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 ...

Has the traditional data warehouse finally reached the end of its life? If so, what will follow it? Will it be a hybrid? We find out.

To build a data warehouse, data must first be extracted and transformed from an organization’s various sources. Then, the data must be loaded into the database in a structured format. Finally, an ETL ...

The early implementation of the cloud service is still on a traditional data warehouse architecture where storage is directly attached to compute.

What is a data lake? Some mistakenly believe that a data lake is just the 2.0 version of a data warehouse. While they are similar, they are different tools that should be used for different purposes.

Inmon versus Kimball is one of the biggest data modelling debates among data warehouse architects. Here is some help to select your own approach.

Why is Steve Jobs standing in front a huge data warehouse just weeks after patching a big privacy hole in iOS? Steve Jobs' morning keynote at Apple's World Wide Developers Conference included some ...

A data lakehouse addresses these typical limitations of a data lake, as well as data warehouse architecture, by combining the best elements of data warehouses and data lakes to deliver significant ...