Client Reporting Data Modernization for an Investment Company
An investment company’s client reporting environment connected investment, fixed-income, equity and trading data to ETL processes, reporting marts and downstream applications built on aging Oracle infrastructure.
Legacy dependencies too risky to migrate all at once.
Legacy Oracle data marts and long-standing pipelines had accumulated significant dependencies, making a direct migration impractical and potentially disruptive to business-critical client reporting. The organization needed a modernization path that preserved continuity.
A phased path to a modern lakehouse architecture.
We led a current-state architecture assessment mapping end-to-end data flows from upstream trading systems through ETL pipelines and reporting marts, and developed a target-state approach using Microsoft Fabric or Databricks.
Resilient pipelines, without disrupting reporting.
We defined phased migration sequencing and a controlled approach for retiring legacy Oracle data marts, strengthened Python-based pipelines with retry, backfill and failure-recovery patterns, and standardized data mart interface contracts.
04 ACCELERATED ROI
A modernization foundation the business can build on.
Concrete outcomes from the engagement, not projections.
CONTINUITY
Preserved business-critical client reporting throughout the modernization effort.
RESILIENCY
Retry, backfill and failure-recovery patterns strengthened pipeline reliability.
RISK
Standardized interface contracts reduced downstream reporting issues.
SCALABILITY
A phased path to Microsoft Fabric or Databricks without a high-risk, all-at-once replacement.
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