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.
Advanced data modeling is more important than ever. Agile Data Engine's data modeling for resilient data warehousing workshop helps you save millions in...
Data quality issues are present in all data warehouses. But how can you tell if the quality of your data is good? The answer is data quality dimensions!
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.
Discover how to choose the right data modeling approach by mastering the three stages: conceptual, logical, and physical modeling.
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.
