The High Cost of Treating a Dirty Data Infection
You notice a few mistakes at first – outdated contact information for someone, irreconcilable reports, a strange customer name that’s infiltrated your favorite database. The Help Desk has a recorded message stating “…technicians are looking into system performance issues, and an update will be posted in one hour.” After stepping through the prompts, you speak to a real person, and politely get brushed off.
The problems may be resolved in an hour, maybe in a day. Or, you may be witnessing the first stage of a dirty data outbreak. Dirty data functions as an infection, and at ComResource, we treat the problem accordingly. If dirty data has infiltrated your environment, you need to deal with it before it gets out of hand.
One of the biggest problems with dirty data is that it looks similar to “good” data. Dirty data appears alongside the clean data that you rely on to make solid business decisions. Just one misplaced character may not seem like a big deal when you are dealing with petabytes of data, but that single character can lead directly to decreased customer satisfaction and lost revenue.
Years of mergers and acquisitions, with their requisite system integrations, help to propagate the risk of infection. As information systems become more complex, the chances of any one person understanding how a data element flows throughout the organization decreases. This means that your chances of identifying the source of the outbreak and vulnerable systems are greatly diminished. Even if the source is identified, can you successfully locate, isolate and remove all signs of the infection? A single piece of isolated dirty data in your systems may not be a problem today, or even tomorrow; while it exists, there is a chance that it will escape isolation, and the infection will begin.
Unless you do something about it, dirty data will lead to all of the problems mentioned above. There are several approaches to prevent dirty data from entering, including tracking down the entry point and shoring up the data rules. You can also ensure that your business applications and data validation routines are water-tight, purposefully excluding the possibility of dirty data entering or being used by any business critical application. Preparing to respond to a dirty data infection is just as important as preventative measures. Ensuring that your response is correctly aligned to the level of infection is critical.