Data analytics have either been centralized or decentralized. Data mesh tried to fix that. The hub-and-spoke model goes further.

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 ...

As companies implement identity resolution solutions, many are left with the challenge of needing to merge offline customer ...

Designing your data warehouse Let’s start at the design phase. When planning your design, the vision for your new data warehouse is best laid out over an enterprise data model (EDM), which consists of ...

The Boston College Enterprise Data Warehouse (EDW) supports reporting and analytics over a broad spectrum of University data. Developed in 2003, the EDW has advanced in terms of content, information ...

Current enterprise data architectures include NoSQL databases co-existing with RDBMS. In this article, author discusses a solution for managing NoSQL & relational data using unified data modeling.

One of the most important shifts in data warehousing in recent times has been the emergence of the cloud data warehouse. Previously, setting up a data warehouse required a huge investment in IT ...

Cloud-native Snowflake seeks to overcome the challenges of previous generations of data warehouse technology and embrace big data. How is its approach unique?

The DBA or data warehouse specialist must have extensive knowledge of data warehouse technologies and principles. Her role is to build the model for the data warehouse and design test cases for ...

With the new release, Oracle is expanding the appeal of the autonomous data warehouse to add end-to-end self-service experiences geared for business users.