From Raw Data to AI
Engaging insights on data governance and AI implementation
Engaging insights on data governance and AI implementation
Data stewardship (DS) is the practice of overseeing an organization’s data assets to ensure they are accessible, reliable, and secure throughout their lifecycles. Learn about the different stewardship types and their importance, challenges, and roles in emerging technologies.
Data fabric is an innovative approach to Data Architecture that simplifies Data Management through unification. But its concepts can seem overly technical. This "What is..." article demystifies the data fabric and describes its impact on future improvements and emerging technologies.
Master Data Management (MDM) can be tricky to understand. It connects all enterprise data assets to enable the understanding and execution of business activities. This "What Is" article will cover its meaning, how it works, its advantages, drawbacks, use cases, and some tips.
With the increasing use of generative AI, companies are turning to graph databases to train AI models and extract insights. This piece will cover the workings of a graph database, its distinctions from other database technologies, and explore various types available.
Data dictionaries are a unique tool that describes data in business terminology. This piece explains their uniqueness from data catalogs and data models. It also describes its benefits and function in data governance.
Michelle P. Knight: Engaging & Educational Writing
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