| 6 months for end-to-end modernization | 2x performance improvement | Powering AI & predictive analytics with Databricks Lakehouse | Business context connected across enterprise domains |
What Drove the Move to Databricks
A Fortune 200 global power technology leader operates a mission-critical reliability ecosystem that underpins decision-making across supply chain, manufacturing, and service operations. As workloads grew in volume and complexity, the company’s on-premises data estate, built on legacy platforms like Oracle Exadata, Informatica, ODI, and AppWorx, became a massive bottleneck.
Multiple pressures converged, making modernization non-negotiable:
- Impending Oracle Exadata license expiry created immediate migration urgency
- Escalating data warehouse and ETL overhead costs across eroded IT budgets
- On-premises infrastructure limitations restricted scalability, innovation, and responsiveness
- Rigid ETL and orchestration frameworks blocked adoption of advanced analytics and AI
- Fragmented data systems delayed insights and slowed business responsiveness
- Fragmented domain data prevented 360-degree visibility across products, parts, materials, suppliers, plants, assets, and service operations.
The organization needed to quickly move to a future-ready platform that would unlock AI and advanced analytics use cases—without disrupting ongoing operations.
A snapshot of the client’s current and future technology stack
Unified EDW, ETL, and orchestration on Azure Databricks, replacing a fragmented legacy estate with a single, scalable, AI-ready Lakehouse.
Powering a connected, AI-ready data foundation on Azure Databricks
Partnering with Databricks and Impetus enabled the client to transition from a maintenance-heavy, on-premises data estate to a scalable industrial digital thread—delivering measurable performance improvements, reducing costs, and elevating business outcomes.
Business benefits:
Estate consolidation: Replaced multiple legacy and niche tools with a single Azure Databricks platform, simplifying the technology landscape and lowering total cost of ownership.
Massive cost savings: Sunset Oracle Exadata, Informatica, ODI, and AppWorx licenses, decommissioned on-prem infrastructure, and eliminated escalating overhead costs.
2x performance improvement: Delivered a significant performance uplift on Databricks, enabling faster, smarter reliability operations across the enterprise.
45% faster batch processing: Reduced end-to-end execution window from 4.5 hours to 2.5 hours, accelerating data availability for analytics and reporting teams.
Production continuity: Modernized mission-critical workloads without disrupting core service processes, while preserving 100% business logic and meeting operational SLAs.
AI-readiness: Established a future-proof Lakehouse platform powering AI innovation and predictive analytics across supply chain, manufacturing, and service operations.
Governed, context-rich data foundation: Created a lineage-aware foundation for forecasting, quality intelligence, anomaly detection, manufacturing optimization, and agentic AI governance.
Reduced technical debt: Eliminated redundant workflows and orchestration jobs, simplifying the estate and enabling engineers to focus on high-value tasks.
Retired Oracle and Informatica in just 6 months, delivering 2x performance and 45% faster batch processing
Enabling fast, risk-free modernization with Impetus & Databricks
Impetus’ ontology-led modernization solution, LeapLogic™ Suite accelerated the end-to-end transformation journey by automatically converting Oracle Exadata SQL, Informatica mappings, and ODI workflows into Databricks-native equivalents. This dramatically reduced manual effort and compressed the overall migration timeline. Rather than a mechanical lift-and-shift, modernization involved strategic re-platforming, with every workload assessed, optimized, and validated for cloud-native performance and governance.
Key solution highlights:
- Intelligent inventory assessment: Identified legacy jobs along with dependencies and provided actionable recommendations to optimize complex ingestion pipelines on Databricks.
- Accelerated migration at enterprise-scale: Auto-converted 395+ Oracle procedures, 545+ tables, 170+ Informatica workflows, 90+ AppWorx chains and multiple ODI jobs to Databricks-native equivalents.
- Unified Delta Lake foundation: Replaced Oracle Exadata with a scalable, ACID-compliant storage layer, consolidating all migrated EDW objects and materialized views into a single trusted source.
- Cloud-native orchestration: Redesigned master orchestration workflows for Databricks, enabling end-to-end execution of all migrated jobs in a single run.
- Cost-efficient compute: Leveraged Databricks Cluster Pools to streamline DBU consumption across development, testing, and production, eliminating resource wastage.
- Enterprise-grade governance: Established centralized security, access control, and lineage across all migrated workloads on Unity Catalog.
- Automated CI/CD pipelines: Integrated Databricks Asset Bundles seamlessly with the existing DevOps framework to enable faster, automated releases.
- Industrial digital thread: Established connected business context across products, parts, materials, suppliers, plants, assets, and service operations for holistic intelligence.
- Reliability intelligence: Preserved equipment, maintenance, failure and service logic to support predictive maintenance, reliability analysis, and more proactive service operations.
- Operational semantics: Harmonized KPIs, calculations and business rules across domains, reducing inconsistent interpretation between enterprise teams.
From a siloed legacy estate to a future-ready architecture on Azure Databricks
Modernization empowered the power solutions leader with a unified platform that was optimized, governed, and production-ready from day one. The transition equipped them with the new-age data foundation needed to accelerate supply chain decisions, improve manufacturing efficiency, drive agentic AI innovation, and scale business growth.
