Project F — Data Reliability & Governance Framework

This repository presents a practical Data Reliability / Data Quality & Observability portfolio.

It demonstrates how business-critical datasets can become:

• trustworthy
• governable
• auditable
• incident-ready

Project F focuses on building the controls and evidence layer that makes data a reusable enterprise asset.

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✅ Core Deliverables (Project F)

Project F is a complete governance framework with concrete reliability artifacts:

Capability	Deliverable File
F1 — Data Lifecycle Governance	01-data-lifecycle.md
F2 — Data Quality Rules Catalog	02-data-quality-rules.md
F3 — Monitoring & Alert Specification	03-monitoring-alert-spec.md
F4 — Incident Response Playbook	04-incident-response-playbook.md
F5 — Data Contracts (Schema Guarantees)	05-data-contracts.md
F6 — Metadata & Lineage Evidence	06-metadata-lineage.md

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🧾 ISO 27001 Evidence Pack (Project D Extension)

This portfolio includes an audit-ready mapping pack aligned with ISO/IEC 27001 Clause 4–10.

📂 Location: case-studies/iso27001-audit-evidence/

This extension demonstrates how reliability controls produce governance evidence for:

• scope & ownership
• risk-based control selection
• operational execution
• monitoring & review
• continuous improvement

(Project D is an evidence extension, not a separate implementation track.)

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🚀 Extension Roadmap (Projects 1–3)

After completing Project F, the framework can be extended in three applied directions:

Figure: Project F governance framework with three applied extension paths (SQL, ELK evidence automation, and business intent preservation case study).

Project 1 — Streaming SQL Reliability

Real-time quality enforcement and decision-readiness validation using SQL.

Project 2 — ELK Observability Evidence + Auto Ticketing

Logs, alert evidence, and minimal incident automation (Alert → Ticket → Runbook).

Project 3 — Business Intent Preservation Case Study

Governance validation across transformations using Marquez + OpenLineage.

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Why This Portfolio Matters

This work is not about collecting tools.

It validates a core enterprise question:

Can business intent, governance controls, and auditability survive across data transformations?

Project F demonstrates how reliable data systems are built through:

• quality controls
• monitoring evidence
• ownership accountability
• incident readiness
• continuous governance improvement

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Author

Pi Hsin Tsai
Focus: Data Reliability / Data Quality & Observability Engineering