Month Theme / Focus Area Key Actions Tangible Evidence / Deliverables Success Indicators Month 1 Baseline review & planning • Confirm current Level 5 competency scores and priorities• Align with manager/mentor on fellowship expectations• Map your influence across Data Engineering + Analytics disciplines Updated self-assessment & evidence tracker Clear alignment between Data Engineering objectives and … Read more
This proposal outlines a phased approach to broaden the scope of our Data Engineering capability, incorporating Microsoft Fabric as a unified analytics platform and evolving our approach to include foundational elements of AI Engineering. The goal is to create an agile, scalable, and intelligent data platform that supports operational analytics, predictive insights, and innovation. 1. … Read more
A novel about IT, DevOps and Helping your Business Win
🎯 Purpose This framework ensures that values in complex metadata structures (e.g. project earned value, invoice accounting, or employee attributes) are verified for presence even when using incremental loads. It protects against stale data persistence or silent value loss, using metadata-driven auditing. 🧩 Problem Context In many CDM views, values are upserted using procedures like … Read more
🎯 Objective To proactively expire or flag metadata rows that are no longer present in the source data even if their values haven’t changed, avoiding persistence of stale or misleading data. 1. 🏗 Recommended Table Extension Add these optional columns to any table using patch_upsert or put_update: 2. 📥 Staging Input Table – stage.project_values_current Your … Read more
🎯 Core Issue: 🔍 Risks of the Current Approach Scenario Problem Value disappears entirely You keep the last-seen value forever unless a new version overwrites Value moves to another key The old one is retained, and the new one appears as duplicate context Periodic reporting gaps Reporting shows a “stale” value that’s no longer present … Read more
SFIA Reference: RLMT Level 4 Data Architect (Grade 3) Competency Description Participates in Agile planning and stakeholder forums to align architecture with business and platform roadmaps. Learning Outcomes Evidence Requirements Level 4: Suggested Learning Activities Recommended Resources
SFIA Reference: TECH Level 4 Data Architect (Grade 3) Competency Description Contributes to solution review processes and maintains architecture documentation in line with standards. Learning Outcomes Evidence Requirements Level 4: Suggested Learning Activities Recommended Resources
SFIA Reference: METL Level 4/5 Data Architect (Grade 3) Competency Description Collaborates with engineers to embed automation and version control within architectural assets and processes. Learning Outcomes Evidence Requirements Level 4: Suggested Learning Activities Recommended Resources
SFIA Reference: INAN Level 4 Competency Description Designs semantic models and curated datasets to support analytics, dashboards, and self-service BI. Learning Outcomes Evidence Requirements Level 4: Suggested Learning Activities Recommended Resources