.png?width=350&height=65&name=Skandia%20for%20website%20%20(340%20x%2065%20px).png)
.png?width=50&height=65&name=S-group%20logos%20for%20website%20%20(50%20x%2065%20px).png)
Explore how Agile Data Engine powers data teams
- 01Simplified architecture, less time on maintenance.
- 02Built-in team productivity, more value for business.
- 03Governed flexibility.
Scale your cloud data warehouse with confidence
Agile Data Engine is the all-in-one automation platform for modern cloud data warehouses.
Built for scale, designed for speed.
All-in-one automation platform for modern cloud data warehouses
Agile Data Engine is a low-code DataOps platform for designing, deploying and operating cloud data warehouses. It also provides you the ability to manage data platform implementation work.
Goodbye heroes. Hello productivity at scale.
Agile Data Engine redefines how you build and run data warehouses. Make your team productive in solving business needs, instead of becoming indispensable heroes.
Control your delivery flow. Control your success.
True continuous delivery is the engine behind a successful data platform. By enabling faster, more reliable deployments, it enhances both the quality and stability of your data pipelines.
Cut data operations costs. Optimize TCO.
With Agile Data Engine your team can focus on delivering value without the maintenance overhead and continuous troubleshooting. You achieve more value with the same team.
The One Platform
Where data comes together
Up to 73% of enterprise data goes unused—not from lack of value, but lack of cohesion. Agile Data Engine unifies data operations across the entire data production line. Increase your data quality and build a resilient data platform that you can trust.
For businesses scaling in a changing environment
Built for data teams that want to master continuous change and growth.
Learn and connect
January 24, 2025Downsides of the Modern Data Stack
January 13, 2025Agile Data Lakehouses with Databricks and ADE
December 23, 2024Best practice for addressing Data Vault challenges in Databricks