Data validation is arguably an essential aspect of operating an SQL server successfully, especially if you are aiming to migrate, modify, transform or manipulate data in any way and you want to preserve its validity.
That is not to say that this process is without its issues. To help you work out when and in what context you should embrace data validation, here is a look at the perks and problems involved.
Accuracy & Error Detection
For a database to be effective, the information it contains must necessarily be accurate, consistent and free from errors. Data validation does not directly guarantee accuracy, but when mission-critical apps are on the line it is important to be able to extract and transform data from different sources while preserving the correct format, while also having the ability to highlight errors that arise.
This can be achieved as part of the broader use of SQL server integration services, which are outlined comprehensively in the SentryOne guide to SSIS. Without the use of data validation, you will have now way of knowing whether the information available to you has been handled correctly, let alone whether or not it is accurate.
Resource Requirements
The main obstacle that data validation throws in the path of anyone looking to operate an SQL server efficiently is that this process invariably monopolizes hardware resources.
Thankfully there are ways to overcome certain constraints imposed in this context, whether by tweaking the code to make it as streamlined as possible or simply scheduling the validation in such a way that it does not conflict with any peak periods of database use to help minimize its impact on performance.
Feedback Potential
While in ideal circumstances you will be able to execute a data validation operation and return no errors whatsoever, this is not realistic in most cases.
Of course when errors are pinpointed, this is actually an advantage since it gives you evidence that you can then relay to administrators so that data can be imported with fewer hold-ups in the future.
Being able to base your decisions on tangible, precise error reports will be far better than relying on intuition and guesswork. If the industry you occupy requires the utmost in terms of data validity and accuracy, this will be all the more important as an advantage.
Manual Manipulation
In the vast majority of scenarios, it will make sense to implement data validation in the normal course of running an SQL server, but like many aspects of administering to such a system there are some quirks and complications involved.
As hinted at above, the standard tools provided by SSIS may not be adequate to allow you to achieve your goals. Even with the rise of machine learning and other impressive implementations of automation in this sphere, it is sometimes necessary to get your hands dirty and make manual ameliorations.
Ultimately you may already be aware of the perks that data validation affords in an SQL database, so you simply need to be prepared to accept the comparatively minor pitfalls that are also associated with it.