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 ...

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 ...

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 ...

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

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 ...

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 ...

The headless data architecture is the formalization of a data access layer at the center of your organization. Encompassing both streams and tables, it provides consistent data access for both ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

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.