In data warehousing, the logical model is often an afterthought or merely a carbon copy of the physical sans platform-specific properties. That limits the visibility and the use of the model to a ...

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 ...

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.

Data warehouse designs are the foundation of business intelligence projects. Find out 5 mistakes you need to avoid now.

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 ...

Software giant SAP Wednesday unveiled SAP Datasphere, the next generation of the company’s cloud data warehouse service with new data cataloging, simplified data replication and enhanced data ...

Although difficult, flawless data warehouse design is a must for a successful BI system. Avoid these six mistakes to make your data warehouse perfect.

Data Warehouse and Data Mart Design: ERwin governs and optimize data warehousing-specific modeling techniques for analyzing its performance.

Data lakes and data warehouses are achieving a measure of success in modern data architectures, but the emergence of the data lakehouse offers new challenges and opportunities for database ...

In the spirit of capturing and describing this data-warehouse revolution and the drivers shaping Data Warehouse 2.0, Oracle has assembled a list of the Top 10 Data Warehousing Trends for 2013, and ...