The cleaned-up data is then converted from a database format to a warehouse format. Once stored in the warehouse, the data goes through sorting, consolidating, and summarizing, so that it will be ...

The “data” part of the terms “data lake,” “data warehouse,” and “database” is easy enough to understand. Data are everywhere, and the bits need to be kept somewhere.

The database virtualization platform sits between applications and the new destination data warehouse. Like any virtualization technology, it decouples two otherwise tightly bonded components.

An advanced database virtualization platform can even create virtual databases off of other virtual databases, allowing teams to provision a copy of the production data warehouse, perform changes, and ...

Essentially, a data warehouse is an analytic database, usually relational, that is created from two or more data sources, typically to store historical data, which may have a scale of petabytes.

Here, we've split the most important discrepancies between database and data warehouse so you can highlight all aspects and select the one that meets the requirements of your data structure situation.

With a data warehouse, typically, the information was originally stored on different computers, using different programs, and is not necessarily organized using traditional database techniques. So ...

A configuration management database (CMDB) is a data repository that stores information about all hardware and software assets in your IT environment. This critical component of the ITIL framework ...

The response to this question is always the same. Data warehouse projects fail when they are treated as purely technology projects and aren’t focused on the end users and delivering value.

The Boston College Enterprise Data Warehouse (EDW) supports reporting and analytics over a broad spectrum of University data. Developed in 2003, ... The EDW is the University’s largest database and ...