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Data quality focus affects all levels of business

Rachel Wheeler Archive
Business data quality is a central concern for companies trying to get ahead in the modern, information-driven market climate. TechTarget recently reported that the duty of keeping data clean and accurate does not only lie with top management officials. In fact, the source argued, the everyday business users who come in constant contact with the information have a strong responsibility to make sure their data management strategies are sound and live up to metrics.

Important priorities

According to the source, the process of getting business users invested in protecting the data they use should begin early, when the plan is being formulated. TechTarget spoke with consultant William McKnight, who stated that information quality plans should be carefully crafted, with significant time and effort put into them. He explained that standards are more likely to find acceptance if business workers are part of the process to determine the rules.

"Getting business users involved early in the process of creating standards is always a good idea," McKnight told the source. "They're likely to challenge the rules if they weren’t part of the process of determining them."

TechTarget went on to explain the difference between the outdated perception that business employees pose a threat to data through carelessness and the real factors that cause mistakes in a modern workplace. According to the source, many employees have to work hard and quickly, meaning there is little time in the day to enforce data cleansing policies. Gartner's Ted Friedman told TechTarget that inputting data could be one important point for business users to improve their data quality, making sure everything is placed into the system in a stringent and controlled manner.

Top leaders included

While it can be a challenge to get everyday data users to harness data quality, it can also be difficult to secure support from top executives. According to IT News Africa contributor Gary Allemann, the key to bringing top brass into the data quality world could involve explaining the project in terms of the value it creates for the business rather than the technical details of how it works or what it would accomplish.

Allemann explained that some data management professionals become blinded to the fact that not everyone can see the end results of bad data as they can. He suggested that such employees explain their message clearly and concisely for the benefit of leadership to secure the best results.