Data quality issues are not limited to a particular type of organization. When you bring people, process, and technology together – there are going to be issues. But managing data quality has become more complicated due to changes in how data is produced, processed, and used. Tech Target brought this interesting topic to our attention in their article, “Align business and IT drivers through data quality best practices.”
Data is more real-time, automated, and business-driven than in the past. Previously, batch processing and manual data cleansing were prevalent and IT typically drove things. Data quality now requires more of an enterprise-wide view than a platform-specific one, due partly to an increased focus on ensuring data is accurate for reporting and analytics uses.
What hasn’t changed is the importance of data quality. Poor data quality can have an impact on an organization’s brand, reputation and customer loyalty, as well as its legal and regulatory compliance, thus affecting not only revenue, but also costs and profits.
Melody K. Smith
Sponsored by Access Innovations, the world leader in thesaurus, ontology, and taxonomy creation and metadata application.
