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Expand to Business Analytics: Add Customer, Sales, and KPI models

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Major expansion from fraud detection to comprehensive business analytics:

DATABASE CHANGES:
- Renamed database from 'fraud_detection' to 'business_analytics'
- Renamed user from 'fraud_analyst' to 'data_analyst'
- Expanded from 20 to 39 tables across 4 business models

NEW MODELS (19 tables):
1. Customer Analytics (5 tables):
   - customer_segments, customer_lifetime_value, churn_predictions
   - customer_satisfaction, engagement_metrics

2. Sales & Revenue Analytics (6 tables):
   - product_catalog, sales_transactions, sales_targets
   - sales_performance, revenue_forecasts

3. KPI & Metrics (8 tables):
   - kpi_definitions, daily_metrics, monthly_summaries
   - trend_analysis, dashboard_snapshots
   - report_definitions, report_executions, data_quality_checks

DATA GENERATION:
- Extended generate_data.sh with 6 new steps (now 15 total)
- Added CLV calculations for all customers
- Added churn predictions based on transaction recency
- Added 30K customer satisfaction surveys
- Added 1M sales transactions linked to 24 products
- Added 90 days of daily KPI metrics
- Added 24 months of business summaries

SQL EXERCISES (3 new levels):
- Level 2: Customer Analytics (10 exercises + 3 challenges)
- Level 3: Sales & Revenue Analysis (12 exercises + 3 challenges)
- Level 4: KPI Dashboards & Metrics (12 exercises + 3 challenges)

DOCUMENTATION:
- Updated README.md with business analytics focus
- Updated QUICKSTART.md with new data generation steps
- Updated SETUP_COMPLETE.md with 39-table architecture
- Added DATA_MODELS.md with complete model specifications
- Added WHATS_NEW.md with migration guide

SEED DATA:
- Added 8 customer segments (VIP, High Value, etc.)
- Added 24 products across 5 categories
- Added 16 KPI definitions across 4 categories
- Added 8 standard report definitions

All changes maintain idempotency and backward compatibility with existing fraud detection functionality.
This commit is contained in:
Alphaeus Mote
2025-10-23 14:17:12 -04:00
parent b30733ccad
commit aa803bd3bd
14 changed files with 2762 additions and 132 deletions
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schema/02-seed-data.sql
+109
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@@ -5,6 +5,27 @@
-- ============================================================================
-- Clear existing reference data (in reverse dependency order)
-- New analytics tables
TRUNCATE TABLE report_executions CASCADE;
TRUNCATE TABLE report_definitions RESTART IDENTITY CASCADE;
TRUNCATE TABLE data_quality_checks RESTART IDENTITY CASCADE;
TRUNCATE TABLE dashboard_snapshots RESTART IDENTITY CASCADE;
TRUNCATE TABLE trend_analysis RESTART IDENTITY CASCADE;
TRUNCATE TABLE monthly_summaries RESTART IDENTITY CASCADE;
TRUNCATE TABLE daily_metrics RESTART IDENTITY CASCADE;
TRUNCATE TABLE kpi_definitions RESTART IDENTITY CASCADE;
TRUNCATE TABLE revenue_forecasts RESTART IDENTITY CASCADE;
TRUNCATE TABLE sales_performance RESTART IDENTITY CASCADE;
TRUNCATE TABLE sales_targets RESTART IDENTITY CASCADE;
TRUNCATE TABLE sales_transactions RESTART IDENTITY CASCADE;
TRUNCATE TABLE product_catalog RESTART IDENTITY CASCADE;
TRUNCATE TABLE engagement_metrics RESTART IDENTITY CASCADE;
TRUNCATE TABLE customer_satisfaction RESTART IDENTITY CASCADE;
TRUNCATE TABLE churn_predictions RESTART IDENTITY CASCADE;
TRUNCATE TABLE customer_lifetime_value RESTART IDENTITY CASCADE;
TRUNCATE TABLE customer_segments RESTART IDENTITY CASCADE;
-- Existing tables
TRUNCATE TABLE suspicious_activity_reports CASCADE;
TRUNCATE TABLE case_alerts CASCADE;
TRUNCATE TABLE case_transactions CASCADE;
@@ -254,3 +275,91 @@ COMMENT ON FUNCTION generate_fraud_score IS 'Calculates fraud risk score based o
COMMENT ON FUNCTION update_account_balance IS 'Automatically updates account balance after transaction';
COMMENT ON FUNCTION check_suspicious_transaction IS 'Generates alerts for suspicious transactions';
-- ============================================================================
-- SEED DATA FOR NEW ANALYTICS TABLES
-- ============================================================================
-- Customer Segments
INSERT INTO customer_segments (segment_name, segment_description, min_clv, max_clv) VALUES
('VIP', 'Very Important Person - Highest value customers', 50000, NULL),
('High Value', 'High spending customers with strong loyalty', 10000, 49999),
('Medium Value', 'Regular customers with moderate spending', 2000, 9999),
('Low Value', 'Occasional customers with low spending', 500, 1999),
('At Risk', 'Previously active customers showing decline', NULL, NULL),
('New Customer', 'Recently acquired customers (< 90 days)', NULL, NULL),
('Dormant', 'Inactive customers (> 180 days)', NULL, NULL),
('Churned', 'Lost customers who have not transacted in 365+ days', NULL, NULL);
-- Product Catalog (Sample Products)
INSERT INTO product_catalog (product_name, product_category, product_subcategory, unit_price, cost_price, margin_percentage, is_active, launch_date) VALUES
-- Banking Products
('Premium Checking Account', 'Banking', 'Checking', 0.00, 0.00, 0.00, TRUE, '2020-01-01'),
('Basic Savings Account', 'Banking', 'Savings', 0.00, 0.00, 0.00, TRUE, '2020-01-01'),
('High-Yield Savings', 'Banking', 'Savings', 0.00, 0.00, 0.00, TRUE, '2021-06-01'),
('Business Checking', 'Banking', 'Business', 15.00, 5.00, 66.67, TRUE, '2020-01-01'),
('Student Checking', 'Banking', 'Checking', 0.00, 0.00, 0.00, TRUE, '2020-01-01'),
-- Credit Cards
('Platinum Credit Card', 'Credit', 'Premium', 99.00, 20.00, 79.80, TRUE, '2020-01-01'),
('Gold Credit Card', 'Credit', 'Standard', 49.00, 15.00, 69.39, TRUE, '2020-01-01'),
('Cash Back Card', 'Credit', 'Rewards', 0.00, 10.00, -100.00, TRUE, '2021-01-01'),
('Travel Rewards Card', 'Credit', 'Rewards', 95.00, 25.00, 73.68, TRUE, '2021-03-01'),
('Business Credit Card', 'Credit', 'Business', 75.00, 20.00, 73.33, TRUE, '2020-06-01'),
-- Loans
('Personal Loan', 'Lending', 'Personal', 0.00, 0.00, 0.00, TRUE, '2020-01-01'),
('Auto Loan', 'Lending', 'Auto', 0.00, 0.00, 0.00, TRUE, '2020-01-01'),
('Home Mortgage', 'Lending', 'Mortgage', 0.00, 0.00, 0.00, TRUE, '2020-01-01'),
('Small Business Loan', 'Lending', 'Business', 0.00, 0.00, 0.00, TRUE, '2020-01-01'),
-- Investment Products
('Index Fund', 'Investment', 'Mutual Funds', 0.00, 0.00, 0.00, TRUE, '2020-01-01'),
('Bond Fund', 'Investment', 'Mutual Funds', 0.00, 0.00, 0.00, TRUE, '2020-01-01'),
('Retirement Account (IRA)', 'Investment', 'Retirement', 0.00, 0.00, 0.00, TRUE, '2020-01-01'),
('401k Plan', 'Investment', 'Retirement', 0.00, 0.00, 0.00, TRUE, '2020-01-01'),
-- Services
('Wire Transfer', 'Services', 'Transfers', 25.00, 5.00, 80.00, TRUE, '2020-01-01'),
('International Transfer', 'Services', 'Transfers', 45.00, 10.00, 77.78, TRUE, '2020-01-01'),
('Overdraft Protection', 'Services', 'Protection', 35.00, 5.00, 85.71, TRUE, '2020-01-01'),
('Safe Deposit Box', 'Services', 'Security', 75.00, 20.00, 73.33, TRUE, '2020-01-01'),
('Financial Advisory', 'Services', 'Advisory', 150.00, 50.00, 66.67, TRUE, '2021-01-01'),
('Mobile Banking Premium', 'Services', 'Digital', 9.99, 2.00, 79.98, TRUE, '2022-01-01');
-- KPI Definitions
INSERT INTO kpi_definitions (kpi_name, kpi_description, kpi_category, calculation_formula, target_value, threshold_warning, threshold_critical, unit_of_measure, refresh_frequency, is_active) VALUES
-- Sales KPIs
('Daily Revenue', 'Total revenue generated per day', 'SALES', 'SUM(amount) FROM transactions WHERE DATE(transaction_date) = CURRENT_DATE', 500000, 400000, 300000, 'USD', 'DAILY', TRUE),
('Monthly Revenue', 'Total revenue for the month', 'SALES', 'SUM(amount) FROM transactions WHERE MONTH(transaction_date) = CURRENT_MONTH', 15000000, 12000000, 10000000, 'USD', 'DAILY', TRUE),
('Average Transaction Value', 'Average value per transaction', 'SALES', 'AVG(amount) FROM transactions', 150, 100, 75, 'USD', 'DAILY', TRUE),
('Transactions Per Day', 'Number of transactions per day', 'SALES', 'COUNT(*) FROM transactions WHERE DATE(transaction_date) = CURRENT_DATE', 10000, 7500, 5000, 'Count', 'DAILY', TRUE),
-- Customer KPIs
('New Customers', 'New customer acquisitions', 'CUSTOMER', 'COUNT(*) FROM customers WHERE registration_date >= CURRENT_DATE - 30', 1000, 750, 500, 'Count', 'DAILY', TRUE),
('Customer Churn Rate', 'Percentage of customers churning', 'CUSTOMER', '(Churned / Total) * 100', 5, 7, 10, 'Percentage', 'WEEKLY', TRUE),
('Customer Lifetime Value', 'Average CLV across all customers', 'CUSTOMER', 'AVG(clv_score) FROM customer_lifetime_value', 5000, 4000, 3000, 'USD', 'WEEKLY', TRUE),
('Net Promoter Score', 'Customer satisfaction metric', 'CUSTOMER', 'AVG(nps_score) FROM customer_satisfaction', 50, 30, 10, 'Score', 'WEEKLY', TRUE),
('Customer Engagement Score', 'Average engagement across customers', 'CUSTOMER', 'AVG(engagement_score) FROM engagement_metrics', 75, 60, 45, 'Score', 'DAILY', TRUE),
-- Operational KPIs
('Transaction Success Rate', 'Percentage of successful transactions', 'OPERATIONAL', '(Successful / Total) * 100', 99, 97, 95, 'Percentage', 'HOURLY', TRUE),
('Average Response Time', 'System response time', 'OPERATIONAL', 'AVG(response_time_ms)', 200, 500, 1000, 'Milliseconds', 'REALTIME', TRUE),
('Fraud Detection Rate', 'Percentage of fraud caught', 'OPERATIONAL', '(Detected / Total Fraud) * 100', 95, 90, 85, 'Percentage', 'DAILY', TRUE),
('Alert Resolution Time', 'Average time to resolve alerts', 'OPERATIONAL', 'AVG(resolution_time_hours)', 24, 48, 72, 'Hours', 'DAILY', TRUE),
-- Financial KPIs
('Gross Margin', 'Overall profit margin', 'FINANCIAL', '((Revenue - Cost) / Revenue) * 100', 75, 65, 55, 'Percentage', 'DAILY', TRUE),
('Customer Acquisition Cost', 'Cost to acquire new customer', 'FINANCIAL', 'Marketing Spend / New Customers', 50, 75, 100, 'USD', 'WEEKLY', TRUE),
('Return on Investment', 'ROI on marketing campaigns', 'FINANCIAL', '((Revenue - Cost) / Cost) * 100', 300, 200, 100, 'Percentage', 'WEEKLY', TRUE);
-- Report Definitions
INSERT INTO report_definitions (report_name, report_description, report_category, output_format, schedule_frequency, is_active) VALUES
('Daily Sales Summary', 'Daily sales performance report', 'Sales', 'PDF', 'Daily at 6 AM', TRUE),
('Weekly Customer Analytics', 'Customer behavior and segmentation analysis', 'Customer', 'EXCEL', 'Weekly on Monday', TRUE),
('Monthly Financial Summary', 'Comprehensive monthly financial report', 'Financial', 'PDF', 'Monthly on 1st', TRUE),
('Fraud Detection Report', 'Daily fraud alerts and cases', 'Risk', 'PDF', 'Daily at 8 AM', TRUE),
('KPI Dashboard', 'Executive KPI dashboard', 'Executive', 'HTML', 'Daily at 7 AM', TRUE),
('Customer Churn Analysis', 'At-risk customer identification', 'Customer', 'EXCEL', 'Weekly on Friday', TRUE),
('Product Performance', 'Product sales and profitability analysis', 'Sales', 'EXCEL', 'Monthly on 5th', TRUE),
('Data Quality Report', 'Data validation and quality metrics', 'Operations', 'CSV', 'Daily at 5 AM', TRUE);