Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...

Data models are used to represent real-world entities, but they often have limitations. Avoid these common data modeling mistakes to keep data integrity. Data modeling is the process through which we ...

In an era where data is a strategic asset, organizations often falter not because they lack data—but because their architecture doesn’t scale with their needs. Leaders must design data ecosystems that ...

Every data modernization effort starts with a blueprint. The architecture looks clean. The data flows are defined. The platform choice is justified. Whether it is a data warehouse, a data lake or a ...

The evolution of data architecture is accelerating. In 2025, 85% of DBTA subscribers reported plans to modernize their data platforms—driven largely by the explosive rise of GenAI and large language ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.

When it comes to business information, chief information officers (CIOs) and chief data officers (CDOs) are tasked with bringing order to chaos. As firms gather ever more data, they face both ...

A headless data architecture means no longer having to coordinate multiple copies of data and being free to use whatever processing or query engine is most suitable for the job. Here’s how it works.