The team at Agile Data Engine likes to write about things we are passionate about: DataOps, data quality, solving business cases and keeping up with the evolving technology landscape.
Discover the downsides of separating data development and operations. Learn how merging these teams can drive efficiency, collaboration, and innovation.
“We couldn’t have done it without DataOps….” stated Karri Linoinnen, CDO of Nordic Investment Bank, at the 2024 Data Innovation Summit (DIS) in Stockholm.
Read on for perspectives on how Agile Data Engine helps business and IT departments improve their DataOps and take action to fix bottlenecks and issues.
Outlining Data Vault best practices - approaches for managing, structuring, and modeling data and data warehouses in complex, dynamic environments.
Data modeling as important as ever when you move your data warehouse from on-prem into the cloud - it's a crucial component of resilient data ops.
In DataOps, terms get muddled by jargon - as does data when stored in a data lake, eventually devolving into to a data swamp. Here's a brief guide to help.
DataOps database selection can be complex – but with Agile Data Engine, you design once, deploy anywhere, and streamline your cloud data journey.
DataOps is an approach that has gained popularity in recent years as a way to manage and develop data solutions in an efficient and reliable manner.
A blog post about dataops, analytics and data teams in 2022.
DataOps is an agile approach to enterprise data that speeds up time to value by optimizing data product development and operations.
