Data available in one place
Relevant data from different sources is brought together in a managed environment.
Databricks implementation
Build a manageable data platform on Databricks around concrete data and AI applications.
A Databricks environment delivers value only when data sources, governance and applications are set up to work together. A Databricks implementation brings relevant data and workloads together within a chosen architecture.
From an isolated possibility to a useful application
An application only becomes meaningful when it fits a specific task and the information available for it.
DSL is a Databricks Partner and sets up the environment around practical use cases. That’s why we define in advance what the solution should and should not do, how its output will be checked and who remains responsible.
What it delivers
A foundation for BI and AI
The same reliable data can be used for reporting and new applications.
Expand in a controlled way
You can add new sources and use cases step by step.
Our approach
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Choose a use case
We start with a specific information need and relevant data sources.
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Define the architecture
We design a setup that fits your organisation and existing environment.
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Make data accessible
We bring the selected sources together and set up data processing and quality measures.
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Deliver the first application
We make data useful in a dashboard, an analysis or an AI use case.
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Organise management and growth
We monitor the foundation and add new sources step by step.
Aligned with your organisation
This service is relevant for organisations that want to organise data engineering, analytics and AI centrally. The exact setup depends on the process, the data available and the risks of the application.
We therefore start with a clearly defined application and only expand it when the initial setup works in practice.
Other solutions
One data platform for fragmented sourcesBring data from separate systems together in one place, where everyone sees the same figures.
Dashboard for day-to-day operationsSee how things stand on one screen, without having to build reports first.
Predicting when maintenance is neededPlan maintenance based on what the data says, not on a fixed schedule.
Frequently asked questions
This service addresses the following challenge: a Databricks implementation brings relevant data and workloads together within a chosen architecture. How it works in practice depends on the process and the available data.
The service may be relevant to organisations that want to manage data engineering, analytics and AI centrally. A specific need and usable information matter more than the size of the organisation.
That depends on the intended application. We start with the question that needs answering, then determine which data or sources are necessary and suitable.
No. For fixed, predictable tasks, conventional automation may be enough. We choose the simplest approach that addresses the challenge effectively and add complexity only when needed.
We define the scope of the application, validate the results with users and put appropriate checks in place. Once it is in use, we monitor how it performs and adjust the solution when the data, its use or the context changes.
Discover what a Databricks implementation could mean for your organisation
Want to explore where it makes sense to start with a Databricks implementation? Together, we’ll map out the challenge, the available information and the constraints.