Intelligent Business Knowledge Graph (IBKG)

A data pipeline and analysis system for processing and analyzing business metrics across multiple companies. This system helps organizations understand their performance metrics, optimize resource allocation, and make data-driven decisions.

Live Demo

A live version of this dashboard is available at:

👉 View the Live Demo on Render.com

🌟 Features

Core Features

Multi-Company Analysis: Process and compare metrics across multiple companies
Impact Analysis: Calculate the effect of budget changes on key metrics
Historical Trends: Track and analyze metric changes over time
Customer Segmentation: Analyze performance across different customer segments
Department Optimization: Optimize resource allocation across departments

Advanced Features

Real-time Processing: Process data as it comes in
Automated Validation: Ensure data quality and consistency
Custom Metrics: Define and track company-specific KPIs
Export Capabilities: Export data in multiple formats
API Integration: Connect with other business systems

📊 Data Structure

Raw Data

Located in src/data/pipeline/raw/, organized by company and data type:

raw/
├── financial/          # Monthly financial metrics
│   ├── Company_financial_2024.csv
│   └── ...
├── departments/        # Department budgets and targets
│   ├── Company_budgets_2024.xlsx
│   └── ...
├── historical/         # Historical trends and metrics
│   ├── Company_metrics_2023.csv
│   └── ...
└── customers/         # Customer segmentation and behavior
    ├── Company_customers_2024.json
    └── ...

Data Formats

Financial Data (CSV)

date,revenue,expenses,profit,cac,ltv,churnRate,arpa
2024-01,6500000,4800000,1700000,2500,15000,0.008,1200
2024-02,6700000,4900000,1800000,2450,15200,0.007,1220

Department Budgets (JSON)

{
  "departments": [
    {
      "name": "Sales",
      "budget": 2000000,
      "headcount": 90,
      "target_revenue": 35000000,
      "tools_budget": 250000
    },
    {
      "name": "Marketing",
      "budget": 1500000,
      "headcount": 70,
      "target_leads": 40000,
      "tools_budget": 200000
    }
  ]
}

Customer Data (JSON)

{
  "customer_segments": {
    "enterprise": {
      "count": 300,
      "avg_contract_value": 800000,
      "churn_rate": 0.04,
      "expansion_rate": 0.35,
      "avg_tenure_months": 42
    },
    "mid_market": {
      "count": 600,
      "avg_contract_value": 200000,
      "churn_rate": 0.07,
      "expansion_rate": 0.28,
      "avg_tenure_months": 30
    }
  },
  "product_adoption": {
    "core_product": 0.95,
    "addon_1": 0.85,
    "addon_2": 0.75
  }
}

Processed Data

Located in src/data/companies/, each company has its own directory containing:

companies/
├── Salesforce/
│   └── impactMatrix.json
├── HubSpot/
│   └── impactMatrix.json
├── Workday/
│   └── impactMatrix.json
├── ServiceNow/
│   └── impactMatrix.json
└── Zoom/
    └── impactMatrix.json

🛠️ Setup

Prerequisites

Node.js (v14 or higher)
npm (v6 or higher)
Git
4GB RAM minimum
1GB free disk space

Installation

Clone the repository:

git clone https://github.com/yourusername/ibkg.git
cd ibkg

Install dependencies:

npm install

Required dependencies:

{
  "dependencies": {
    "csv-parse": "^5.5.3",
    "xlsx": "^0.18.5",
    "react": "^18.2.0",
    "react-dom": "^18.2.0",
    "vite": "^5.0.0"
  }
}

Environment Setup

Create a .env file:

cp .env.example .env

Configure environment variables:

NODE_ENV=development
PORT=3000
DATA_DIR=src/data
LOG_LEVEL=info

🚀 Usage

Running the Data Pipeline

Process all company data:

npm run process-data

Or run for specific companies:

node src/data/pipeline/runPipeline.js

Development

Start the development server:

npm start

Build for production:

npm run build

Run tests:

npm test

Common Commands

# Process specific company
npm run process-data -- --company=Salesforce

# Run with debug logging
npm run process-data -- --debug

# Generate reports
npm run generate-reports

# Validate data
npm run validate-data

📈 Data Processing

Financial Metrics

Revenue: Monthly revenue figures
- Total revenue
- Recurring revenue
- One-time revenue
Expenses: Operating costs and investments
- Fixed costs
- Variable costs
- R&D expenses
Profit: Net income after expenses
- Gross profit
- Operating profit
- Net profit
CAC: Customer Acquisition Cost
- Marketing CAC
- Sales CAC
- Total CAC
LTV: Customer Lifetime Value
- Gross LTV
- Net LTV
- LTV/CAC ratio
Churn Rate: Customer attrition rate
- Gross churn
- Net churn
- Revenue churn
ARPA: Average Revenue Per Account
- Monthly ARPA
- Annual ARPA
- ARPA growth

Department Metrics

Budget Allocations: Department-wise budget distribution
- Operating budget
- Capital budget
- Project budget
Headcount: Team size and composition
- Full-time employees
- Contractors
- Team distribution
Target Metrics: Department-specific KPIs
- Sales targets
- Marketing goals
- R&D milestones
Tool Budgets: Software and tool investments
- SaaS tools
- Development tools
- Analytics tools

Impact Analysis

The system generates impact matrices showing how changes in:

Marketing Budget:
- Effect on CAC (typically negative correlation)
- Impact on revenue growth
- Brand awareness metrics
- Lead generation efficiency
Sales Budget:
- Revenue generation efficiency
- CAC optimization
- Sales cycle length
- Win rate improvement
R&D Budget:
- Churn rate reduction
- LTV improvement
- Product adoption
- Feature usage

📊 Current State

The system successfully processes data for all supported companies, generating impact matrices that reflect:

Salesforce
- Strong sales impact on revenue (0.41125)
- Balanced marketing and R&D impacts
- Enterprise-focused metrics
- High customer retention
- Strong upsell potential
HubSpot
- High marketing efficiency
- Strong customer retention metrics
- Mid-market optimization
- Content marketing focus
- High organic growth
Workday
- Enterprise-focused metrics
- High LTV impact from R&D (0.32)
- Strong HR/Finance focus
- High implementation success
- Strong partner ecosystem
ServiceNow
- Highest R&D impact on LTV (0.34)
- Strong enterprise retention
- IT service management focus
- High platform adoption
- Strong integration capabilities
Zoom
- High marketing impact on CAC reduction (-0.2925)
- Strong sales revenue impact (0.41475)
- High user engagement metrics
- Strong freemium model
- High viral growth

🔧 Technical Details

Pipeline Architecture

src/data/pipeline/
├── processData.js      # Main processing logic
├── runPipeline.js      # Pipeline execution
├── utils/             # Helper functions
│   ├── validation.js  # Data validation
│   ├── metrics.js     # Metric calculations
│   └── export.js      # Data export
├── models/            # Data models
│   ├── Company.js     # Company model
│   ├── Metrics.js     # Metrics model
│   └── Impact.js      # Impact model
├── processed/         # Intermediate results
└── raw/              # Input data

Processing Steps

Data Validation
- Format checking
- Type validation
- Range validation
- Consistency checks
Metric Calculation
- Financial metrics
- Operational metrics
- Customer metrics
- Department metrics
Impact Analysis
- Budget impact
- Resource allocation
- Performance metrics
- Trend analysis
Matrix Generation
- Impact matrices
- Correlation matrices
- Trend matrices
- Performance matrices
Result Storage
- JSON output
- CSV export
- Database storage
- Cache management

Error Handling

Input Validation
- File existence
- Format validation
- Data type checking
- Range validation
Processing Errors
- Calculation errors
- Memory issues
- Timeout handling
- Resource limits
Output Validation
- Result verification
- Format checking
- Consistency validation
- Export validation

Performance Optimization

Parallel processing
Caching strategies
Memory management
Resource optimization

🐛 Troubleshooting

Common Issues

Data Processing Errors

Error: Invalid data format
Solution: Check file format and structure

Memory Issues

Error: Out of memory
Solution: Increase Node.js memory limit

File Access Issues

Error: Cannot read file
Solution: Check file permissions

Debug Mode

# Enable debug logging
DEBUG=* npm run process-data

# Show detailed errors
npm run process-data -- --verbose

🤝 Contributing

Fork the repository
Create a feature branch
Commit your changes
Push to the branch
Create a Pull Request

Development Guidelines

Follow the existing code style
Add tests for new features
Update documentation
Ensure backward compatibility

Code Style

// Example of code style
function processData(data) {
  // Input validation
  if (!data) {
    throw new Error('Invalid input');
  }

  // Process data
  const result = data.map(item => ({
    ...item,
    processed: true
  }));

  return result;
}

Testing

# Run all tests
npm test

# Run specific test
npm test -- --grep="processData"

# Coverage report
npm run test:coverage

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

Inspired by the need for better financial benchmarking tools
Built with modern web technologies
Designed for CFOs and financial analysts
Community contributions and feedback

Screenshots

See below for examples of the dashboard in action. These screenshots illustrate the core features and user experience of the IBKG platform.

AI Insights and Knowledge Graph

The left panel provides AI-powered insights, including trend predictions, anomaly detection, and actionable recommendations. The bottom-left bar chart compares the selected metric across industry peers, color-coded by performance. The right panel features an interactive knowledge graph, visualizing real relationships between departments (red) and business metrics (green) for the selected company. Users can drag nodes to explore dependencies and influences.

What-If Scenario

The What-If Scenario panel allows users to simulate the impact of changing a department's budget on key business metrics. Users can adjust the budget percentage and instantly see projected changes in revenue, costs, and other KPIs. Each metric is shown as a delta card, clearly displaying the current value, what-if value, and the percent change, color-coded for intuitive interpretation.

Name		Name	Last commit message	Last commit date
Latest commit History 25 Commits
dist		dist
docs/screenshots		docs/screenshots
public		public
src		src
.gitattributes		.gitattributes
.gitignore		.gitignore
.npmrc		.npmrc
.nvmrc		.nvmrc
README.md		README.md
directory_structure.md		directory_structure.md
environment.yml		environment.yml
index.html		index.html
init.sh		init.sh
package-lock.json		package-lock.json
package.json		package.json
project_plan.md		project_plan.md
render.yaml		render.yaml
setup.sh		setup.sh
vite.config.js		vite.config.js

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