Data lakes are cool, but you don’t have to jump in head-first. It’s easy to start by dipping a toe: Integrating a legacy data warehouse into a data lake leverages the structured systems that have been ...

Data warehouses have proven to be great repositories for enormous amounts of critical information, but the process of preloading data into the necessary structure to run business analytics workloads ...

The data lake was a critical concept for companies looking to put information in one place and then tap it for business intelligence, analytics and big data. But the promise never quite played out.

Call them what you will—online analytical processing (OLAP) databases, enterprise data warehouses (EDWs), massively parallel processing (MPP) databases but databases designed for analytical workloads ...

Most credit James Dixon of the open source BI vendor Pentaho with coining the phrase “data lake.” Think of a data lake as an unstructured data warehouse, a place where you pull in all of your ...

MLflow is a Databricks open source project that's integrated into UDAP but available on an open source basis for integration with other platforms. MLflow helps with machine learning experiment and ...