Sure. For example, when the data quality software addresses a problem where there is no way to control the creation of the data and the team tasked with implementing it is accountable for the results. There is no need for additional overhead in that case.
One such situation might involve data standardization and correction for the mailing of marketing materials. The problem may be localized to a specific division that doesn’t control the data creation process, and applying the required data quality fix is self-contained.
At any point where there is an impact on another group, or where the organization can benefit from eliminating the root cause of a data quality problem instead of simply fixing the resulting issues, you might want to reconsider your data governance policies.
Dig Deeper on Data quality management software
Related Q&A from David Loshin
Fact tables and dimension tables are used together in star schemas to support data analytics applications. But they play different roles and hold ... Continue Reading
Learn how often companies should update their data quality strategy. See how changes in data quality problems create new challenges and how revising ... Continue Reading
Learn what to consider before adopting open source data quality software to help with identity resolution and name matching. Continue Reading
Have a question for an expert?
Please add a title for your question
Get answers from a TechTarget expert on whatever's puzzling you.