Data lakes and data warehouses are two of the most popular forms of data storage and processing platforms, both of which can be employed to improve a business’s use of information. However, these ...

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. Data lakes are cool, but you don’t have to jump in head-first. It’s easy to start by dipping ...

Data lake is a newer IT term created for a new category of data store. But just what is a data lake? According to IBM, “a data lake is a storage repository that holds an enormous amount of raw or ...

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. Big data is here, and it’s getting bigger by the day. With ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More A data lake is defined as a centralized and scalable storage repository ...

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 ...

I work at a startup and our data is very messy at the moment, as you might imagine. We have a few product level transactional databases, but no central database to store it all in a useful way for ...

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 data ...

Enterprise data warehouses, or EDWs, are unified databases for all historical data across an enterprise, optimized for analytics. These days, organizations implementing data warehouses often consider ...

Data warehouses have been at the center of data analytics systems within many businesses and organizations for years, going as far back as the 1980s. With the growing adoption of cloud, data warehouse ...