Enterprise data platforms increasingly unite analytics, governance and orchestration, with new generative and agentic AI-enabled features to improve autonomy and speed.

Understanding data is a prerequisite to gaining control of any enterprise. But understanding is only useful if that knowledge can be shared and transmitted. Effective data modeling should be a ...

Model Execution & Data In-Warehousing: Finally, as data keeps increasing and analytical outputs are needed in shorter timeframes, a big challenge to financial institutions is the timeliness of ...

When designing an effective enterprise data strategy, organizations often choose between a top-down and a bottom-up approach. Each method has its unique advantages and is suitable for various ...

Data Modeling Data Modeling and Database Design and Development – including popular approaches such as Agile and Waterfall design - provide the basis for the Visualization, and Management of, Business ...

So, given that, do you need an enterprise data model? If you are building a more or less stand-alone application where the data has no significant reuse, then data modeling is often counterproductive.

Current enterprise data architectures include NoSQL databases co-existing with RDBMS. In this article, author discusses a solution for managing NoSQL & relational data using unified data modeling.

An enterprise data model describes how the business wishes to function. That means policy and procedure will be affected by the data modeling effort (and vice versa).

Will some data remain at the business unit level and not be part of the enterprise data model?