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 ...

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 ...

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 ...

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 ...

Part of the SD Times 100 2026 series. See the full SD Times 100 2026 list for every category and honoree. Every conversation ...

Industry discussions about what’s holding back AI often focus on security, graphics processing unit availability and other ...

Time flies in the world of data analytics and artificial intelligence (AI). Seemingly every day, new technologies rise, new use cases emerge, and new frontiers unfurl themselves before a world that ...

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 ...

Data scientists today face a perfect storm: an explosion of inconsistent, unstructured, multimodal data scattered across silos – and mounting pressure to turn it into accessible, AI-ready insights.

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.