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Workshop
We’ve seen it all. Let us share our customers’ stories of both failed and successful cloud journeys. We will reveal the recipe and a few magic ingredients for building a system that stands the test of time, and thrives despite the constant changes.
Agile Data Engine’s metadata approach to data modeling and workload orchestration means that everyone in the DataOps teams understands how the solution does what it does. So even if the team members change over time, we can be sure that any change to the platform will not disrupt the daily work of our data consumers.
Head of Data Platforms, Kesko
We can develop at an entirely different rate. In practice, the improvement is in multiple percentages. We previously saw development cycle turnarounds in weeks – now they happen in days.
Head of Data and Analytics, DNA (part of Telenor Group)
Agile Data Engine guaranteed a very fast start to the project: in a couple of weeks, the solution was already creating value to the business.
Head of Business Intelligence & Analytics, Matkahuolto
Join our growing community of data enthusiasts.
DataOps and data warehousing in general are ever-evolving. Head over to our blog to stay up-to-date on how you can make yours more resilient and future-proof as possible!
Understand the challenges of the Modern Data Stack: high costs, complex maintenance, and integration issues, compared with the ease of all-in-one platforms
Learn the key benefits of Agile Data Engine's Databricks Built On Partner status for the customers and end users.
Agile Data Engine is the best choice for addressing Data Vault issues in Databricks, as shown in the German Data Vault User Group's Willibald Challenge.