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.
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
Data modeling turns data structures, relationships, attributes, and rules into visual and understandable blueprints that describe how the organization uses its data.
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.
Data warehouse automation (DWA) is the process of automating data workflows across the data warehouse lifecycle for increased efficiency, consistency, and value.
Learn why going low-code for your cloud data warehouse can save you time, reduce errors, and increase collaboration. Discover the benefits of low-code development and how it can make building and operating your data warehouse more efficient and cost-effective.
Worried about vendor lock-in when it comes to cloud data warehousing? Learn how to minimize resource lock-in and foster collaboration.
