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 ...

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 ...

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 ...

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 ...

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.

Data lakes are cool, but you don’t have to jump in head-first. It’s easy to start by dipping a toe: Integrating a legacy data warehouse into a data lake leverages the structured systems that ...

Data warehouse software is essential for companies looking to streamline their data centers or implement business intelligence software. Business intelligence software stores and analyzes huge volumes ...

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 ...

Data quality is paramount in data warehouses, but data quality practices are often overlooked during the development process.

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

Snowflake Inc. is a leader in the data warehousing space, and is looking to expand into other areas like data lakes. Click for more on SNOW stock prospects.