Practical guides for learning efficiently, managing complexity, and thinking clearly across three focus areas: Data management, Project management, Software engineering. The goal is to optimize the learning pathway that experience builds on, and to serve as a quick reference when navigating the intersection of technology, constraints, and stakeholder needs.
Note: Content is AI-generated. This repo complements but does not replace official documentation, formal training, hands-on experience, or your organization's own standards. Always verify against authoritative sources.
| Folder | Contents |
|---|---|
| data_management/ | Data concepts, cloud (Fabric, Databricks, ADF), governance, engineering |
| project_management/ | Project management, methodologies, product management, SDLC, reporting |
| software_engineering/ | Software concepts, languages and utilities (Bicep, Git, Terraform) |
| _strategy/ | Shared learning approach, complexity, critical thinking, systems thinking, performance |
| _resources/ | Research trends, interactive diagrams, Excel IT knowledge database |
Each area has its own concepts, terminology, and resources (see the area README). Each also has a strategy/ subfolder with area-specific critical thinking and systems thinking guides.
Four stages that work as both a learning path and a decision lens. See full approach for details.
Orientation Foundations Application Judgment
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What? ──▶ How? ──▶ When & why? ──▶ What if?
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Landscape Concepts Trade-offs Reasoning