From "I've never used SQL Server" to "Here's my 1,000-line operational runbook": How I turned a job opportunity into a portfolio-building sprint.
Hard work is my preferred language and I try to speak it fluently.
🎯 The Opportunity
When "I Don't Know SQL Server" Becomes a Challenge
A friend reached out with an intriguing proposition: "Do you work with Microsoft SQL Server? We're desperate to fill a school data administrator role."
My honest answer? No—but I know databases.
My background spans PostgreSQL, MySQL, MongoDB, and GraphQL. I've built ETL pipelines, optimized queries, designed schemas, and managed production data systems. The fundamentals are universal: normalization, indexing, backup strategies, referential integrity, stored procedures.
SQL Server syntax? Just a dialect I hadn't learned yet.
But here's the thing about job opportunities in unfamiliar territory: saying "I can learn it" isn't enough. Hiring managers hear that every day. What they want is proof.
The Real Challenge
Can I go from zero SQL Server experience to interview-ready in two weeks, with portfolio-quality deliverables to prove it?
This wasn't just about learning T-SQL syntax. The role required:
- Managing school data systems (student records, attendance, class scheduling)
- Running reports for leadership and teaching staff
- Integrating data from legacy systems like SEQTA and Synergetic
- Maintaining backup/recovery procedures
- Documenting operations for non-technical staff
- Operating responsibly with child-safety-sensitive data
The approach: Treat it like a master's assignment. I've spent months tackling academic projects with a disciplined workflow: Receive Brief → Research → Design → Build → Document → Present → NEXT. Why not leverage that momentum?
This is where strategic use of LLMs came into play. Instead of aimlessly "learning SQL Server," I needed a structured challenge that would simulate real-world job responsibilities.
The Prompt That Launched the Project
The prompt:
"I need to demonstrate enterprise-level SQL Server skills for a school data administrator role. Create a comprehensive 3-level assessment covering: (1) database fundamentals and backup/restore, (2) reporting and data integration, (3) operational documentation and training. Structure it like an internal deliverable with real-world scenarios matching school systems like SEQTA and Synergetic."
The Problem
Build a "School Data Platform" on SQL Server, documented like an internal deliverable. Do the deed and show the proof.
The structure emerged as a 3-level assessment simulation (Level 1 → Level 2 → Level 3), matching exactly what the role calls for:
| Assessment Level | Focus Area | Real-World Equivalent |
|---|---|---|
| Level 1 | Database Fundamentals | "Won't break production" |
| Level 2 | Data Integration & Reporting | "Can generate reports and move data between systems" |
| Level 3 | Production Operations | "Documents well, trains staff, operates safely" |
Execution Plan (Dec 2025 - Jan 2026)
| Date | Focus | Deliverables | Status |
|---|---|---|---|
| Dec 20-21 | Setup & Schema | SQL Server Express + SSMS installation, DB creation, table structure | ✅ |
| Dec 22-23 | Backup & Restore | Full backup/restore procedures, documentation with screenshots | ✅ |
| Dec 24-25 | Data Generation | Realistic seed data with edge cases | ✅ |
| Dec 26-27 | Reporting Views | Student profiles, class rolls, attendance summaries | ✅ |
| Dec 28-29 | Stored Procedures | Parameter-based queries, optimization | ✅ |
| Dec 30-31 | Import/Export | CSV handling, staging tables, data validation | ✅ |
| Jan 1-2 | Runbook & Documentation | Operational procedures, troubleshooting guide | ✅ |
| Jan 3-4 | Demo Preparation | Presentation script, screenshots, talking points | ✅ |
| Jan 5 | Final Review | Validate all components, practice demo | ✅ |
🤖 The Solution
Building an Enterprise Data Infrastructure
What started as "learn SQL Server syntax" evolved into a complete operational simulation. Here's what I built:
System Architecture
Database Architecture
The foundation is a normalized relational database representing a school's core operational data:
Core Tables (6):
- Students (200 records) — Privacy-sensitive fields including medical info, emergency contacts, and boarding status
- Staff (20 records) — Role-based attributes (Teacher, Principal, ICT, Admin, Counselor)
- Subjects (12 records) — Curriculum structure covering Math, English, Science, Humanities, Arts, Technology
- Classes (30 records) — Teacher assignments, room scheduling, year level groupings
- Enrollments (500 records) — Student-class relationships with status tracking (Active, Withdrawn, Completed, Pending)
- Attendance (800 records) — Daily tracking with status codes (Present, Absent, Late, Excused) across 10 days
Design Principles:
-- Example: Students table with constraints
CREATE TABLE Students (
student_id INT IDENTITY(1,1) PRIMARY KEY,
student_number NVARCHAR(20) UNIQUE NOT NULL,
first_name NVARCHAR(50) NOT NULL,
medical_info NVARCHAR(500), -- Privacy sensitive
emergency_contact NVARCHAR(100),
enrollment_year INT NOT NULL,
INDEX idx_enrollment_year (enrollment_year),
INDEX idx_student_number (student_number)
);
Operational Features
1. Reporting Views (4 core views)
-
vw_StudentProfile— Complete student records with emergency contacts -
vw_ClassRoll— Daily attendance with class lists and teacher assignments -
vw_AttendanceDaily— Roll call summaries with absence follow-up contacts -
vw_EnrollmentSummary— Class capacity planning with utilization metrics
2. Stored Procedures (4 parameterized)
-
sp_GetStudentProfile— Multi-result set with profile + enrollments + attendance -
sp_EnrollmentSummaryByYear— Year-level filtering with capacity indicators -
sp_AttendanceByDate— Date range queries for specific time periods -
sp_GetTableDataExport— Generic data export for Power BI integration
3. Data Integration Pipeline
- CSV import staging tables with validation rules
- Referential integrity checks before production load
- Error logging and rollback procedures
- Export functionality for SEQTA/Power BI sync
4. Backup & Recovery
- Full backup T-SQL scripts (SQL Server Express compatible)
- Differential backup procedures
- Three-stage restore validation (verify → test → production)
- RPO: 1 hour | RTO: 30 minutes
How It Works in Practice
Scenario 1: Morning Roll Call
-- Teacher logs in at 8:45 AM, needs today's class roll
EXEC sp_AttendanceByDate
@StartDate = '2025-01-22',
@EndDate = '2025-01-22';
-- Returns: Student list with attendance status, emergency contacts for absences
Scenario 2: Semester Planning
-- Leadership needs Year 7 enrollment metrics for 2026 planning
EXEC sp_EnrollmentSummaryByYear @EnrollmentYear = 2026;
-- Returns: Class utilization, capacity warnings, subject distribution
Scenario 3: System Integration
-- SEQTA export runs daily at 6 AM, imports new attendance data
-- 1. Load CSV into staging table
-- 2. Validate referential integrity (all student_ids exist)
-- 3. Merge into production Attendance table
-- 4. Log success/failures for monitoring
Data Quality by Design
Intentional edge cases throughout the seed data:
- NULL values — Missing phone numbers (9%), NULL emergency contacts
- Casing inconsistencies — Lowercase first names, uppercase emails, trailing spaces
- International scenarios — Singapore/Jakarta addresses for boarding students
- Duplicate data — Shared email addresses to test deduplication logic
- Invalid formats — Phone numbers marked as '???', incomplete grades ('INC')
This messy data simulates real school system exports (SEQTA, Synergetic) where cleaning and validation are critical.
Tech Stack
| Layer | Technology | Purpose |
|---|---|---|
| Database | SQL Server 2022 Express | On-premise simulation (macOS via Docker) |
| Management | SSMS + sqlcmd CLI | GUI and scripted operations |
| Data Generation | T-SQL CTEs + temp tables | Deterministic seed data with edge cases |
| Backup | Native SQL Server backups | Full/differential with RPO/RTO targets |
| Integration | CSV imports via BULK INSERT | Simulates SEQTA/Synergetic exports |
| Documentation | Markdown + Mermaid | Runbooks, training guides, flowcharts |
Project Structure:
stc_datalab/
├── sql/
│ ├── 00_create_db.sql # Initial database creation
│ ├── 01_schema.sql # Tables, constraints, indexes
│ ├── 02_seed_data.sql # 1,500+ records with edge cases
│ ├── 03_views.sql # 4 reporting views
│ ├── 04_stored_procedures.sql # 4 parameterized SPs
│ ├── 05_import_export.sql # CSV integration logic
│ └── 07_backup_restore.sql # Backup/recovery procedures
├── data/
│ ├── students_import.csv # Sample import data
│ ├── classes_import.csv
│ └── enrollments_import.csv
├── docs/
│ ├── Assessment1/ # Level 1: Setup & basics
│ ├── Assessment2/ # Level 2: Integration
│ └── Assessment3/ # Level 3: Operations
│ ├── 06_runbook.md # 1,000+ line operational guide
│ ├── 07_demo_script.md # Interview presentation
│ └── 08_staff_training_guide.md
└── screenshots/ # 15+ annotated screenshots
The Impact: Confidence Through Deliverables
This wasn't just practice—it was portfolio-building with interview-ready artifacts:
| Metric | Result |
|---|---|
| Technical documentation | 3,000+ lines across 15 files |
| SQL scripts | 10 files, 800+ lines of T-SQL |
| Seed data generated | 1,562 records across 6 tables |
| Views & procedures | 8 reusable database objects |
| Operational runbook | 1,000+ lines with flowcharts |
| Training materials | Non-technical staff guide |
| Time investment | 16 days, committed execution |
What This Proves
| Skill Category | Evidence |
|---|---|
| Database fundamentals | Schema design with normalization, constraints, indexes |
| T-SQL proficiency | CTEs, window functions, stored procedures, error handling |
| Data integration | CSV imports with staging, validation, rollback procedures |
| Backup/recovery | Full/differential backups, 3-stage restore validation |
| Documentation | Runbooks, training guides, troubleshooting flowcharts |
| Production mindset | Security (least privilege), audit logging, change management |
Interview Readiness
Instead of saying "I can learn SQL Server", I can now walk into an interview and say:
"I built a production-grade school data platform with 6 normalized tables, 8 reporting objects, comprehensive backup procedures, and operational documentation. Here's the GitHub repo, here's the demo script, and here are the 15 annotated screenshots. Let me show you the runbook."
Future Roadmap: From Simulation to Production
While this project is interview-focused, the architecture supports real-world expansion:
1. Power BI Dashboard Integration
- Connect reporting views to interactive dashboards
- Real-time attendance monitoring with alerting
- Enrollment trend analysis across years
- Teacher workload visualization
2. Automated SEQTA Sync
- Scheduled SSIS packages for nightly imports
- Incremental updates with change data capture
- Email notifications on import failures
- Data quality scorecards
3. Advanced Security & Compliance
- Row-level security based on staff roles
- Transparent data encryption for medical_info
- Audit tables with temporal queries
- GDPR-compliant data retention policies
4. Performance Optimization
- Columnstore indexes for historical reporting
- Query Store analysis for slow queries
- Database partitioning by enrollment_year
- Read replicas for Power BI loads
5. Cloud Migration Path
- Azure SQL Database deployment
- Geo-replication for disaster recovery
- Azure Data Factory for ETL orchestration
- Integration with Microsoft 365 (SharePoint, Teams)
Key Takeaways
This project reinforced several engineering principles:
- Build to prove, not just to practice — Every decision was portfolio-oriented
- Documentation = Deliverable — The runbook is as important as the code
- Simulate real constraints — SQL Server Express limits forced production-ready design
- Edge cases reveal skill — Intentional data quality issues prove validation competency
- Timeline discipline — 16-day execution plan kept momentum and accountability
Try It Yourself
The complete project is open source and ready to deploy:
| Resource | Link |
|---|---|
| GitHub Repo | github.com/lfariabr/stc-datalab |
| Setup Guide | Assessment 1 Documentation |
| Operational Runbook | 06_runbook.md |
| Demo Script | 07_demo_script.md |
Quick Start (Docker):
# 1. Clone the repo
git clone https://github.com/lfariabr/stc-datalab.git
cd stc-datalab
# 2. Start SQL Server Express
docker run -e "ACCEPT_EULA=Y" \
-e "MSSQL_SA_PASSWORD=StC_SchoolLab2025!" \
-e "MSSQL_PID=Express" \
-p 1433:1433 --name sqlserver \
-d mcr.microsoft.com/mssql/server:2022-latest
# 3. Create database and schema
sqlcmd -S localhost -U sa -P 'StC_SchoolLab2025!' -C -i sql/00_create_db.sql
sqlcmd -S localhost -U sa -P 'StC_SchoolLab2025!' -C -i sql/01_schema.sql
# 4. Seed demo data
sqlcmd -S localhost -U sa -P 'StC_SchoolLab2025!' -C -i sql/02_seed_data.sql
# 5. Test reporting
sqlcmd -S localhost -U sa -P 'StC_SchoolLab2025!' -C -Q \
"USE StC_SchoolLab; EXEC sp_AttendanceByDate @StartDate='2025-01-22', @EndDate='2025-01-22';"
Let's Connect!
This project exemplifies my approach to technical challenges: structured execution, production-quality deliverables, and comprehensive documentation. If you're:
- Building enterprise data systems
- Working with SQL Server in education/non-profit sectors
- Interested in data engineering best practices
- Hiring for database administration roles
I'd love to connect:
- LinkedIn: linkedin.com/in/lfariabr
- GitHub: github.com/lfariabr
- Portfolio: luisfaria.dev
Tech Stack Summary:
| Current Implementation | Production Extensions |
|---|---|
| SQL Server 2022 Express, SSMS, T-SQL, Docker, Markdown | Azure SQL Database, SSIS, Power BI, Columnstore Indexes, TDE, Azure Data Factory |
Built with 🎓 and database discipline by Luis Faria
Hard work is my preferred language and I try to speak it fluently.
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