Source Discovery
Automatic detection of new data sources
Healthcare & Public Sector
DataOps Platform
A platform for automated data discovery, ingestion, and quality assurance across operational data sources.
DataOps Platform
Built for the Saudi Food & Drug Authority to support a data quality engagement covering the regulator's operational data sources.
The DataOps Platform automates the work of finding, ingesting, validating, and cataloging data across an organization's source systems. It replaces manual data handling with a controlled pipeline, applies quality checks before data enters downstream systems, and gives analysts and operational staff visibility through a dashboard designed for non-technical users. The platform is designed for private deployment under the client's own infrastructure, with no external dependencies, suitable for environments where data sovereignty is required.
What it delivers
Outcomes the platform produces in production.
- Automated data discovery and ingestion across operational sources
- A live data catalog maintained automatically
- Quality checks applied before data is used downstream
- Operational visibility for non-technical users
- Self-hosted deployment with no external dependencies
- Pipeline observability with end-to-end tracing
Platform capabilities
Eight capabilities, end-to-end.
Pipeline Ingestion
Controlled, repeatable data ingestion
Quality Checks
Automated validation and rule enforcement
Data Catalog
Live, self-updating registry of sources
Operational Dashboard
Visibility for non-technical users
Pipeline Observability
End-to-end tracing across stages
Sovereign Deployment
Private, self-hosted, no external calls
Audit Trail
Full lineage and change history
Architecture Python-based data engineering platform · FastAPI backend · pandas and SQLAlchemy for ingestion and quality processing · relational data store extensible to PostgreSQL · designed for private deployment with no external dependencies · delivered using EWP's AI-assisted SDLC.