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 Warehousing is the storage of big data. Data mining is the analysis of the collected data in order to find trends in the ...

If data pipelines and streams are the future, why are we still thinking of data as static?

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 benefits of a centralised and efficient data warehouse are obvious, but it's even more obvious that building one can be a right royal pain in the back end.Prior failures with building data ...

As companies embrace digital trans­formation across the enterprise, it is data and the effective use of it that determines whether new technologies such as AI, auto­mation, and analytics will be ...

Compliance with increasingly rigorous reporting obligations and a thirst for customer behaviour information are driving the financial sector's rising investment in data warehousing and analytics ...

First, there was a data warehouse – an information storage architecture that allowed structured data to be archived for specific business intelligence purposes and reporting. The concept of the ...

What is the future of data warehousing with relation to the cloud? This question was originally answered on Quora by Christopher Lynch.

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.

Cloudera’s head of emerging business shares lessons that machine learning practitioners can learn from their cousins in data warehousing.