Data Management | News, how-tos, features, reviews, and videos
We’ve known for years that application portability between public cloud providers is not easy or cheap. Here are a few approaches to try instead.
Data pipelines are essential for connecting data across systems and platforms. Here's a deep dive into how data pipelines are implemented, what they're used for, and how they're evolving with genAI.
Distributing workloads among various providers offers protection from failure, but make sure your business can handle the complexity and costs.
Until CIOs are ready to confront data that is siloed, redundant, or can’t be traced through the business process, generative AI will not pay off.
After all these years, we still haven’t implemented enough finops, automation, and governance to stop wasting money in the cloud.
For those who have done the real work of data modernization and preparation, AI is worth its high price tag.
From performance to programmability, the right database makes all the difference. Here are 13 key questions to guide your selection.
Microsoft delivers a one-stop shop for big data applications with its latest updates to its data platform.
Apache Airflow is a great data pipeline as code, but having most of its contributors work for Astronomer is another example of a problem with open source.
New techniques make graph databases a powerful tool for grounding large language models in private data.