A data warehouse is defined as a central repository that allows enterprises to store and consolidate business data extracted from multiple source systems for the task of historical and trend ...

Data lakehouse architecture combines the best of cloud data lake and warehousing architectures to give teams the most recent data.

Learn how one higher education institution is modernizing and strengthening its endowment and fundraising strategy by ...

As data volumes continue to grow exponentially, AI inference and big data analytics demand systems that can scale, while providing real-time processing capabilities. A data lakehouse combines the ...

By combining streaming, location, and machine learning analytics into a unified platform, the streaming data warehouse actually untangles a data architecture.

Essentially, a data warehouse is an analytic database, usually relational, that is created from two or more data sources, typically to store historical data, which may have a scale of petabytes.

In its announcement on 2/18, MapR made a strong statement about its vision of the right product to support use of big data in the business world. MapR’s product is its platform, a set of ...

In the ongoing debate about where companies ought to store data they want to analyze – in a data warehouses or in data lake — Databricks today unveiled a third way. With SQL Analytics, Databricks is ...

A fast, no-fuss data warehouse as a service, Snowflake scales dynamically to give you the performance you need exactly when you need it ...

Nearly every data warehouse ecosystem has attempted to manage master data within its data warehouse architecture, but has focused on mastering data after transactions occur. This approach does little ...