Data Modeling

Data modeling is the practice of defining and organizing information so it can be understood, used and governed consistently across an organization. It creates a shared language between business, data and technology teams, making complex information clear, structured and reusable.

A good data model explains what your data means, how it relates, and how it should be used in reporting, analytics, automation and AI. It improves data quality, speeds up development and ensures that decisions are based on trusted, well-defined information.

Data modeling is essential for:

• Public sector organizations needing clarity, interoperability and governance

• Companies wanting scalable analytics and high-quality reporting

• Data and architecture teams managing complex environments

• Any organization preparing for automation or AI

At DSharp, we help teams build strong semantic foundations through intuitive modeling, consistent definitions and metadata-driven automation, ensuring data is meaningful, reliable and ready for intelligent use.

On this page a selection od data modeling articles.