Practices > Collecting Data > Clean Data

How to clean up your data?


Whether it's from an external source or your own collection effort, raw data is generally messy. There might empty records, duplication, unidentifiable inputs, and other anomalies that make it hard to understand what the data can tell you.

There are a number of tools that can help to give you perspectives on your data set that make it easier to spot problems.

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You can also learn more about techniques and tips regarding data cleaning:


Relevant tools Tools that can be of use to apply this practice