Welcome to the public repository for Data Technologies Administration.
This course is designed as a full-lifecycle enterprise data architecture simulation.
Students do not simply learn tools.
They learn how to design, govern, protect, validate, and defend modern data systems.
Modern organizations do not fail because they lack data.
They fail because they cannot govern it.
This course integrates:
- Data modeling
- Lifecycle architecture
- Workload separation (OLTP vs OLAP)
- Governance strategy
- Role-based access control
- Monitoring and audit reasoning
- Executive communication
The goal is to move students from:
“I can write queries.”
to
“I can design accountable data systems.”
.
├── capstone_prokect/
├── dbt/
├── docs/
├── labs/
├── notebooks/
├── scripts/
├── submissions/
└── README.md
The lab sequence builds progressively through governance layers.
Lab 1 → Infrastructure Setup
Lab 2 → Data Classification
Lab 3 → Layered Modeling Architecture
Lab 4 → Lifecycle & Lineage Validation
Lab 5 → Access Control Enforcement
Lab 6 → Monitoring & Audit Evaluation
Together, they simulate the enterprise lifecycle:
Design → Classify → Model → Execute → Protect → Monitor → Evaluate
Each lab introduces one governance layer and validates it technically.
📄 See: labs/README.md
All capstone phases are grounded in the Business Interview Transcript:
📄 See: Business_Interview_Transcript.md
Architectural and governance decisions must be traceable to transcript evidence.
The capstone integrates the entire lab sequence into a professional architecture simulation.
Students design, defend, and validate a secure retail data platform across seven phases:
- Discovery
- Logical Data Modeling
- Workload Strategy
- Governance Overlay
- Evidence & Enforcement
- Executive Defense
- Individual Reflection
This capstone emphasizes:
- Risk-based reasoning
- Accountability mapping
- Lifecycle protection
- Evidence-based architectural validation
- Executive-level communication
📄 See: capstone_project/README.md
This course uses a practical, industry-aligned toolchain:
- PostgreSQL
- dbt (data build tool)
- Linux/Ubuntu environment
- Role-Based Access Control (RBAC)
- Audit log monitoring
The framework is tool-agnostic but governance-centered.
Tools may evolve.
Architectural discipline remains constant.
By completing this course, students gain experience in:
- Enterprise data modeling
- Lifecycle-aware architecture
- Governance strategy integration
- Security enforcement reasoning
- Risk and compliance analysis
- Monitoring & audit interpretation
- Executive communication
- Evidence-based design validation
This is applied data administration — not theoretical database instruction.
This repository demonstrates a governance-centered approach to teaching data technologies.
Key pedagogical principles:
- Architecture before tools
- Governance embedded in structure
- Lifecycle separation enforced technically
- Evidence required for claims
- Executive communication simulated
The framework can be adapted to:
- Different industries
- Alternative tooling stacks
- Shorter or longer academic terms
The emphasis is on accountability, not syntax.
This course is designed to prepare students for roles such as:
- Data Engineer
- Analytics Engineer
- Data Governance Analyst
- Data Platform Administrator
- Enterprise Data Architect (entry-level pathway)
Students leave understanding not just how systems work —
but how systems must be defended.
Enterprise data architecture requires more than technical fluency.
It requires:
- Structured reasoning
- Risk awareness
- Governance discipline
- Proof of enforceability
- Clear executive communication
This repository represents a complete lifecycle framework for developing those competencies.
Welcome to enterprise data administration.
Spring 2026 Edition
Future updates will be tagged by semester.
- Code components are licensed under the MIT License.
- Curriculum and documentation content are licensed under Creative Commons Attribution 4.0 (CC BY 4.0).
See LICENSE and LICENSE-CONTENT.md for details.