A comprehensive SQL Server database for tracking refugee beneficiary outcomes across employment training, language, housing, and integration programs. Includes 7 analytical query categories and deeper business intelligence insights.
This project demonstrates:
- Relational database design with 8 normalized tables modeling a real NGO workflow
- Advanced SQL analytics across 17 queries covering employment, program effectiveness, attendance, and staff performance
- Business intelligence: impact metrics, at-risk identification, program ROI, staff caseload analysis
- Data-driven decision making for NGO operations optimization
8 Core Tables:
Beneficiaries— Refugee clients in the program (10 records)Staff— Caseworkers, trainers, coordinators (6 staff members)Programs— Language, employment, housing, integration tracks (6 programs)BeneficiaryPrograms— Enrollment records (19 enrollments)Sessions— Individual training sessions (15 sessions)Attendance— Session attendance tracking (50+ records)Outcomes— Certifications, job placements, housing secured (14 outcomes)Employment— Detailed job placement data (5 placements)
| Metric | Value | Status |
|---|---|---|
| Total Beneficiaries | 10 | Active |
| Currently Employed | 6 (60%) | ✅ Strong |
| Job Placements | 5 | ✅ Consistent |
| Average Salary | €1,510/month | 💼 Competitive |
| Salary Range | €1,350 - €1,700 | 💰 Solid |
| Language Certifications | 5 earned | 🎓 Effective |
| Housing Secured | 3 beneficiaries | 🏠 Progressing |
| Program Completion Rate | 70% | ✅ Good |
| Overall Attendance Rate | 91.7% | 🎯 Excellent |
| Name | Country | Job Title | Employer | Monthly Salary | Months to Employment |
|---|---|---|---|---|---|
| Amina Saeed | Syria | Line Cook | Hotel Restaurant Sibaritide | €1,700 | 8 |
| Farida Mohammad | Afghanistan | Food Prep Cook | Trattoria Bella | €1,600 | 7 |
| Hana Rashid | Syria | Receptionist | Community Health Center | €1,500 | 4 |
| Ahmed Ibrahim | Syria | Kitchen Assistant | Restaurant Milano | €1,400 | 7 |
| Leila Husein | Syria | Customer Service Agent | Call Center Italia | €1,350 | 5 |
Key Findings:
- ⚡ Fastest to Employment: Hana Rashid (4 months from arrival)
- 💰 Highest Salary: Amina Saeed (€1,700/month — Line Cook)
- 🏭 Top Sector: Hospitality/Food Service (3 of 5 placements)
- 📊 Salary Statistics: Min €1,350, Max €1,700, Average €1,510
| Program | Type | Enrolled | Completed | Active | Completion % | Total Outcomes |
|---|---|---|---|---|---|---|
| Culinary Skills Workshop | Employment | 2 | 2 | 0 | 100% ⭐ | 6 |
| Italian Language Basics | Language | 7 | 5 | 2 | 71.4% | 12 |
| Job Readiness Training | Employment | 5 | 3 | 2 | 60% | 6 |
| Digital Literacy for Adults | Integration | 2 | 1 | 1 | 50% | 2 |
| Healthcare & Social Services | Integration | 2 | 0 | 2 | 0% | 0 |
| Housing Navigation Program | Housing | 1 | 0 | 1 | 0% | 0 |
Program Popularity & Outcomes:
| Program | Enrolled | Total Outcomes | Outcome Per Beneficiary |
|---|---|---|---|
| Italian Language Basics | 7 | 12 | 1.71 |
| Job Readiness Training | 5 | 6 | 1.20 |
| Culinary Skills Workshop | 2 | 6 | 3.0 ⭐ |
| Digital Literacy for Adults | 2 | 2 | 1.0 |
| Healthcare & Social Services | 2 | 0 | 0 |
| Housing Navigation Program | 1 | 0 | 0 |
Key Insight: Culinary Skills Workshop is the most efficient — smallest cohort (2) with highest outcome ratio (3 outcomes per beneficiary).
| Caseworker | Role | Caseload | Employed | Success Rate | Avg Months in Program |
|---|---|---|---|---|---|
| Fatima Ahmed | Caseworker | 5 | 4 | 80% ⭐ | 37 months avg |
| Aisha Hassan | Caseworker | 5 | 2 | 40% | 38 months avg |
Non-Direct Caseload Roles:
- Marco Rossi (Trainer) — 0 direct beneficiaries
- Giovanni Bianchi (Employment Coordinator) — 0 direct beneficiaries
- Maria Conti (Language Trainer) — 0 direct beneficiaries
- David Moretti (Integration Officer) — 0 direct beneficiaries
Key Finding: Fatima Ahmed leads with 80% employment success rate (4 of 5 beneficiaries employed). Opportunity: analyze Fatima's approach and replicate with Aisha's caseload.
| Beneficiary | Total Sessions | Present | Absent | Attendance Rate | Status |
|---|---|---|---|---|---|
| Ahmed Ibrahim | 7 | 7 | 0 | 100% ⭐ | Employed |
| Leila Husein | 7 | 7 | 0 | 100% ⭐ | Employed |
| Amina Saeed | 7 | 7 | 0 | 100% ⭐ | Employed |
| Karim Mahmoud | 5 | 5 | 0 | 100% ⭐ | In Program |
| Hana Rashid | 7 | 7 | 0 | 100% ⭐ | Employed |
| Zainab Ahmed | 3 | 3 | 0 | 100% ⭐ | Employed |
| Farida Mohammad | 7 | 6 | 1 | 85.7% | Employed |
| Hassan Ali | 4 | 3 | 1 | 75% | In Program |
| Mohammed Khalil | 4 | 3 | 1 | 75% | In Program |
| Omar Hassan | 3 | 2 | 1 | 66.7% | In Program |
Attendance by Program:
| Program | Total Sessions | Present | Attendance Rate |
|---|---|---|---|
| Culinary Skills Workshop | 6 | 6 | 100% ⭐ |
| Healthcare & Social Services | 3 | 3 | 100% ⭐ |
| Job Readiness Training | 15 | 14 | 93.3% |
| Italian Language Basics | 25 | 23 | 92% |
| Digital Literacy for Adults | 5 | 4 | 80% |
Critical Insight: 6 beneficiaries have 100% attendance and 5 of them are employed. Strong correlation between attendance and employment outcomes.
| Beneficiary | Status | Programs | Program Pathway | Outcomes |
|---|---|---|---|---|
| Farida Mohammad | Employed | 6 | Language → Language → Language → Culinary → Culinary → Culinary | 3 |
| Amina Saeed | Employed | 6 | Language → Language → Language → Culinary → Culinary → Culinary | 3 |
| Leila Husein | Employed | 4 | Language → Language → Job Readiness → Job Readiness | 2 |
| Ahmed Ibrahim | Employed | 4 | Language → Language → Job Readiness → Job Readiness | 2 |
| Hana Rashid | Employed | 4 | Language → Language → Job Readiness → Job Readiness | 2 |
| Zainab Ahmed | Employed | 2 | Digital Literacy → Digital Literacy | 2 |
| Mohammed Khalil | In Program | 2 | Job Readiness → Healthcare & Social Services | 0 |
| Karim Mahmoud | In Program | 2 | Job Readiness → Healthcare & Social Services | 0 |
| Omar Hassan | In Program | 2 | Housing Navigation → Italian Language | 0 |
| Hassan Ali | In Program | 2 | Digital Literacy → Italian Language | 0 |
Successful Pathways (Leading to Employment):
- Language + Culinary (Farida, Amina) — 100% employment ⭐
- Language + Job Readiness (Leila, Ahmed, Hana) — 100% employment ⭐
- Digital Literacy (Zainab) — 100% employment ⭐
In-Progress Pathways (No Outcomes Yet):
- Job Readiness + Healthcare (Mohammed, Karim)
- Housing Navigation + Language (Omar)
- Digital Literacy + Language (Hassan)
| Outcome Type | Total | Beneficiaries | Names |
|---|---|---|---|
| Job Placement | 5 | 5 | Ahmed Ibrahim, Amina Saeed, Farida Mohammad, Hana Rashid, Leila Husein |
| Language Certification | 5 | 5 | Ahmed Ibrahim, Amina Saeed, Farida Mohammad, Hana Rashid, Leila Husein |
| Housing Secured | 3 | 3 | Amina Saeed, Farida Mohammad, Zainab Ahmed |
| Digital Literacy Certification | 1 | 1 | Zainab Ahmed |
| Beneficiary | Arrival Date | Employment Date | Days to Employment | Months to Employment |
|---|---|---|---|---|
| Hana Rashid | 2023-05-20 | 2023-09-10 | 113 | 4 |
| Leila Husein | 2023-04-12 | 2023-09-05 | 146 | 5 |
| Ahmed Ibrahim | 2023-02-10 | 2023-09-15 | 217 | 7 |
| Farida Mohammad | 2023-03-05 | 2023-10-20 | 229 | 7 |
| Amina Saeed | 2023-02-28 | 2023-10-25 | 239 | 8 |
Time-to-Outcome Range: 113-239 days (4-8 months) — Excellent velocity for employment outcomes.
| Beneficiary | Status | Days in Program | Sessions Attended | Absences | Attendance % | Outcomes |
|---|---|---|---|---|---|---|
| Omar Hassan | In Program | 35 | 3 | 1 | 66.7% |
0 |
| Hassan Ali | In Program | 40 | 4 | 0 | 75% |
0 |
| Mohammed Khalil | In Program | 36 | 4 | 1 | 75% |
0 |
Risk Factors:
- All 3 are still "In Program" with no outcomes achieved yet
- Omar Hassan has lowest attendance (66.7%) — highest dropout risk
- Hassan Ali has been in program longest (40 days) with minimal progress
- Mohammed Khalil has 1 absence — attention needed
Recommendation: Conduct 1-on-1 check-ins with these beneficiaries; consider mentorship pairing with high-performing beneficiaries (Ahmed, Leila, Amina).
| Program | Duration (days) | Completed | In Progress | Enrollment to Completion Time |
|---|---|---|---|---|
| Culinary Skills Workshop | 122 | 2 | 0 | Shortest ⭐ |
| Job Readiness Training | 276 | 3 | 2 | Fast |
| Italian Language Basics | 375 | 5 | 2 | Medium |
| Digital Literacy for Adults | 574 | 1 | 1 | Longer |
| Healthcare & Social Services | 996 | 0 | 2 | Longest (ongoing) |
| Housing Navigation Program | 1088 | 0 | 1 | Longest (ongoing) |
Key Insight: Culinary Skills moves fastest (122 days average) and has 100% completion — ideal for quick wins and momentum building.
REFUGEE SUPPORT NGO IMPACT REPORT
═══════════════════════════════════════════════════════════════
BENEFICIARIES SERVED: 10 total
✅ Employed: 5 (50%)
📚 In Active Programs: 5 (50%)
🎯 Outcomes Achieved: 14 total
EMPLOYMENT OUTCOMES:
💼 Total Placements: 5
💰 Average Salary: €1,510/month
⏱️ Average Time to Employment: 5.4 months
🏭 Top Sector: Hospitality/Food Service
PROGRAM PERFORMANCE:
⭐ Best Performing: Culinary (100% completion)
🎓 Most Popular: Italian Language (7 enrolled)
📈 Fastest Results: Culinary (122 days)
🎯 Highest Engagement: Culinary & Healthcare (100% attendance)
QUALITY METRICS:
👥 Overall Attendance Rate: 91.7%
📊 Program Completion Rate: 70%
🎯 Beneficiaries with 100% Attendance: 6 (60%)
💼 Employment Rate (Multi-Program): 70% (7 of 10)
STAFF HIGHLIGHTS:
⭐ Top Caseworker: Fatima Ahmed (80% success rate)
👥 Team Size: 6 staff (2 caseworkers, 4 specialists)
═══════════════════════════════════════════════════════════════
refugee-support-ngo-database/
├── README.md # This comprehensive guide
├── database/
│ ├── 01_schema.sql # 8 table definitions
│ └── 02_sample_data.sql # 10 beneficiaries + programs
├── queries/
│ ├── 01_employment_outcomes.sql
│ ├── 02_employment_statistics.sql
│ ├── 03_program_completion_rates.sql
│ ├── 04_program_popularity.sql
│ ├── 05_staff_performance.sql
│ ├── 06_attendance_by_beneficiary.sql
│ ├── 07_attendance_by_program.sql
│ ├── 08_beneficiary_journey.sql
│ ├── 09_program_pathway.sql
│ ├── 10_outcomes_by_type.sql
│ ├── 11_time_to_employment.sql
│ ├── 12_impact_dashboard.sql
│ ├── 13_at_risk_beneficiaries.sql
│ ├── 14_program_roi.sql
│ ├── 15_staff_caseload_analysis.sql
│ └── 16_bottleneck_analysis.sql
└── results/
├── Q1-Result.csv # Employment outcomes (5 placed)
├── Q1-Result2.csv # Employment statistics
├── Q2-Result.csv # Program completion rates
├── Q2-Result2.csv # Program popularity
├── Q3-Result.csv # Staff performance
├── Q4-Result.csv # Attendance by beneficiary
├── Q4-Result2.csv # Attendance by program
├── Q5-Result.csv # Beneficiary journeys
├── Q5-Result2.csv # Program pathways
├── Q6-Result.csv # Outcomes by type
├── Q6-Result2.csv # Time to employment
├── Q7-Result.csv # Impact dashboard
├── Q8-Result.csv # Program ROI
├── Q9-Result.csv # Deeper employment analysis
├── Q10-Result.csv # Staff caseload analysis
├── Q11-Result.csv # Bottleneck analysis
└── At-Risk_Beneficiaries-Result.csv # At-risk identification
CREATE DATABASE RefugeeSupportNGO;- Open SQL Server Management Studio (SSMS)
- Connect to SQL Server
- Right-click
RefugeeSupportNGO→ New Query - Run
database/01_schema.sql(creates 8 tables) - Run
database/02_sample_data.sql(loads 10 beneficiaries + data)
- Open any query from
queries/folder - Execute in SSMS
- Export results to CSV
- Compare with files in
results/folder
-
Culinary Skills Program is outperforming on efficiency
- 100% completion, fastest duration, perfect outcomes ratio
- Action: Scale or replicate for other sectors
-
High attendance predicts employment
- 6 beneficiaries with 100% attendance, 5 are employed
- Action: Implement early-warning system for <80% attendance
-
Language + Job Readiness pathway is proven
- 5 of 5 beneficiaries (100%) employed
- Action: Make this the standard pathway for employment-track participants
-
Fatima Ahmed's casework approach is effective
- 80% employment success rate (4 of 5)
- Action: Document her methods, mentor Aisha Hassan's caseload
-
3 beneficiaries at-risk of dropout
- Omar Hassan (66.7% attendance), Hassan Ali (0 outcomes after 40 days), Mohammed Khalil (low progress)
- Action: Implement intervention protocol, 1-on-1 support, mentorship pairing
-
Healthcare & Housing programs show 0 completion
- Both have only "In Progress" beneficiaries with no outcomes
- Action: Review curriculum, increase support, integrate with employment programs
-
Housing program has low enrollment
- Only 1 beneficiary enrolled
- Action: Promote housing support more actively; bundle with employment outcomes
- Database Engine: SQL Server 2025 (Express Edition)
- Version: 17.0.1000.7 (X64)
- Environment: Windows 10 Pro, Hypervisor
- Query Tool: SQL Server Management Studio (SSMS)
- Language: T-SQL
- Normalization Level: Third Normal Form (3NF)
- JOINs: LEFT JOIN, INNER JOIN for table relationships
- Aggregation: COUNT, SUM, AVG, MIN, MAX with CASE statements
- Window Functions: ROW_NUMBER, RANK for ranking
- String Functions: STRING_AGG for program sequences with ORDER BY
- Date Functions: DATEDIFF for duration calculations
- Conditional Logic: CASE WHEN for status categorization
- Add Power BI dashboard for executive reporting
- Create Tableau interactive visualizations by beneficiary status
- Build funnel analysis for program drop-out prediction
- Implement automated at-risk alerts (attendance <80%)
- Expand to 12-month historical data for trend analysis
- Track long-term employment retention (6, 12, 24 months)
- Add beneficiary satisfaction survey results
- Integrate salary progression tracking
- Create custom reports for donor reporting
- Build API for real-time dashboard updates
Type: Portfolio Project — SQL Database Design & Analytics
Author: Eva Safi | Data Analyst
University: Üsküdar University, Istanbul
Date Created: May 2026
Purpose: Demonstrate database design, advanced SQL queries, and data-driven decision making for NGO operations
Skills Demonstrated:
- ✅ Relational database design (schema, normalization)
- ✅ Complex SQL queries (aggregation, JOINs, window functions)
- ✅ Data analysis and business intelligence
- ✅ KPI development and impact measurement
- ✅ Risk identification and decision support
- ✅ Documentation and reporting
Dataset: Fictitious refugee support NGO (demo data for educational purposes)
This project is open-source for educational and portfolio purposes. Feel free to fork, modify, or adapt for your own NGO database projects.
Last Updated: May 24, 2026
Query Results Included: 17 comprehensive analyses
Documentation Status: Complete ✅