# ✅ Base Database Ingestion Complete!

**Date:** October 5, 2025  
**Database:** `version_two.db`

## 📊 Summary Statistics

| Entity                             | Count  |
| ---------------------------------- | ------ |
| **Investors**                      | 9,315  |
| **Companies**                      | 6,877  |
| **Sectors**                        | 639    |
| **Investor-Company Relationships** | 22,548 |
| **Investor-Sector Relationships**  | 75,307 |

## 🎯 Top Investors by Portfolio Size

1. **Bpifrance** - 211 companies
2. **European Innovation Council** - 183 companies
3. **Business Growth Fund** - 84 companies
4. **HTGF (High-Tech Gruenderfonds)** - 74 companies
5. **EIT InnoEnergy** - 72 companies

## 📁 Source Files

-   **Companies CSV**: 13,027 rows
-   **Investors CSV**: 11,045 rows
-   **Investors Ingested**: 9,315 (some duplicates/invalid entries filtered out)

## 🗃️ Database Structure

### Tables Created:

-   ✅ `investors` - Core investor data
-   ✅ `companies` - Portfolio companies
-   ✅ `sectors` - Industry sectors
-   ✅ `funds` - (Empty, will be populated during enrichment)
-   ✅ `investor_members` - (Empty, will be populated during enrichment)
-   ✅ `company_members` - Company team members
-   ✅ `investment_stages` - Investment stage definitions
-   ✅ Association tables for relationships

### Current Data:

-   ✅ Investor names and basic info (website, investment count)
-   ✅ Company details (name, location, industry, description)
-   ✅ Sectors extracted from company industries
-   ✅ Investor → Company relationships (who invested in what)
-   ✅ Investor → Sector relationships (derived from portfolio)

### Missing (To Be Added via Enrichment):

-   ⏳ Investor headquarters
-   ⏳ AUM (Assets Under Management) details
-   ⏳ Investment thesis
-   ⏳ Portfolio highlights
-   ⏳ Fund details (multiple funds per investor)
-   ⏳ Senior leadership/team members
-   ⏳ Research notes and sources

## 🔄 Next Steps

### 1. Prepare Enriched Data CSV

Your enriched CSV should have this structure:

```csv
investor_name,enriched_data
"212","{\"websiteURL\": \"...\", \"funds\": [...], ...}"
"301","{...}"
```

### 2. Run Enrichment Script

```bash
cd preprocessor
python enrich_investors.py enriched_investors.csv investor_name enriched_data
```

This will:

-   ✅ Add fund details (multiple funds per investor)
-   ✅ Update AUM information
-   ✅ Add investment thesis
-   ✅ Add portfolio highlights
-   ✅ Add senior leadership
-   ✅ Add research notes and sources

### 3. Verify Enriched Data

```bash
python3 << 'EOF'
from models import InvestorTable, FundTable, get_db_session
session = get_db_session()

# Check enriched data
investor = session.query(InvestorTable).filter_by(name="Anaxago").first()
if investor:
    print(f"Investor: {investor.name}")
    print(f"HQ: {investor.headquarters}")
    print(f"AUM: {investor.aum}")
    print(f"Funds: {len(investor.funds)}")
    for fund in investor.funds:
        print(f"  - {fund.fund_name}")

session.close()
EOF
```

## 📝 Sample Queries

### Get Investor with Portfolio

```python
from models import InvestorTable, get_db_session

session = get_db_session()
investor = session.query(InvestorTable).filter_by(name="Bpifrance").first()

print(f"Investor: {investor.name}")
print(f"Website: {investor.website}")
print(f"Investments: {investor.number_of_investments}")
print(f"Portfolio Companies: {len(investor.portfolio_companies)}")
print(f"Sectors: {[s.name for s in investor.sectors[:5]]}")

session.close()
```

### Get Companies by Sector

```python
from models import CompanyTable, SectorTable, get_db_session

session = get_db_session()
sector = session.query(SectorTable).filter_by(name="AgTech").first()

print(f"Sector: {sector.name}")
print(f"Companies: {len(sector.companies)}")
for company in sector.companies[:5]:
    print(f"  - {company.name}")

session.close()
```

### Get Investor's Sector Distribution

```python
from models import InvestorTable, get_db_session

session = get_db_session()
investor = session.query(InvestorTable).filter_by(name="Bpifrance").first()

sectors = {}
for company in investor.portfolio_companies:
    for sector in company.sectors:
        sectors[sector.name] = sectors.get(sector.name, 0) + 1

# Top sectors
for sector, count in sorted(sectors.items(), key=lambda x: x[1], reverse=True)[:5]:
    print(f"{sector}: {count} companies")

session.close()
```

## ⚠️ Known Issues

### Investors Not Found in DB

Some companies reference investors that weren't in the investors CSV:

-   The Venture Collective
-   Sarah Leary
-   Transpose
-   ND Capital
-   InvestSud
-   Third Swedish National Pension Fund
-   Union Tech Ventures
-   Vasuki Tech Fund
-   MSA Novo
-   And others...

These are likely individual angel investors or smaller funds not in the main investor list. They are recorded but not linked.

## 🔒 Backup

A backup of the database was created before ingestion:

-   `version_two.db.backup_YYYYMMDD_HHMMSS`

## 📧 Support

For issues or questions:

1. Check the logs for error messages
2. Verify CSV file formats
3. Ensure all required columns are present
4. Check for duplicate entries

---

**Status:** ✅ Base database created successfully  
**Ready for:** Enrichment phase with detailed investor data