Databricks Partner
Databricks Consulting & Implementation Services
Move your enterprise data onto a lakehouse you can govern, cost-control, and build AI on. As an official Databricks partner, GAMC designs, migrates, and operates Databricks environments for energy, manufacturing, and high-tech enterprises — backed by 15+ years as a certified SAP partner and deep knowledge of the ERP and HCM systems your data actually comes from.
Databricks PartnerCertified SAP Partner15+ years enterprise delivery
1. Why enterprises bring us in
Most Databricks programs go over budget not because compute is expensive, but because nobody can attribute it. We instrument cost from the first workspace: cluster policies, tagging standards, job-level chargeback, and serverless vs. classic decisions made deliberately rather than by default. You get a monthly view of spend by business unit, pipeline, and workload — and the levers to change it. The result is a platform finance teams can approve and engineering teams can keep using, instead of a bill that arrives as a surprise in month four.
2. Databricks services
Databricks Assessment & Architecture
Evaluate your current data estate, define the target lakehouse architecture, and produce a costed, sequenced roadmap.
Migration to Databricks
Move data warehouses, SAP BW, on-prem Hadoop, and legacy ETL onto Delta Lake in validated waves.
SAP & ERP Data Integration
Extract, model, and govern SAP ECC, S/4HANA, and SuccessFactors data in the lakehouse without breaking source-system contracts.
Data Engineering & Pipelines
Build reliable batch and streaming pipelines with Delta Live Tables, orchestration, testing, and observability.
Governance with Unity Catalog
Implement catalog structure, access control, lineage, and audit to meet internal and regulatory requirements.
Cost Optimization & FinOps
Right-size compute, apply cluster policies, and establish chargeback so platform spend stays attributable and predictable.
BI & Analytics Enablement
Deliver semantic models and dashboards on Databricks SQL, and connect the tools your business already uses.
Applied AI & ML
Build and operationalize machine learning and GenAI use cases on governed enterprise data, with MLOps practices that survive handover.
3. How we work
01 — Assessment & Architecture Design
2–4 weeksWe map your current data estate, workloads, and consumers; identify what is worth migrating and what should be retired; and produce a target architecture with a cost model and a wave plan. Deliverable: an architecture decision record and a sequenced roadmap you can budget against.
02 — Pilot / MVP
6–10 weeksOne meaningful workload, taken end to end — ingestion, modeling, governance, and a consumer-facing output. The pilot proves the architecture on your real data and establishes the engineering standards every later wave follows.
03 — Migration Waves
6–12 weeks per waveWorkloads move in prioritized groups. Legacy business logic is documented and rebuilt; pipelines are tested against defined data quality expectations; each wave ships with its own runbook.
04 — Parallel-Run Validation
2–4 weeksOld and new run side by side. We reconcile outputs at the record and aggregate level, resolve discrepancies with the business owners, and only then recommend cutover.
05 — Enterprise Rollout
6–18+ monthsRemaining domains onboard onto the proven pattern, with platform standards, self-service enablement, and training so your teams can build without us in the room.
06 — Optimize & Scale
OngoingOngoing cost tuning, performance work, governance review, and extension into AI workloads as the platform matures.
4. Why GAMC
- Official Databricks Partner
- platform expertise validated through the Databricks partner program
- Certified SAP Partner
- 15+ years delivering enterprise systems
- 20+ SAP consultants
- ERP, HCM, and business-process depth
- Energy, manufacturing, high tech
- our core industries
GAMC did not arrive at data engineering from the outside. We came to it through 15+ years of implementing and maintaining the systems that generate enterprise data — SAP ERP, SuccessFactors HCM, and the operational platforms around them. As an official Databricks partner, we pair that source-system fluency with platform expertise validated through the Databricks partner program, plus access to partner enablement, training, and technical resources. The practical effect: we start a program already understanding your cost centers, your production hierarchy, and your HR data model — fewer discovery cycles, fewer rebuilt data models, and a lakehouse the business trusts because the numbers reconcile.
5. Industry focus
Energy & Power
Consolidate SCADA, metering, asset, and ERP data into a governed lakehouse; enable predictive maintenance, generation and load analytics, and regulatory reporting on a single source of truth.
Manufacturing
Unify MES, quality, supply chain, and SAP data to support yield analysis, demand forecasting, and traceability across plants and product lines.
High Tech
Bring product telemetry, engineering, and commercial data together to shorten analytics cycles and support ML-driven product and operational decisions.
6. Frequently asked questions
Let's scope your Databricks program
Tell us about your current data estate and what you need it to do. We'll come back with an honest assessment of scope, sequence, and cost — before you commit to a platform decision.
Talk to our Databricks team