End-to-End Structured & Unstructured Data Ingestion Using ADF & GenAI
A Practical Blueprint for Automated Enterprise Ingestion
Most organizations can ingest structured data. Unstructured content—invoices, contracts, emails, images—remains trapped.
Template-based parsers break when layouts change. Manual review doesn’t scale. GenAI offers a solution, but it must be productionized with deterministic controls.
This whitepaper, authored by Kaveti Venkateswarlu (Senior Data Engineer, Royal Cyber) , delivers a field-tested framework for unified ingestion using Azure Data Factory and Generative AI.
What You’ll Learn
- Unified Ingestion Architecture: How ADF orchestrates both structured (databases, APIs) and unstructured (PDFs, images, emails) data into a governed Lakehouse (Bronze–Silver–Gold).
- GenAI Extraction with Guardrails: OCR → LLM extraction → JSON validation. Confidence scoring, prompt versioning, PII redaction, and human-in-the-loop workflows.
- Metadata-Driven Automation: Onboard new sources with configuration, not code. Control tables drive reusable framework pipelines at scale.
- CI/CD for ADF: Git integration, pull requests, automated DevOps deployment, and environment-specific parameterization.
- Observability & Data Quality: Freshness SLAs, volume drift, retry policies, quarantine zones, and GenAI-specific metrics (confidence, tokens, cost).
- Security & Compliance: Managed identities, Key Vault, private endpoints, audit logging, and responsible AI safeguards.
- Implementation Roadmap: Phased 4–10 week delivery: Foundation → GenAI Pilot → Scale & Governance. Real-world use case: Invoice–PO matching.
Who Should Read This
- CDOs & Data Leaders – Build ingestion that scales
- Enterprise Architects – Design unified batch + AI ingestion
- Data Engineering Teams – Implement metadata-driven ADF + GenAI patterns
- Governance & Compliance – Establish auditability and quality controls
- IT Operations – Monitor cost, performance, and SLAs
Download the Full Whitepaper
15 pages. Architecture diagrams. Control table schemas. Prompt templates. CI/CD pipeline examples. Production readiness checklist.