• United States

Recognize the importance of data-quality management

Apr 11, 20062 mins
Data Center

* Data-quality management

A key element of information stewardship is data-quality management – that is, ensuring that the mission-critical data within an enterprise is reliable, accurate and complete. DQM is increasingly important as data is used by more people to make more decisions within the enterprise, and as compliance requires that certain types of data be kept accurate during the entire course of their lives.

IT executives understand the importance of DQM, but many of those same managers don’t deploy the necessary technology or processes to ensure their data-quality efforts are as good as they could be.

Indeed, until now, most IT executives have treated DQM as a tactical problem – fixing data in batch jobs or at a customer’s request – rather than as a strategic issue that requires forethought and planning. The key: avoid problems before they can affect the bottom line.

The first challenge lies in acknowledging, and defining, the problem. DQM is clearly an issue that resonates with IT executives. Nemertes last year surveyed 43 IT executives at companies ranging across industries for its benchmark “Information Stewardship: Holistic Data Management in the Enterprise.” When asked to describe their most critical information stewardship challenge, 30% of IT executives singled out DQM – more than any other information-stewardship issue. Despite that, only 26% of companies are using any kind of technology to manage DQM, and much of what’s in use is homegrown.

Many IT executives avoid using DQM technology because they are unfamiliar with its benefits; typically, they view it as nothing more than demographic-data updating software. But in fact today’s DQM tools do much more than that. They profile data, enrich it, help companies cleanly integrate data from disparate sources, and perform ongoing monitoring.

In fact, there are good reasons to think DQM technology is quite worthwhile. Overall, 44% of IT executives consider themselves “very” or “extremely” successful when it comes to data quality management. But among companies that report using some type of DQM technology, 63% say their efforts in that area are “very” or “extremely” successful; that number drops to just 35% among companies that are not using such technology.