Depending on the size of the organization, a data warehouse runs the risk of extra work on departments. Each type of data that's needed in the warehouse typically has to be generated by the IT ...

Start here: Cloud vs. on-premise data warehousing. Two main types of cloud warehouse solutions exist, including cloud-based warehouses and on-premise warehouses.

Data lakehouses combine the best of data warehouses and data lakes, enabling organizations to run analytics on all types of data. Learn about the benefits and features.

Data warehouses, on the other hand, are “schema on write,” meaning that data types, indexes, and relationships are imposed on the data as it is stored in the EDW.

Traditional data warehouses, on the other hand, are “schema on write,” meaning that data types, indexes, and relationships are imposed on the data as it is stored in the data warehouse.

Top 25 firm Armanino plans to launch a data warehouse service for smaller organizations later this year and has been using AI to develop some of its rollout strategies. Carmel Wynkoop — Armanino's ...

Data warehouses map data into a predefined structure before it’s quarriable, but data lakes are more flexible. A data lake collects all types of data without imposing a structure until the query is ...

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.

The ability to transform data into information and knowledge is at the center of business success. Decision-makers at every level of an organization require pertinent information to do their jobs well ...