Data models are now as much about lineage and data "whereabouts" as they are about engineering quality databases, putting them squarely in the data warehousing/BI realm. This article discusses some ...

In a data mesh, the warehouse still has a role, but it becomes just another consumer of data rather than the oracular source of truth. “We don’t want to go back to ground zero and rebuild ...

Image: Tee11/Adobe Stock. At its heart, data modeling is about understanding how data flows through a system. Just as a map can help us understand a city’s layout, data modeling can help us ...

A data warehouse is traditionally the go-to architecture for structured data. It’s optimized for analytics and reporting, providing high performance and reliability. In contrast, data lakes are ...

Subject area model. This identifies major business subject areas defining the enterprise scope. Conceptual data model. The next layer defines business entities and their relationships and includes a ...

Data model is needed to help understand and re-structure data for data analysis. Data integration system can extract dimension data from original streaming data to data warehouse according to data ...

This article was contributed by Gunasekaran S., director of data engineering at Sigmoid. Over the years, cloud data lake and warehousing architectures have helped enterprises scale their data ...

A novel approach from the Allen Institute for AI enables data to be removed from an artificial intelligence model even after ...

Data warehouse topology ends up multiplying data (creating governance issues, among other problems), ... InfluxDB’s new model for time series workloads. By Pete Barnett. May 26, 2025 6 mins.