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Solutions → Azure Databricks

Azure Databricks Consulting

Design, deploy, and operate Databricks on Azure — integrated with Azure Data Lake Storage, Microsoft Entra ID, Azure networking, and the wider Microsoft data estate.

Microsoft Azure
→
Databricks
Talk to a Databricks ArchitectTalk to a Databricks Architect

Built for these industries

InsuranceHealthcareBanking & Financial ServicesRetailManufacturingAgricultureLogistics

Platform setup

What we set up and integrate

Platform setup

  • Workspace deployment
  • VNet injection & private link
  • Unity Catalog on Azure

Integration

  • Azure Data Lake Storage Gen2
  • Microsoft Entra ID (Azure AD)
  • Azure Data Factory & Synapse

Operations

  • Cost management & budgets
  • Monitoring via Azure Monitor
  • CI/CD with Azure DevOps

Methodology

Our delivery approach

01

Discovery

Understand business goals, current systems, and constraints before proposing anything.

02

Assessment

Inventory databases, tables, pipelines, workloads, dependencies and usage across the estate.

03

Architecture

Design the target Databricks Lakehouse architecture, Unity Catalog, and governance model.

04

Design

Define detailed technical design — data models, pipeline patterns, and platform standards.

05

Migration

Move data, SQL, transformations and pipelines in planned, testable phases.

06

Engineering

Build and re-engineer pipelines, jobs, and integrations on the target platform.

07

Validation

Compare record counts, aggregations, business rules, data quality and performance against source.

08

Optimization

Tune file sizes, partitioning/clustering, SQL, compute, and Delta table configuration.

09

Deployment

Move production traffic with a rollback plan and minimal disruption to downstream consumers.

10

Operate

Hand over with documentation and training, or continue under a managed-services partnership.

Architecture

Target architecture: Azure Databricks

Microsoft Azure
Azure Sources
Tables
Views
Pipelines
Azure-Native Landing Zone & Governance
DatabricksDatabricks Lakehouse
Bronze
Silver
Gold
Unity Catalog · Data Quality · Observability
SQL · BI · AI · GenAI
Applications
Microsoft Azure
Delta Lake
Unity Catalog
Terraform

What to expect

Migration challenges we plan for

1

VNet injection & private networking design

2

Entra ID identity federation & SCIM provisioning

3

Storage account & ADLS Gen2 access patterns

4

Integration with Synapse and Fabric where present

5

Cost allocation across shared Azure subscriptions

Why Karsient

Why Karsient for Azure Databricks

We don't simply move workloads — we redesign the platform for Databricks, combining architecture expertise, data engineering delivery, migration engineering, and AI/MLOps integration under one team.

Architecture expertise

Data engineering

Migration engineering

AI/ML integration

Migration assessment

Is Azure Databricks right for your organization?

Get a technical assessment covering architecture, workloads, migration complexity, dependencies, risks and optimization opportunities.

Get a Free Migration Assessment

FAQ

Common questions

Yes — we set up Microsoft Entra ID federation and SCIM provisioning so existing users and groups carry over directly.

Related

Other Databricks solutions

Snowflake

Snowflake → Databricks

Structured migration of Snowflake workloads to the Databricks Lakehouse.

Learn more →
Talend

Talend → Databricks

Re-platform Talend ETL jobs onto native Databricks pipelines.

Learn more →

Vertica → Databricks

Move Vertica analytical workloads to the Databricks Lakehouse.

Learn more →
AWS

AWS Databricks

Deploy and operate Databricks natively on Amazon Web Services.

Learn more →

Ready when you are

Planning a Azure Databricks migration?

Let's assess your current platform, identify migration risks and design your target Databricks architecture.

Schedule a Migration Assessment