DataOps, short for data operations, is an emerging discipline that focuses on improving the collaboration, integration, and automation of data processes across an organization.
DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics.
Understand how data lineage tools provide a visual representation of your data's journey across multiple systems and transformations.
In this article we’ll show 12 data integrity examples, includes he different types and risks organizations face today.
Data quality testing refers to the evaluation and validation of a dataset's accuracy, consistency, completeness, and reliability.
A worthy list of the top data strategy influencers and content creators that you should follow on LinkedIn.
A helpful list of the top data analytics and science influencers and content creators that you should follow on LinkedIn.
Jump into our most noteworthy list, of the Top 25 data engineering influencers and content creators that you should follow on LinkedIn.
We recently had the opportunity to join an episode of The Ravit Show, to discuss how data observability and governance work together. Learn how more observability leads to better governance with insightful questions answered by Databand and IBM experts.
In this blog, we'll explain why data observability is so important, what’s needed for data observability, and how Databand can help.
