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

On the morning of August 21, Dameng Data's Vice General Manager, Fu Xin, delivered a keynote speech titled "Intelligent Multi ...

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.

Increasingly, customers are demanding that their databases take on multiple chores. Emergence of multi-model databases providing developers multiple paths through APIs is the latest evidence of ...

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.

With AI at the data level, you can use that model to do a lot of the work, and then apply vector search on top of that.

An example of a popular graph database system is Neo4j. Another Choice: The Multi-Model DBMS Yet another choice in the NoSQL market is the multi-model DBMS. A growing number of vendors have delivered ...

Marginal models for multivariate binary data permit separate modelling of the relationship of the response with explanatory variables, and the association between pairs of responses. When the former ...

Better data annotation—more accurate, detailed or contextually rich—can drastically improve an AI system’s performance, adaptability and fairness.