The Difference Between Data Cleansing & Data Validation

Data cleansing and data validation are both common terms used in data processing. But for those less familiar with the technical side of data management, they can be easy to mix up. 

Today, we'd like to clarify the difference between these terms and explain why both are vital to good data management.

The Similarities

One of the biggest challenges in maintaining a large and often complex database is ensuring accuracy and consistency throughout. Over time, it’s easy - and sometimes even unavoidable - for discrepancies and human error to creep in. Add to that the fact that sometimes old or outdated information is not updated and sooner or later serious problems start to crop up.

The solution to these problems is to have a robust system of self-policing in place. Data cleansing and data validation are the two steps by which this process can take place.

Data Cleansing

In its simplest form data cleansing is the process of going through and cleaning up all the data. How we do this can vary from situation to situation, but the goal is to ensure that inaccurate or poorly formatted data is either corrected or removed from the system.

This process can be done manually with one person examining each item at a time, however there are many ways in which we can speed up the process through automation. 

One common source of user errors is inconsistent date formatting. This issue can happen because of regional differences (MM/DD/YY for the US versus DD/MM/YY for the UK) but it can also be the result of formatting choices on behalf of the user. Some might choose to write the whole year while others will only input the last two digits. Some will use a forward slash as a separator while others may use a full stop.

These are just a handful of the ways in which user input can be inconsistent. The important thing, however, is that it can, for the most part, be fixed with a set of simple rules designed to account for each scenario. For example, any 4 digit year can easily be corrected by simply removing the first two digits.

Data Validation

Data validation is a lot like data cleansing except the focus is more on catching problems rather than correcting them. You can think of data validation as a set of rules the system uses to check if the data has been correctly cleansed. This acts as a gating system to prevent faulty data from being used.

One way to talk about the difference between the two would be to say that data validation is a passive/non-destructive way of flagging problems while cleansing is an active/destructive method for changing the data.

Looking for professional data solutions? Get in touch with us today by calling 01273 202 006 or emailing ​[email protected] to find out more.

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