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. But should they be stored in a ...

Digital transformations often require real-time business processes driven by data from operational, historical and streaming sources. I've noticed that data and analytics leaders often use the terms ...

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 ...

Every college and university has data storage needs, and student records are just the beginning. IT systems demand storage as well: Internet logs, security events, building systems, security cameras ...

When it comes to data, today’s CIOs are being pulled in all directions. They’re asked to provide an effective data platform that supports machine learning and other data-driven innovation, but they ...

Aggregating data from a broad range of sources is critical to enhancing the consumer experience and providing the most innovative offerings. Finding the right data aggregation solutions and providers ...

The true measure of an effective data warehouse is how much key business stakeholders trust the data that is stored within. To achieve certain levels of data trustworthiness, data quality strategies ...

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. 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 ...