Data governance professionals should take advantage of the variety of social media and social networking opportunities available to advance their knowledge, their programs, and their careers Most data governance initiatives start as a result of an event (discovery of data
Healthcare data can present a series of challenges not often found in other industries, sometimes based on the disparate systems and processes Data management in many industries, such as travel, transportation, retail, finance, can seem similar to many practitioners. However,
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
Every organization needs an enterprise approach to manage its data assets; every program should be based on common guiding principles Many organizations struggle to obtain the full benefits of their Enterprise Information Management (EIM) initiative by approaching the framework components
The purpose of data documentation is to collect information about the data to facilitate understanding, interpretation, transformation, use, etc. The semantics of the term “documenting” include “Record or report in detail, support with citations or references, support with evidence or
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,
Three fundamental principles: Severability, Accommodation, and Wholeness, form the basis of all fundamental business rules and policies. What principles in the real world (not software) necessarily underlie meaningful, pragmatic expression of business rules and other elements of guidance (i.e., advices
All successful business intelligence / analytics endeavors are based on a formal strategy and use a best-practices based methodology, even in agile environments. Many companies do not have a data strategy, which is a basic component for successful management of
Managing reference data is a complex and essential activity to ensure usable data for operations and decisions Managing reference data poorly can have a profound impact on operations and business intelligence, data analytics, machine learning (ML) and artificial intelligence (AI)
