Weeding Out Bad Data in a Business Process

Michael Vizard

There are really two types of business users. There are the people who get a report and just implicitly believe everything the report says because it came from a computer. Then there are the people who don't trust any of the data because they know how much of an issue data quality can be inside any business process.

Both approaches represent a black eye for IT. The first scenario is more troubling because it shows there are a lot of people making critical business decisions based on bad data. The latter scenario, meanwhile, raises crucial questions about the value of IT if too many people feel the need to check the data by hand using spreadsheets and paper.

Few people want to talk about this because nobody really has had a fix for the problem. Sure, we can invest in data quality and master data management tools to clean up the data. But once bad data is inserted into a business process, it tend to corrupt everything in that process as it continues to be replicated through sometimes hundreds of applications.

This issue is what makes a new InfoSphere Business Information Monitor project from IBM intriguing. The basic idea is to monitor specific business processes in real time and flag all suspect data. That data can then be investigated and any process or application that relies on that data can be alerted about the potential quality of that information.

Michael Curry, IBM Information Integration program manager, says IBM is releasing this technology as a "preview" to select customers. But it's also clear that with the acquisition of MDM players such as Initiate Systems by IBM and Siperian by Informatica, we're going to see a lot more sophisticated approaches to data governance that could alarm more people on one hand by shaking their confidence in the data, while at the same time pacifying others who already know how bad the problem really is.

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