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    Databricks Consulting PartnerDatabricks Consulting Partner

    Databricks consulting from a certified <Databricks Consulting Partner>

    Lakehouse architecture, Unity Catalog governance, Delta Live Tables, MLflow and migrations to Databricks, delivered by senior engineers, with native integration into Microsoft Fabric, Azure and Power BI.

    Discuss Your Databricks Strategy

    What We Build

    Enterprise-grade Databricks capabilities, expertly delivered.

    Lakehouse Architecture

    Unify data for analytics and AI with a scalable, governed lakehouse foundation.

    Delta Lake & Delta Live Tables

    Reliable, ACID transactions and declarative pipelines for streaming and batch workloads.

    MLflow & Model Lifecycle Management

    Track experiments, register models, and streamline deployment with governance.

    Real-Time / Streaming Pipelines

    Build event-driven pipelines to deliver fresh data to downstream analytics and apps.

    Advanced ETL/ELT Workloads

    Optimize transformations with Spark, auto-scaling clusters, and cost-aware execution.

    Analytics & Governance on the Lakehouse

    Secure access, data quality, and domain governance for enterprise-grade insights.

    Reference Architecture on Databricks

    A modern, governed lakehouse at a glance.

    Ingest

    Stream / Batch

    Bronze / Silver / Gold

    Delta Lake

    ML / Analytics

    Spark / MLflow

    Serving

    BI / Apps

    Governance / Observability

    Unity Catalog

    • Medallion design improves reliability and reduces time-to-insight.
    • Model lifecycle with MLflow standardizes experimentation and deployment.
    • Cluster and job governance enable performance, security, and cost control.

    Selected Results

    Real outcomes from Databricks-powered transformations.

    CUF case study
    Healthcare

    CUF

    +4% Surgery Conversion Rate

    View Case Study
    Kaseya case study
    Technology

    Kaseya

    Automated Global Consolidation

    View Case Study
    Salvador Caetano case study
    Automotive

    Salvador Caetano

    Real-time Market Intelligence

    View Case Study

    Our Databricks consulting services

    End-to-end delivery on Databricks, from first Lakehouse to managed operations, with the Microsoft / Power BI integration that most Databricks teams need but few partners deliver at senior level.

    • Lakehouse architecture on Databricks (Delta, Bronze/Silver/Gold, medallion design).
    • Unity Catalog & governance, fine-grained access, lineage, masking and cross-workspace federation.
    • Delta Live Tables & Workflows, declarative, observable, production-grade pipelines.
    • Databricks SQL & BI enablement, Partner Connect to Power BI, Direct Lake over Delta.
    • ML & AI on Databricks, MLflow lifecycle, Mosaic AI, feature store, model serving.
    • Migration to Databricks, Synapse, Hadoop, SQL Server and on-prem Spark to the Lakehouse.
    • FinOps & operations, cluster policies, job tuning, cost guardrails and managed Databricks ops.

    Databricks consulting, frequently asked

    A Databricks Consulting Partner is a firm certified by Databricks to design, deliver and operate Lakehouse, Unity Catalog and ML workloads in production. DevScope holds the partnership alongside our Microsoft Solutions Partner credentials, which means we can deliver Databricks end-to-end and integrate it natively with Azure, Microsoft Fabric and Power BI.

    Both are valid Lakehouse platforms. Microsoft Fabric is a strong fit for Microsoft-centric estates with heavy Power BI usage, simpler analytics workloads and teams already living in the Microsoft 365 / Azure ecosystem. Databricks is the right call for mixed BI + ML + streaming at scale, demanding data engineering and ML lifecycles, or multi-cloud requirements. As a dual partner, our recommendation is based on your workloads, team and roadmap, not vendor incentives.

    A focused first delivery (one business domain, governed Lakehouse with Bronze/Silver/Gold, Unity Catalog and a first BI use case) typically ships in 8–12 weeks. Enterprise-wide rollouts with multi-source ingestion, ML workloads and full governance usually run 4–9 months, delivered in waves.

    Yes. We run a 2–3 week assessment of your current estate (workloads, dependencies, security, cost), then deliver a phased migration with parallel-run validation. Typical paths include Synapse Dedicated Pools → Databricks SQL, on-prem Hadoop → Lakehouse, and SQL Server warehouses → Delta on Databricks.

    Yes, a senior pod operating your Databricks workspace end-to-end: pipelines, incidents, change requests, cluster policies, cost optimisation and Unity Catalog governance, on a monthly retainer.

    Ready to accelerate your <Databricks> lakehouse?

    Let's design a unified, scalable lakehouse tailored to your analytics and AI needs.

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