Taxonomy Distribution Report

Overview

• Total Concepts: 200
• Number of Taxonomies: 11
• Average Concepts per Taxonomy: 18.2

Distribution Summary

Category	TaxonomyID	Count	Percentage	Status
System Architecture	SARCH	25	12.5%	✅
Databases and Data	DBASE	25	12.5%	✅
Analytics and Data Science	ANLYT	25	12.5%	✅
Product Management Foundations	PMFND	20	10.0%	✅
APIs and Integrations	APINT	20	10.0%	✅
SDLC and Agile	AGILE	20	10.0%	✅
AI Tools and Strategy	AITOL	20	10.0%	✅
Quality and Testing	QATST	15	7.5%	✅
Software Development	SWDEV	11	5.5%	✅
Career and Leadership	CARER	10	5.0%	✅
Technical Documentation	TCDOC	9	4.5%	✅

Visual Distribution

SARCH  ██████  25 ( 12.5%)
DBASE  ██████  25 ( 12.5%)
ANLYT  ██████  25 ( 12.5%)
PMFND  █████  20 ( 10.0%)
APINT  █████  20 ( 10.0%)
AGILE  █████  20 ( 10.0%)
AITOL  █████  20 ( 10.0%)
QATST  ███  15 (  7.5%)
SWDEV  ██  11 (  5.5%)
CARER  ██  10 (  5.0%)
TCDOC  ██   9 (  4.5%)

Balance Analysis

✅ No Over-Represented Categories

All categories are under the 30% threshold. Good balance!

Category Details

System Architecture (SARCH)

Count: 25 concepts (12.5%)

Concepts:

• 1. System Architecture
• 1. Software Components
• 1. Client-Server Model
• 1. Monolithic Architecture
• 1. Microservices
• 1. Service-Oriented Architecture
• 1. Distributed Systems
• 1. Cloud Computing
• 1. Infrastructure as a Service
• 1. Platform as a Service
• 1. Software as a Service
• 1. Serverless Computing
• 1. Containerization
• 1. Docker Overview
• 1. Kubernetes Overview
• ...and 10 more

Databases and Data (DBASE)

Count: 25 concepts (12.5%)

Concepts:

• 1. Database Fundamentals
• 1. Relational Databases
• 1. SQL Basics
• 1. SQL Queries
• 1. SQL Joins
• 1. Data Tables
• 1. Primary Keys
• 1. Foreign Keys
• 1. Database Schema
• 1. Data Normalization
• 1. NoSQL Databases
• 1. Document Databases
• 1. Key-Value Stores
• 1. Data Warehouse
• 1. Data Lake
• ...and 10 more

Analytics and Data Science (ANLYT)

Count: 25 concepts (12.5%)

Concepts:

• 1. Data-Driven Decisions
• 1. Product Analytics
• 1. Web Analytics
• 1. User Behavior Tracking
• 1. Funnel Analysis
• 1. Cohort Analysis
• 1. A/B Testing
• 1. Statistical Significance
• 1. Conversion Rate
• 1. Retention Metrics
• 1. Churn Rate
• 1. Dashboard Design
• 1. Data Visualization
• 1. Python for Data Analysis
• 1. Data Pipelines
• ...and 10 more

Product Management Foundations (PMFND)

Count: 20 concepts (10.0%)

Concepts:

• 1. Product Management
• 1. Technical Product Manager
• 1. Product Lifecycle
• 1. Software Product
• 1. Technical Literacy
• 1. Engineering Mindset
• 1. Product Strategy
• 1. Business Requirements
• 1. User Needs
• 1. Stakeholder Management
• 1. Cross-Functional Teams
• 1. Product Vision
• 1. Product Roadmap
• 1. Value Proposition
• 1. Market Research
• ...and 5 more

APIs and Integrations (APINT)

Count: 20 concepts (10.0%)

Concepts:

• 1. API Fundamentals
• 1. REST API
• 1. GraphQL Overview
• 1. API Endpoints
• 1. HTTP Methods
• 1. API Authentication
• 1. API Rate Limiting
• 1. API Versioning
• 1. API Documentation
• 1. Webhooks
• 1. Third-Party Integrations
• 1. API Gateway
• 1. Middleware
• 1. Data Serialization
• 1. JSON Format
• ...and 5 more

SDLC and Agile (AGILE)

Count: 20 concepts (10.0%)

Concepts:

• 1. Software Dev Lifecycle
• 1. Waterfall Methodology
• 1. Agile Development
• 1. Scrum Framework
• 1. Sprint Planning
• 1. Daily Standups
• 1. Sprint Review
• 1. Sprint Retrospective
• 1. Product Backlog
• 1. User Stories
• 1. Acceptance Criteria
• 1. Story Points
• 1. Velocity Tracking
• 1. Kanban Method
• 1. Continuous Integration
• ...and 5 more

AI Tools and Strategy (AITOL)

Count: 20 concepts (10.0%)

Concepts:

• 1. Generative AI Overview
• 1. Large Language Models
• 1. ChatGPT for PMs
• 1. Claude for PMs
• 1. GitHub Copilot
• 1. AI Prompt Engineering
• 1. AI Code Understanding
• 1. AI for Documentation
• 1. AI for Data Analysis
• 1. AI Limitations
• 1. AI Ethics
• 1. AI in Product Strategy
• 1. AI-Augmented Learning
• 1. AI for Debugging
• 1. AI for Prototyping
• ...and 5 more

Quality and Testing (QATST)

Count: 15 concepts (7.5%)

Concepts:

• 1. Technical Debt
• 1. Code Quality
• 1. Code Refactoring
• 1. Legacy Systems
• 1. System Migration
• 1. Testing Fundamentals
• 1. Unit Testing
• 1. Integration Testing
• 1. End-to-End Testing
• 1. Quality Assurance
• 1. Performance Testing
• 1. Security Testing
• 1. Code Coverage
• 1. Automated Testing
• 1. Technical Debt Tracking

Software Development (SWDEV)

Count: 11 concepts (5.5%)

Concepts:

• 1. Software Development
• 1. Source Code
• 1. Programming Languages
• 1. Frontend Development
• 1. Backend Development
• 1. Full Stack Overview
• 1. Version Control
• 1. Git Basics
• 1. Code Repository
• 1. Code Review
• 1. Pull Request

Career and Leadership (CARER)

Count: 10 concepts (5.0%)

Concepts:

• 1. Technical PM Job Market
• 1. Technical Interview Prep
• 1. Technical Communication
• 1. Engineering Team Dynamics
• 1. Build vs Buy Analysis
• 1. Technical Decision Making
• 1. Escalation Frameworks
• 1. Technical Roadmapping
• 1. Personal Learning Plan
• 1. Continuous Tech Learning

Technical Documentation (TCDOC)

Count: 9 concepts (4.5%)

Concepts:

• 1. Technical Documentation
• 1. Engineering Specifications
• 1. Technical Requirements
• 1. Functional Requirements
• 1. Non-Functional Requirements
• 1. Technical Specifications
• 1. Software Bug
• 1. Debugging Basics
• 1. Technical Jargon

Recommendations

• ✅ Excellent balance: Categories are evenly distributed (spread: 8.0%)
• ✅ MISC category minimal: Good categorization specificity

Educational Use Recommendations

• Use taxonomy categories for color-coding in graph visualizations
• Design curriculum modules based on taxonomy groupings
• Create filtered views for focused learning paths
• Use categories for assessment organization
• Enable navigation by topic area in interactive tools

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Report generated by learning-graph-reports/taxonomy_distribution.py