Data Quality

Every organization should develop and implement a plan to assess current data quality and take clear steps to improve and maintain it High-quality data quality

Informal data quality improvements are often at odds with what the organization actually needs.  Focus on organizational data quality and not on individual efforts. Often

Achieving high quality data is a goal that all professionals and executives should strive for continually.  Observations on how to achieve high quality data and

Marketing functions can experience a variety of pain points in their management of data. Understanding these challenges and arriving at effective solutions can offer many

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