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Succeeding with Data Governance and Data Quality

Deanne Larson, Ph.D., president of Larson & Associates, discusses data governance and data quality -- including success factors for data governance and which roles are responsible for data quality within an organization.

In a TDWI “Speaking of Data” podcast earlier this year, Deanne Larson discussed data governance and data quality, including success factors and the roles responsible for data quality. Larson is president of Larson & Associates and a well-known academic and industry educator. [Editor’s note: Speaker quotations have been edited for length and clarity.]

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“The concept of data governance can be sometimes nebulous, but generally it refers to the processes, policies, standards, and controls an organization uses to make data an asset,” Larson began. “This includes rules that provide consistent, accurate data and the security protocols for keeping it safe.” Identifying those responsible for data -- the owners and stewards -- also falls under the scope of data governance.

Succeeding with data governance can be a struggle, though, Larson admitted. “Fortunately, we are seeing some emerging success factors.” The most important starting point is to have clear goals and objectives that are well defined and tied to the company’s business strategy. The next most important factor is to have strong executive sponsorship -- ideally someone at the C-level. Effective governance is an enterprisewide effort and requires strong leadership to ensure everyone knows it’s a company priority.

What gets most organizations started on their data governance journeys?

“Many times, governance gets started because organizations realize they have requirements with security and privacy, but other factors are just as important. For example, data quality is as important as either of those two things,” Larson said. Accuracy and consistency, two key aspects of governance, are the result of data quality. Poor data quality can lead to loss of productivity, increased costs, and most important, poor decision-making.

Data quality, as part of governance, also includes processes such as profiling and monitoring, cleansing and remediation, and data lineage and traceability.

The biggest challenge, though, according to Larson, is identifying the people in the organization to take responsibility for governance.

“Although it’s the responsibility of the entire organization, there are still key roles that need to be filled,” Larson explained. “Data stewards, for example, and data analysts often help lead data quality efforts.” IT also has a responsibility when it comes to managing the technical infrastructure and making sure data management processes are in place.

[Editor’s notes: To hear the full conversation, replay the podcast episode here. TDWI is offering a seminar on data governance and quality taught by Deanne Larson August 28-30, 2023. Dr. Larson will also be teaching four classes at the TDWI Orlando Conference, November 5-10, 2023. At the Orlando conference, Richard Hines will be teaching courses on data governance principles and data quality management.]

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