Sometimes the resulting architecture has a hub, sometimes not. That’s different from data integration’s architectural focus on interfaces and data transformations, which almost always hinge on a hub.

A hub-and-spoke data warehouse architecture pattern works by following a series of steps. First, the data from various sources is extracted, transformed, and loaded (ETL) into the hub.

Learn about common data integration architectures and how to evaluate them based on data quality criteria, such as accuracy, completeness, consistency, timeliness, relevance, and security.

Using the hub-and-spoke model of a centralized data hub, businesses can easily achieve their real-time data goals, says Hanadi Salameh, an Enterprise Digital Architect at Cognizant.

In a previous article, I discussed redefining the challenge facing companies that want to become data-driven. The way most people think about this problem—and the most commonly proposed solution ...

So, when developing your reference architecture for a data integration hub, be sure to use robust data governance policies - don’t wait for the headlines to include your company and someone’s ...

Responding to customer complaints about its lackluster support for data integration with competing products, Oracle is introducing an integration initiative to its customers and developers. The ...

The pre-engineered, validated hardware and software solution delivers the Greenbird Utilihive hub on Intel based Dell EMC VxRail and PowerScale platforms – the only fully integrated, preconfigured, ...

A data integration hub is a proven system which provides a self service model for publishing data. Such a hub can enable certain information to be made readily available for a variety of users ...