To help make big data analytics applications more effective, IT teams need to augment conventional data quality processes with measures aimed at improving the usability of data.
Data quality processes have become more prominent in organizations, often as part of data governance programs. For many companies, the growing interest in quality is commensurate with an increased need to ensure that analytics data is trustworthy. That’s especially true with data quality for big data; more data usually means more data problems.
Author: David Loshin