Data validation is beneficial as it certifies the functionality of your data


Data validation is beneficial because it certifies the functionality of your data. There are many instances of situations where a lack of data validation reduces the helpfulness of the database.

Imagine a web-shop database that would permit you to enter a new customer without an address. You would be powerless to ship goods to such a customer.

Imagine that the same web-shop database stores the country of residence of its consumers. If the database doesn't impose a certain input pattern on this data you will end up different with values for the same country, like USA, US, United States and the United States of America. This makes it unfeasible, or at least much difficult to remove information like how much consumers from the United States have used your web-shop, and how many from India.

And what would happen if your database didn't detect the minimum length of a phone number? You might end up with a lot of people you can't approach.

These instances are all about actual data, but the database can validate more than just data. They can also validate associations. A database can, for instance, protect a user or program from entering a new order in the Orders table if it is not related (by a key) to an existing consumer from the Customers table. Because, where would you send the order if it wasn't linked to an existing customer?

As you can see from these instances, data validation is of great significance to a user database.

How will you certify the validity and accuracy of data?

To certify the validity and accuracy of data, market researchers can portray the same surveys to different respondents in the same sample area. Using a broader sample area will also provide a true picture of the outcome.


BDS Services offers professional data validation services to its customers in various industries. The validation is usually done on the complete record or database for given fields; we provide consumers the pliability of choosing particular fields for data validation based upon their priorities.

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