An organization’s data quality is often the result of poor metadata management. Improve business and technical metadata and manage it properly to ensure higher quality data and information. The state of an enterprise’s information depends on its data quality and
Accuracy is not the only measurement that can or should determine quality for an organization’s data. Data can be accurate in one context and inaccurate in another, and both versions can have value. Many people think accuracy is the sole
Accuracy, more than most of the other data quality characteristics, is often considered to be the foundational dimension of good data quality Accuracy is one of the 16 characteristics or dimensions of data quality. It is considered to be the
Most data quality experts identify 16 major characteristics that affect the quality of data and information. It is important to understand their context before examining each characteristic. Information quality can have many different definitions. When users describe issues with data,
To enable information quality in any environment, it is essential to identify the collectors, consumers, and custodians of each item of information and define their responsibilities clearly. If organizations want to treat information as a product, then they must look
A key principle to start and sustain any successful business process is to “treat data and information as a product.” There are many issues related to information quality and information management practices that affect information quality in organizations. Every organization
Every organization needs a set of roles that are responsible for managing the quality of the data and metadata that are used in the enterprise’s operations and analytics. These roles are the “data quality heroes.” Introduction Data management entails the
A CONVERSATION WITH TOM REDMAN : Anne Marie Smith, Ph.D. Data quality has been a continual challenge for almost every organization for many years. In this recap of a conversation with Dr. Thomas C. Redman, he offers a possible simple
Master data management continues to be plagued by poor data quality, costing many organizations time, money, lost customers, lost reputation and inefficiencies. Introduction In several surveys, taken by various research organizations about master data management and data quality, on average, 83%
ISO 8000 defines the parameters of data quality, so one can ask for quality data and verify that one has received quality data Introduction It is common to see the relationship between data and information represented as a pyramid with
