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What Is Data Quality Management and Why Is It Important?

The concept "garbage In, garbage out" can easily be applied to the data used by companies to inform everything from hiring decisions to anticipating and meeting the demands of emerging markets.

But as the volume of data generated by internal and external sources grows almost exponentially, ensuring its integrity becomes ever more challenging. Data quality management is often complicated by legacy systems that struggle to communicate and that hinder interdepartmental collaboration of operating units.

Well-managed data reliably supports a company's analytics initiatives, helps refine its predictions and decisions, and builds trust in the accuracy of performance metrics. On the other hand, data managed poorly can cripple a company.

Ensuring data quality begins with people, as InfoWorld, an online resource for emerging enterprise technologies, explains in an article entitled, "Data Science Needs Drudges": "For years, we've oversold the glamorous side of data science (build models that cure cancer!) while overlooking the simple reality that much of data science is cleaning and preparing data, and this aspect of data science is fundamental to doing data science well."

Struggling to Implement Data Quality Management

The research and advisory firm Gartner notes that 60% of the respondents to a data quality management survey said inter-departmental issues present a significant challenge.

Among the sources of those frustrations is data generated by global operations with unique customer, employee, supplier and vendor requirements, low levels of data literacy and siloed operations.

"Consequently, key business goals, such as financial performance and customer experience are adversely impacted," Gartner said in a report on data quality.

Data Quality Management Career and Advancement Opportunities

As companies become increasingly reliant on data for competitive advantage and governance, its administration becomes ever more critical, driving demand for professionals with expertise in data management.

Through an M.S. in Business Analytics program, data experts can hone their advanced analysis skills by emphasizing real-world applications through case studies, simulations and data-intensive projects. Earning such a degree provides them an advantage in the competition for data quality management positions.

Learn more about UNCW's online Master of Science in Business Analytics program.


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