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.
Unlock the power of automation in data modeling to streamline processes, enhance efficiency, and drive innovation. Learn how Agile Data Engine bridges the gap between design and implementation for maximum value extraction.
Advanced data modeling is more important than ever. Agile Data Engine's data modeling for resilient data warehousing workshop helps you save millions in...
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.
What is data modeling? Learn its importance and explore the three main types of data models to improve data governance and architecture.
This blog post explores modeling principles that enable compliance with regulatory requirements all while preserving the data model's structural integrity.
Tips on how to process the source data to speed up the loading process and model the data to reduce the number of loads and joins without losing any data.
