There are many definitions of data quality, but the commonly understood meaning is: the degree or extent to which an organization’s data meets certain quality characteristics such as: accuracy, completeness of data, validity, uniqueness, consistency, integrity, timeliness and up-to-date. Eventually, data must be able to meet with user and customer demands for efficiency.
High quality data, therefore, is data that can satisfy the requirements of its intended use. An example of high-quality data is data that has the right names and addresses for a company to use in a marketing campaign.
Industries most affected with bad data are healthcare, finance, education, and other public-service institutes where bad data can wreak havoc in people’s lives. Therefore, it’s imperative for organizations to focus on implementing data quality initiatives.