Automated Enterprise Data Ingestion and Reporting Pipeline

CONCEPT

This project focuses on designing and implementing a fully automated, scalable data ingestion pipeline that reliably processes data from multiple upstream systems and delivers trusted, analytics‑ready datasets.

The primary objectives were:
1] Automate ingestion from multiple source systems with minimal manual effort.
2] Enforce robust data quality checks and proactive issue notifications.
3] Provide end‑to‑end visibility of ingestion status to engineering, product, and business teams.

DATA

Data is sourced from multiple internal and external providers in varying formats and delivery schedules. Incoming datasets are securely landed on a centralised SFTP server and standardised prior to ingestion.

The solution supports incremental and full loads while maintaining historical traceability and auditability across all ingestion cycles.

APPROACH

The pipeline is orchestrated end‑to‑end using Azure Data Factory (ADF), coordinating data movement, validation, processing, and reporting workflows.

Automated data quality checks are applied early in the pipeline to validate schema consistency, completeness, and business rules. If issues are detected, automated email notifications are triggered to source data providers with detailed error context.

Upon successful validation, data is processed and stored using a medallion architecture (Bronze, Silver, and Gold layers) to ensure a clear separation between raw, curated, and analytics‑ready data.

TECHNOLOGIES USED

The platform leverages a modern cloud‑native data stack:

• Orchestration and Scheduling
  • Azure Data Factory (ADF)
  • Power Automate
• Data Processing and Storage
  • Azure Databricks
  • Snowflake Data Warehouse
  • Secure SFTP
• Analytics and Reporting
  • Power BI (Datasets, Dataflows, Reports)
  • Ingestion Status and Audit Dashboards

OUTCOME

The solution significantly improved data reliability, reduced ingestion failures, and eliminated manual monitoring. Real‑time Power BI dashboards provide full transparency into pipeline health, while automated notifications keep engineering and product teams informed of ingestion status and downstream impacts.

View Architecture

End‑to‑End Architecture