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 ...

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 ...

Data governance: While the data in the data lake tend to be mostly in different file-based formats, a data warehouse is mostly in database format, and it adds to the complexity in terms of data ...

The debate goes on. As part of the CRN 2023 Big Data 100, CRN has compiled a list of data warehouse and data lake system and service vendors that solution providers should be familiar with.

The data lakehouse – it’s not a summer retreat for over-worked database administrators (DBAs) or data scientists, it’s a concept that tries to bridge the gap between the data warehouse and ...

At Ignite, Microsoft enhances its cloud database, warehouse and lake services Microsoft unveils new capabilities within Azure Synapse Analytics, Cosmos DB, and its stable of open source databases.

“It used to be data lake or data warehouse, and you pick one. You probably have both, but you’re not bridging either to their highest potential,” Sharma said.

“A lot of enterprise out there today have two architectures,” he says. “They’ve got their data warehouse and they’ve got their data lake, and they’re moving data between them every day, at quite high ...

Ignite 2019: Microsoft has revved its Azure SQL Data Warehouse, re-branding it Synapse Analytics, and integrating Apache Spark, Azure Data Lake Storage and Azure Data Factory, with a unified Web ...