For a small company, building a business database requires a lot of effort over a long period of time, using whatever means might be available. It is no wonder that the end result tends to be messy and less then perfectly accurate, as this compilation of bits and pieces can be difficult to manage in practice. In the final instance, you are stuck with an imperfect tool despite all the hard work that you invested, and that’s just unfair. Many business owners don’t even bother updating their databases, knowing them to be too unreliable to use for a marketing drive or another useful purpose.
We can make your databases neat and clean.
No company is too small to benefit from a professional data cleansing service. It may be a little counterintuitive, but sometimes getting rid of bad data is all you need to do in order to streamline your business and give your sales people a shot in the arm. By eliminating redundant, poorly formatted, obsolete or downright inaccurate bits of input, you can derive a lot of value and make the use of analytics more convenient as well as more impactful.
It is paramount that this process is conducted professionally and with a good understanding of the underlying business processes. Data cleansing should be viewed as a smart way to improve the quality of insights rather than a purely technical task. The whole point is to ensure consistency across different columns and fields without any loss of useful information, allowing front-line employees to start trusting the accumulated data once again.
Why using Prestanda to clean up your data makes a lot of sense
Technology can make all tasks easier, and Prestanda’s team has a tested method for performing data cleansing services for small and medium companies. Our approach involves careful examination of the data and rigorous cross-referencing to eliminate any duplicate, obsolete, or damaged information from the database, leaving nuggets of pure insight to be discovered on the surface. All you need to do is set up the definition of what each column should contain, and we can do everything else. Our process includes human oversight, which means we can find even those duplicates that a purely automated software module couldn’t. In addition to improving the quality of information, we also try to make the entire data system more usable and user-friendly.