Data lakes and data warehouses are both very important for data analysis - and very different. Here's how to decide which you need.

We asked experts to help us shed light on the differences between a data lake and a data warehouse and what that means for your organization.

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.

A Super-Simple Explanation For Anyone If you’re even tangentially involved with big data, you know that finding storage solutions for the volumes of data being generated every second is of utmost ...

A data warehouse contains structured data whereas a data lake can contain structured, unstructured, and semi-structured data. Data in the data lake comes from multiple sources and will have varying ...

Data warehouses and data lakes also exist to support different enterprise requirements. The data warehouse is good for repeatable and repeated queries using high-quality, cleaned data, often run ...

As businesses continue to focus on leveraging Big Data, IT teams can prevent raw data from being siloed by gathering it into a central repository.

Dive into data lakes—what they are, how they're used, and how data lakes are both different and complementary to data warehouses.

A data lake isn't the same as a data warehouse and vice versa. The easy thing to do, IMO, is to evaluate whether what you want to do is one or the other and then proceeding from there. Just ...

At the 2nd Annual Semantic Layer Summit, which took place April 26, AtScale founder and CTO Dave Mariani sat down with Bill Inmon, recognized by many as the father of the data warehouse, to discuss ...