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Improving data quality begins with people, processes

Rachel Wheeler Archive
As the amount of information enterprises gather continues to increase, ensuring data quality is becoming an essential aspect of running a successful business. Rather than investing thousands of dollars in data quality tools, companies should shift their focus on people and processes, according to a TechTarget report.

"By and large, data quality issues are caused by people around the data just not doing the right stuff to make sure it gets entered and maintained in a high-quality way," Gartner research vice president Ted Friedman said, according to TechTarget.

Organizations need to implement training and education programs that teach employees the importance of data quality and how simple errors can cause severe repercussions to ripple through the entire company. If decision-makers ensure workers understand how poor data quality can impact operations and efficiency, businesses may be able to deter otherwise costly ventures trying to fix mistakes, the news source said.

Firms should also look at innovative ways to fill "data quality holes," TechTarget asserted. Many times these vulnerabilities can be patched with an inexpensive solution.

For example, errors often revolve around manual processes. By taking humans out of the equation and implementing automated solutions instead, these holes can be filled without causing any additional problems, TechTarget said.

Companies can also leverage master data management systems that ensure the reliability and accuracy of mission-critical information. MDM solutions will help firms make more informed and precise decisions that will grant them the ability to gain a competitive advantage over rival firms.

A separate report by Aberdeen Research found that nearly two-thirds of the best-in-class businesses surveyed had formal MDM systems in place, allowing them to minimize errors and improve data quality.

Database administrators can also be invaluable assets to a company's data quality improvement processes that are somewhat constricted because of budgets restraints, according to TechTarget. These individuals can design programs that expose patterns in data quality, allowing IT executives to determine information that doesn't fall in line with the model.

In the end, employees and best practices are the best ways to ensure organizations only leverage high-quality data, TechTarget said. Implementing new initiatives, however, should be grounded with concrete metrics, determining what needs to be done and how.

"You can't just go to people and say that data quality is the right thing to do," Friedman said, according to TechTarget. "You need to measure and you need to show with facts how good or bad the data is and how that is impacting the business."