Seamlessly integrate structured and unstructured data from 6+ sources (databases, APIs, files, cloud storage) with automated retries, validation, and schema enforcement, ensuring zero data loss and continuous ingestion for 24/7 operations.
Normalize raw data into audit-friendly staging tables with full lineage tracking and change data capture (CDC). Supports reproducible processing and instant rollback for any pipeline errors.
Build incremental, testable, and production-ready dbt models for analytics. Includes snapshots, macros, and complex joins to enable near real-time reporting and insight generation at scale.
Implement 50+ automated tests for completeness, accuracy, and freshness. Integrates real-time alerts and dashboards for stakeholders, reducing data errors by 98%.
DAG-based orchestration ensures dependency management, retries, SLA monitoring, and cost optimization across pipelines. Guarantees 99.9% uptime for critical analytics workloads.
ELT Pipeline Architecture
Data Quality Dashboard