Data Quality

Effective business intelligence, analytics, AI/ML requires attention to legacy systems for improved data quality and data management Business Intelligence, analytics, cloud, ML/AI, digital, and business

There are many sources of data in every organization, and many of these sources are valid.  Therefore, challenges can exist about which source is the

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 quality is dependent on achieving measurable goals across six critical dimensions All professionals understand the importance of making data-driven decisions. But the presence and

There are many characteristics of information quality.  Some are intrinsic to the nature of the data, including objectivity, believability and reputation. Many discussions about the

Determining “accuracy” is not always an easy task, and not all data lends itself to discovering a single value for data quality accuracy Several recent

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

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

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

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

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

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