To build a data warehouse, data must first be extracted and transformed from an organization’s various sources. Then, the data must be loaded into the database in a structured format. Finally, an ETL ...

A data lake is not a direct replacement for a data warehouse; they are supplemental technologies that serve different use cases with some overlap. Most organizations that have a data lake will also ...

But should they be stored in a data warehouse, a data lake, or an old-fashioned database? It all depends on how that data is going to be used.

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 ...

There are a few key differences between data warehouses and data lakes. Here’s what K–12 IT leaders should consider when looking at how they might address their schools’ data storage needs. What Are ...

Read here A data warehouse stores data from a variety of “known sources” from across a company or organisation. This data is referenced by employees and decision-makers and exchanged regularly — ...

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 ...

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 ...

Part 4 of CRN’s Big Data 100 takes a look at the vendors solution providers should know in the data warehouse and data lake systems space.

This week CRN is running the Big Data 100 list in a series of slide shows, organized by technology category, spotlighting vendors of business analytics software, database systems, data warehouse ...