investigating, e.g. a record of 121 degrees water temperature is most likely to be wrong.

This article will mainly focus on how to address inconsistent value. There will be more articles coming up to discuss more data quality issues.

Usually, inconsistent values are mitigated using REGEX, however, Tableau Prep Builder provides a more intuitive way to…