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data-governance

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DataTrustEngineering

Data Trust Engineering (DTE) is a vendor-neutral, engineering-first approach to building trusted, Data, Analytics and AI-ready data systems. This repo hosts the Manifesto, Patterns, and the Trust Dashboard MVP.

  • Updated Oct 1, 2025
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Comprehensive data governance pipeline for SSH honeypot logs—covering data profiling, cleansing, quality assurance, encryption, classification, and GDPR/CCPA/HIPAA compliance. Built with Pandas, Pandera, YData Profiling, and cryptography, with simulated Caesar cipher attacks to demonstrate practical data-security techniques.

  • Updated Jun 23, 2025
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End-to-end water data platform built with PySpark, a Medallion Lakehouse, and DataOps principles (CI/CD, Testing). A local-first, containerised data platform (Docker). A governed Medallion Lakehouse with (Data Quality), and DataHub (Governance). Features Medallion architecture, automated data quality, and CI/CD.

  • Updated Nov 15, 2025
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Integration Standards Library — 6-module engagement accelerator for data platform standards (naming, classification, API governance, data quality, metadata/lineage, integration patterns) with browser-based implementation tool, industry profiles, and platform adapters for Microsoft Fabric, Purview, and APIM

  • Updated Feb 7, 2026
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