Unlock the
potential
of your
data –
sustainably.
Agile Data Engine unlocks the potential of your data to drive business value - in a rapidly changing world.
With the help of our DataOps Management platform, you get faster business value, better quality and lower costs over the data platform lifecycle.
What is Agile Data Engine?
Agile Data Engine is a DataOps Management platform for designing, deploying, operating and managing data products, and managing the whole lifecycle of a data warehouse. It combines data modeling, transformations, continuous delivery and workload orchestration into the same platform.
What is DataOps Management?
DataOps Management is the core philosophy of Agile Data Engine. It is about implementing, operating and managing analytical data products and the data platform, so that productivity is maximized, operation costs are minimized and the investments on data continue to pay back longer.
Our customers have achieved
Head of Data and Analytics, DNA (part of Telenor Group)
trusted by


Our Product
Why agile data engine
With the help of our DataOps Management platform, you get faster business value, better quality and lower costs over the data platform lifecycle.
Coming Up
Join us at gartner data & analytics summit 2023
Gartner Data & Analytics Summit is a prestigious event for business and data leaders, held in London on the 22 - 24th of May. We warmly welcome all attendees to come to our booth 427 to connect with our experts.

Highlights from our blog

Unlocking the Power of DataOps
In today's fast-paced business world, organizations are constantly looking for ways to improve their operations and stay ahead of the competition.

Data Processing in Business Real-Time
Big data is getting bigger and faster. Our customers use data from several sources to guide their business-critical decisions in real-time.

How to build and deploy multiple cloud data warehouses simultaneously?
In a recent project, our customer wanted to test drive multiple cloud databases to understand how they would suit their needs.

How to measure the quality of data?
Data quality issues are present in all data warehouses. But how can you tell if the quality of your data is good?