Building a Scalable, Cost-Optimised & Resilient Data Platform
Sector: E-commerce & Retail
Challenge: A fast-growing online retailer faced fragmented data systems, ballooning cloud costs, and unreliable analytics that hindered decision-making.
Solution: RCG engineered a modern cloud-native data platform using open-source and AWS services (NiFi, Kafka, Iceberg, dbt, Airflow, Trino). The architecture unified batch and streaming data into a governed lakehouse, achieving 99.9% uptime and near real-time analytics within a $500/month budget.
Impact: Reduced infrastructure costs by ~30%, accelerated data refresh from days to minutes, and established a single, trusted source of truth for all business units. The platform is resilient, auto-scaling, and future-proof, empowering the client's teams to self-serve insights with complete governance and compliance.
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Accelerating Data Freshness with Incremental Loading in Financial Analytics
Sector: Financial Services
Challenge: A global trading firm's full-load ETL pipeline caused 3-hour delays in post-market dashboards and excessive compute waste.
Solution: RCG redesigned the data warehouse into an incremental, event-driven ingestion pipeline using AWS DMS, S3, Redshift Spectrum, Glue, EventBridge, CodeBuild, and dbt incremental models. Each run now merges only new or changed data instead of rebuilding tables from scratch.
Impact: ETL runtime fell from 3 hours to under 45 minutes (4× faster), compute costs dropped 40–50%, and dashboards update hourly instead of daily. The new design improved scalability, reliability, and compliance, demonstrating how incremental engineering transforms latency-bound analytics into real-time intelligence.
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Establishing Data Governance & Policy Maturity for a Nonprofit
Sector: Nonprofit / Social Impact
Challenge: A mission-driven nonprofit lacked governance structure—no data catalog, unclear ownership, and inconsistent definitions led to mistrust and compliance risk.
Solution: RCG designed a comprehensive data governance framework combining strategy, policy, and technology. We established stewardship roles, created a business glossary, automated data-quality tests (dbt + Great Expectations), and deployed a unified metadata and lineage catalog (OpenMetadata/Amundsen). Policies were codified into an enforceable "governance-as-code" layer integrated with analytics systems.
Impact: Governance maturity increased drastically: data trust rose 90%, compliance incidents halved, and policy enforcement became automated. The nonprofit now operates a transparent, auditable, and self-service governance portal that underpins all reporting and funding decisions.
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