Databricks Consulting & Data Platform Services
Databricks Partner
DCS ITECH helps organisations design, migrate and modernise enterprise data platforms using Databricks, combining data architecture, data modelling, engineering, governance and migration expertise.
Databricks Services
Lakehouse Architecture
- Design and implement Databricks lakehouse architectures using Medallion patterns and Delta Lake to support scalable, governed enterprise data platforms.
Unity Catalog & Governance
- Design and implement Databricks Unity Catalog, access controls and governance policies to centralise permissions, lineage and data protection across your lakehouse.
Data Engineering & Ingestion
- Design and optimise Databricks data pipelines for batch and streaming ingestion, combining Spark, Structured Streaming and ETL best practices to deliver reliable, high-quality data flows.
Migration & Modernisation
- Plan and deliver migrations from legacy data platforms to Databricks, modernising architecture, workloads and data pipelines while managing risk and minimising disruption.
Data Modelling
- Design and implement dimensional and canonical data models on Databricks to support analytics, reporting and governed self-service across the lakehouse.
Analytics & AI Enablement
- Enable advanced analytics and AI on Databricks, combining SQL, ML and real-time insights to support decision-making, reporting and data-driven innovation.
Our Databricks Delivery Approach
DCS ITECH follows a structured Databricks delivery approach that aligns architecture, governance and migration activities so you can modernise with confidence rather than treating Databricks as a one-off implementation.
Our architecture-led approach brings together data engineering, enterprise data modelling, governance and migration assurance to establish a trusted and scalable Databricks platform.
How We Deliver Databricks Projects
Discover & Architect
Understand the existing estate and define the target Databricks architecture.
Build & Govern
Establish the platform, ingestion patterns, data models and Unity Catalog governance.
Migrate & Validate
Move priority datasets and workloads with structured reconciliation and validation.
Deploy & Optimise
Move approved workloads into production and continue improving performance, governance and platform utilisation.
Data Architecture & Modelling for Databricks
We typically structure Databricks lakehouse environments using a Bronze, Silver and Gold pattern:
Bronze — source-aligned/raw data captured from operational systems and external feeds with minimal transformation.
Silver — cleansed, integrated and conformed data, aligned across domains and ready for consistent analytics.
Gold — business-ready models and data products, designed around decision-making, reporting and self-service.
DCS ITECH connects this lakehouse pattern with enterprise data modelling, dimensional models, domain models and data products, ensuring that Bronze, Silver and Gold layers are grounded in a clear enterprise data model rather than isolated pipelines.
Learn more about our modelling approach on the Enterprise Data Modelling service page.
Unity Catalog & Data Governance
Databricks Governance & Unity Catalog
DCS ITECH designs Databricks governance around Unity Catalog, metadata and access control so that data products, models and pipelines are managed consistently across domains. We align catalog structures, permissions and policies with your enterprise data model, helping you maintain clear ownership, lineage and compliance as the lakehouse grows.
Metadata management | Data lineage | Access control | Classification | Data quality | Ownership | Governance standards
Legacy Data Migration to Databricks
DCS ITECH helps organisations move from legacy platforms such as Oracle, SQL Server, file-based warehouses and legacy ETL tools into Databricks. Our approach combines assessment, dependency analysis, ingestion, transformation, reconciliation and controlled cutover so that critical datasets are migrated safely and transparently.
We align Databricks migration work with your wider Data Modernisation strategy, ensuring that new lakehouse platforms, data models and pipelines are part of a coherent enterprise roadmap rather than isolated technical projects.
Data Migration & Modernisation
Migration Assurance & Validation
Databricks Migration Assurance
DCS ITECH applies structured reconciliation and validation to help demonstrate that migrated data is complete, accurate and ready for business use. Our approach goes beyond simple row counts to test the integrity of data across multiple dimensions.
We validate record counts, schemas, data types, null handling, keys, aggregates, business totals and exceptions so that stakeholders can trust the new Databricks environment and sign off migrations with confidence.
Business Outcomes
Reduced Platform Risk
Structured architecture, migration and validation.
Improved Data Performance
Modern ingestion and transformation patterns.
Stronger Data Governance
Metadata, lineage, access and quality controls.
Optimised Platform Costs
Architecture and workload optimisation.
Trusted Data for Analytics & AI
Governed, business-ready data.
Databricks Partner
Enterprise Data Architecture Expertise
We design Databricks environments that are grounded in robust enterprise data architecture rather than isolated workloads.
Specialist Data Modelling Capability
We bring deep data modelling expertise so the structures you move onto Databricks are coherent, governed and analytics‑ready.
Migration & Modernisation Experience
We plan and deliver migrations from legacy platforms into Databricks as part of wider data modernisation, not just platform replacement.
Governance & Migration Assurance
We combine Unity Catalog governance with structured reconciliation and validation so you can trust the data and models running on Databricks.
Why DCS ITECH + Databricks
Plan Your Databricks Modernisation
Whether you're assessing an existing data estate, designing a new Databricks architecture or migrating legacy workloads, talk to DCS ITECH about your requirements.
Our Databricks Delivery Approach
Tangible Efficiency and Performance Gains Through Strategic Databricks Modernisation
Scalable Data Architecture
Governed Data Platforms
Design Databricks environments that support growing data volumes, workloads and enterprise requirements.
Establish governance, data quality and access controls to support trusted and well-managed enterprise data.
Performance & Cost Optimisation
Optimise workloads, architecture and platform utilisation to improve performance and manage operating costs.