Data has never been more valuable to an organization. However, it is only as valuable as the integrity and quality of the data. Are those terms the same? This interesting subject came to us from Inside BIG Data in their article, “Demystifying the Difference Between Data Integrity & Data Quality.”
Businesses today are leveraging data to power nearly every function of their business. However, there is a major risk associated with that data if it’s not trusted.
While many use the terms data integrity and data quality interchangeably, there are some important differences between the two.
Data quality serves as a subset of data integrity. It refers to the reliability of data. Evaluating data quality based on whether it’s complete, unique, valid, timely and consistent helps organizations ensure the information is designed to help drive results.
Data integrity provides the context on reliable and accurate data. It helps the information be useful for the organization.
Organizations are leveraging data to drive greater decision-making processes and results across nearly every facet of the business.
Melody K. Smith
Sponsored by Access Innovations, the world leader in taxonomies, metadata, and semantic enrichment to make your content findable.
