In an era where data is a strategic asset, organizations often falter not because they lack data—but because their ...

It involves all major data processes: collection, storage, access, usage, management and protection. Past versions of data architecture were primarily focused on getting through the day-to-day work.

The good news: Organizations don’t need to stop all work to create an enterprise data architecture. “Health systems can and should work incrementally,” Mr. O’Neill said.

These architectures combine OLTP systems and stream processors as the write-ahead log (WAL), Iceberg as the storage layer, query engines such as Spark and Trino for data processing, and real-time ...

In a recent Engineering article, researchers Jinghai Li and Li Guo discuss the future of data science and its significance for AI. They point out the challenges in scientific data systems, suggest ...

As organizations seek to design, build, and implement data and analytics capabilities, they are pressed to reinvent and reorient their data architectures-as well as justify these activities with ROI ...

Traditional architecture and technologies and newer big data approaches each offer advantages. In a session at Data Summit 2019, titled “Designing a Data Architecture for Modern Business Intelligence ...

Army Intelligence Data Platform (AIDP), managed by Project Manager Intelligence Systems and Analytics (PM IS&A), enables intelligence soldiers the ability to gather, analyze and distribute ...

In response, USPTO has become a pioneer in building and operationalizing Zero Trust Architecture across the five pillars of the federal Zero Trust framework: users, apps, data, networks, and devices.