It’s little surprise that IT managers find their Business Intelligence and related enterprise applications under the corporate microscope these days. Corporate executives and their comptrollers who advise on making correct purchase decisions are increasingly demanding solid ROI figures on all big-ticket IT investments, forcing enterprise-wide applications front and center.

Fortunately, productivity gains for most IT solutions have been fairly well documented in recent years. But the drumbeat of quarterly reporting continually fuels the search for more and deeper levels of ROI.

One approach to increasing ROI has been through data quality. It’s been estimated that more than 60 percent of data integration and data warehouse projects either are seriously delayed, go over budget or fail altogether due to poor data quality. When considering how to increase the quality of a company’s data, most IT and business managers immediately grasp how it will help save them time and resources.

Yet many managers still need to find an easy way to demonstrate to their executives the expected ROI of data cleansing and enhancement technologies. In the past, this required rather lengthy Proof-of-Concept sessions during which vendors brought samples of customers’ data back to their labs, cleansed and improved it, then gave it back for customers to gauge the level of improvement that could be achieved over time, thereby allowing them to compute their ultimate projected levels of ROI. In recent years that hasn’t been enough for many customers. Now they usually request vendors to come onsite and apply data profiling and cleansing technologies directly to their data to give them immediate results, rather than projections.

In parallel with this trend, technology for data assessment and profiling has progressed rapidly over the past few years. Customers are now able to take advantage of more robust profiling capabilities that don’t hinder the performance of operational production environments. And in so doing, they can capture a snapshot of their data at specific points in time, before and after cleansing, which provides a means to compute savings based on the delta between original and scrubbed data.

Over the past two years, data management vendors have seen this situation present itself more and more frequently, becoming the norm among new enterprise Requests for Proposals. Realizing the tremendous synergies between data profiling and data cleansing, progressive vendors have taken the next most logical step and added data profiling to their portfolio.