How We Reduced Operational Costs by 51% with a Governed Databricks Lakehouse
Our client wanted to transform how operational and analytical data were accessed across the organization. Key business data, including operational records...
At a Glance
Our client wanted to transform how operational and analytical data were accessed across the organization. Key business data, including operational records from Oracle on AWS RDS, was siloed, manually curated, and inconsistent across reporting teams. They needed a centralized, governed analytics platform that would accelerate insight delivery while ensuring future expansion into additional datasets and use cases.
Challenge
Fragmented data and slow reporting cycles without centralized analytics
The organization relied on disparate systems where Oracle data was manually extracted and stitched together for reporting. This limited visibility, slowed delivery of operational analytics, and introduced inconsistencies. They needed:
- A centralized Lakehouse foundation with bronze, silver, and gold data layers
- Automated ingestion for both historical and incremental loading
- End-to-end governance with access controls and lineage
- Early validation of business reporting requirements
- A rapid implementation timeline to accelerate adoption
Solution
Unified access and governed analytics on Databricks Lakehouse
We deployed a production-ready Lakehouse foundation on AWS, built to scale business insights and eliminate reporting inefficiencies.
- Databricks Lakehouse Architecture: Implemented a structured bronze–silver–gold medallion model to unify Oracle RDS data into analytics-ready form.
- Automated Ingestion & Data Quality Assurance: Built ingestion pipelines supporting both full backfill and incremental updates, with quality checks and auditability.
- Governed Access with Unity Catalog: Enforced security, lineage, and role-based controls to ensure trusted data consumption across teams.
- Analytics Enablement & Reporting Readiness: Delivered curated gold-layer datasets and a working BI/AI dashboard to validate usage feasibility from day one.
Benefits
Accelerating insights and operational efficiency with 72% better decision-making
Centralizing Oracle data into a governed Lakehouse enabled business users to move from manual processing to trusted, self-service analytics:
- Consistent Enterprise Reporting: Curated and governed datasets improved reporting accuracy and cross-team collaboration, contributing to 72% improved decision-making through more reliable operational insights.
- Shorter Time to Insight: Automated ingestion pipelines and structured data layers reduced manual preparation and reporting delays, resulting in 48% enhanced operational efficiency across analytics workflows.
- Built-for-Growth Architecture: Easily expands to new datasets, use cases, and customers with minimal rework
Ready to accelerate analytics with Databricks on AWS?
As a trusted Databricks partner, we help organizations build scalable Databricks Lakehouse platforms on AWS that unify data, automate pipelines, and enable trusted analytics. Our experts at zeb design architectures that accelerate insights while ensuring governance and long-term scalability.
Connect with our team to explore how a modern Lakehouse can transform your enterprise data into actionable intelligence.
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