Abstract

The Rapid Data Architecture (RDA) Approach offers a modern, agile framework for building scalable, cost-effective, and low-maintenance data ecosystems. Designed to accelerate the delivery of data analytics solutions, RDA leverages cloud-native platforms (AWS, GCP, Azure), SaaS-based ETL tools (e.g., Fivetran, Matillion, Airbyte), and modern transformation and orchestration tools (dbt, Prefect) to streamline data integration and pipeline development. By adopting a modular, Medallion-style architecture (bronze-silver-gold layers), the approach supports progressive data refinement and easy scalability. A key differentiator is the integration of AI technologies—including Agentic AI frameworks—which enable real-time anomaly detection, automated system optimization, and predictive analytics [8]. Compared to traditional enterprise architectures, RDA reduces MVP delivery timelines by up to 60%, cuts infrastructure and labor costs by up to 50% and 40% respectively, and enhances system resilience, scalability, and governance. This makes it particularly well-suited for startups and mid-sized businesses aiming for rapid, data-driven innovation without the overhead of complex legacy systems.

Keywords

  • Data Modeling
  • Artificial Intelligence
  • Data Architecture
  • ETL
  • SaaS ETL
  • Datawarehousing

References

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