Start from a governed foundation
Put identity, network boundaries, policy and ownership in place before more data products and teams arrive.
Azure data platforms
Build a governed home
for data in Azure
We design and implement Azure data platforms and data landing zones, bringing Databricks, networking, identity, governance and infrastructure as code together.
Operational data Files & events
Azure data landing zone
IngestBatch & stream
LakehouseDelta Lake
ProcessAzure Databricks
Unity Catalog · identity · private networking
Data productsAnalyticsAI workloads
Give data teams a platform they can build on
A useful data platform is more than a workspace. It needs clear access, private connectivity, repeatable environments and an operating model that works across platform and data teams.
Make environments repeatable
Define platform components and configuration through infrastructure as code so changes can be reviewed and deployed consistently.
Design for the teams using it
Connect platform decisions to how data engineers, analysts and application teams will access, build and operate their workloads.
Azure platform foundation
Identity
Connectivity
Governance
Azure DatabricksWorkspace · catalog · compute
Data products
Analytics
AI workloads
What’s included
Connect Databricks to the Azure platform around it
We shape the platform around your data workloads, existing Azure environment and operating model. The scope can cover a new data landing zone or improvements to a platform already in use.
Data landing zones
Create a structured starting point for data workloads, with subscriptions, environments, ownership and platform responsibilities made explicit.
Azure Databricks foundations
Design workspace, catalog and environment foundations that fit your security, connectivity and delivery requirements.
Identity, networking & security
Bring private connectivity, name resolution, access control, secrets and security boundaries into the platform design.
Infrastructure as code & delivery
Implement repeatable platform components and deployment workflows using version-controlled code and reviewable changes.
Working together
Build the platform around your data workloads
We start with the workloads, teams and constraints you already have, then agree the platform responsibilities and implementation scope.
- 01
Understand the data landscape
Map teams, workloads, sources, environments, security requirements and the Azure platform they need to connect to.
- 02
Agree the platform design
Define the landing zone, Databricks foundations, connectivity, access model and responsibilities before implementation.
- 03
Implement and automate
Build the agreed platform components and delivery workflows alongside your platform and data teams.
- 04
Hand over the platform
Deliver the agreed code, diagrams and operating documentation, and walk through how the platform is maintained.
FAQ
Questions and answers
Can you work with our existing Databricks environment?
Yes. We can review the platform around an existing environment, identify gaps in connectivity, access, governance or automation, and agree practical improvements.
Is this part of an Azure Landing Zone?
It can be. A data landing zone usually builds on shared Azure identity, connectivity and governance. We can design it as part of a broader platform or as an extension of the foundation you already have.
Do you also help with implementation?
Yes. Our work can include hands-on implementation of the Azure and Databricks platform foundations, infrastructure as code and deployment workflows. The exact boundary with data engineering work is agreed in the scope.
Let’s plan the platform behind your data
Tell us what your data teams need to build and what the current platform is making difficult.
Discuss your data platform