VP & Principal Analyst, Datacenter Compute, Matt Kimball, covers the recent updates to Oracle's Autonomous Data Warehouse (ADW) service, providing his thoughts on how these advancements position ...

Cloud data warehouses have emerged as the go-to repositories for amassing huge amounts of data and running advanced analytics and AI upon it. This is great news for customers, who no longer must worry ...

There once was no alternative to building a data warehouse on-premise, but with cloud providers targeting analytics, building data warehouses on-site is looking obsolete.

Also read: Top Big Data Storage Products Differences between data lake and data warehouse When storing big data, data lakes and data warehouses have different features. Data warehouses store ...

Topics discussed that support the Data Warehousing process are data modeling, data transformation, multi-dimensional databases, data extraction and storage, warehouse loading, client/server, and the ...

Protecting data at rest, in transit, and during processing is key to your organisation's smooth running. Here are some points to consider.

The Snowflake platform offers all the tools necessary to store, retrieve, analyze, and process data from a single readily accessible and scalable system.

Data quality is paramount in data warehouses, but data quality practices are often overlooked during the development process.

What is a data lake? Some mistakenly believe that a data lake is just the 2.0 version of a data warehouse. While they are similar, they are different tools that should be used for different purposes.

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 ...