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.
Learn to talk fluent data with this data glossary, covering data terminology, and specific terms related to analytics, DataOps, data development, and more.
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.
Choosing a data modeling approach requires understanding things from business needs to methodologies. Here we unpack data modeling stages & approaches.
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.
Cloud data warehouse transformation with Agile Data Engine helps airports improve passenger experience and maximise efficiency beyond just DataOps and EDW
What is data modeling? Learn its importance and explore the three main types of data models to improve data governance and architecture.
DataOps Database Selection projects can be time-consuming and overwhelming. But with the right tools, like Agile Data Engine, you can design once and deploy anywhere, saving time and effort. Future-proof your data warehouse and streamline your cloud data journey.
Learn what Data Warehouse Automation (DWA) is, why it matters, and how it transforms traditional data management.
