Data modeling is the framework that lets data analysis use data for decision-making. A combined approach is needed to maximize data insights.

Can software development be accelerated and materially reduce refactoring of in-production modules by giving data modelling a more prominent position in the Agile software development environment?

Unified data modeling supports features like document schema of NoSQL databases and reverse engineering of data from an existing database. It also supports visual refactoring of existing databases.

Microsoft has made a promised public preview of its Common Data Model (CDM) entity database available to testers. CDM is at the heart of the coming Microsoft Dynamics 365 bundle.

Graph data modeling requires a different paradigm than modeling with Relational or other NoSQL databases. InfoQ spoke with Jim Webber and Ian Robinson about data modeling with Graph databases.

One of the most important steps in desiging a database is establishing the data model. Part one of a two-part article describes how to create a logical model.

Data models are used to represent real-world entities, but often have limitations. Avoid common data modeling mistakes for data integrity.

This year is an expansive one for the database ecosystems that have evolved around the major platforms. Artificial intelligence (AI), machine learning, the Internet of Things (IoT), and cloud ...

This approach features a centralized database linked to other data stores with a common data model that carries information from one point to another, without the need to rewrite code.

A multimodel database provides a single back end that supports multiple data models. It’s all about being able to choose the best data model for the job with a single storage substrate.