Whenever there is data involved, data validation can’t be too far away. That much everyone knows, at least the ones involved in the ecosystem. You may be just gathering data, analyzing it, or processing it to glean insights from the said data; you will need to deal with data validation. But what its data validation exactly? Well, it refers to the process of verifying two key things: the quality and reliability of data. It ensures that though it is indeed complete, consistent, and not duplicated, it is done right before you import data and process it. Now that we know what it is let’s see why we need data validation.
Even though it is often ignored, data validation is what allows companies to make sure that they achieve the ideal result. Consider this: If the data you intend to use isn’t without error right from the start, the result of whatever you plan to do with it won’t be error-free either.
As you can see, data validation serves a purpose and a crucial one at that. So, why is it that people continue to look it over? It can be credited to a variety of challenges, including the pace of the process. Some files are convinced that data validation is a time-consuming job that will slow down other operations across the business. But given that now the market offers a plethora of solutions to accelerate that, this isn’t a problem anymore. Now let’s take a look at some of the other challenges in this regard.
- Distributed databases: As mentioned above, data validation, though crucial, is subject to myriad challenges. And perhaps the biggest one of them all comes to the fore when one is dealing with data distributed across several databases. Now, you need all your data in one place so you can start working with it, and with data residing in different databases can pose a problem to that plan. Furthermore, distributed data then runs the risk of being siloed and perhaps even obsolete.
- Data formats: There is no doubt about the fact that data validation can take much time, often to the frustration of myriad stakeholders involved in the process. The problem is further compounded when one is dealing with a particularly extensive database and you intend to undertake a manual validation process. But this particular challenge can be effectively dealt with by sampling data for validation. Doing this allows one to significantly cut down the time they will need to validate all the data at hand.
There is no denying that data validation is a demanding process — it requires time as well as many decisions to be made. And then there are challenges too. But with the right data validation platforms, especially the ones that seem to suit your business’ requirements, all these challenges can be tended to quickly and effectively. And if you find yourself needing assistance, say with the integration of data using Talend, you can always engage the services of a trusted service provider, who will also be able to help you with the rest of your data validation process.