Pharma Genetics ERP and BI Dashboard Development
Patricia Osorio
Pharma Genetics ERP
Overview
This repository contains the complete business management system for Genetics GACP-certified cultivation business. The system consists of two primary components:
Django ERP - Operational system for day-to-day business management
Plotly Dash BI Dashboard - Investor-facing analytics and business intelligence
The architecture implements a clear separation between operational and analytical workloads for optimal performance and scalability.
Architecture Overview
Component Details
1. Django ERP (Operational System)
Purpose: Handle all day-to-day business operations with real-time data entry and management.
Technology Stack:
Django 5.0+
PostgreSQL (Cloud SQL)
Firebase Auth (Authentication)
Django Admin (Primary UI)
Django REST Framework (Optional API)
Frontend: Next.Js (V0 Generated)
Key Apps:
core/ - Shared models (Location, Contact, Currency, Settings)genetics/ - Strain catalog and genetic profilescultivation/ - Mother plant management, production batches, clone trackinginventory/ - Clone stock levels, movements, alertssales/ - Orders, customers, invoices, paymentspurchasing/ - Suppliers, purchase orders, expenseshr/ - Payroll, employees, attendanceaccounting/ - General ledger, journal entries, tax managementDatabase Design:
Normalized schema (3NF) for data integrity
Foreign key constraints
Audit trails (created_at, updated_at, updated_by)
Soft deletes where applicable
Users:
Internal staff (cultivation managers, sales reps, accountants)
Primary interaction via Django Admin interface
Real-time CRUD operations
2. ETL Pipeline (Data Synchronization)
Purpose: Extract operational data from Django ERP and load it into BigQuery for analytics.
Technology Stack:
Google Cloud Functions (Python 3.11)
Cloud Scheduler (Cron jobs)
Cloud SQL Proxy (Secure DB access)
BigQuery Python Client
Pipeline Architecture:
Schedule:
Daily Sync: TBC
Incremental: Only sync changed records (based on
updated_at)Full Refresh: TBC
Data Quality Checks:
Row count validation (source vs destination)
Foreign key integrity checks
Business rule validations
Duplicate detection
3. BigQuery Data Warehouse
Purpose: Centralized analytical database optimized for complex queries and aggregations.
Schema Design:
-> TODO: create reasme schema with claude from sql tables we have.
4. Plotly Dash BI Dashboard
Purpose: Investor-facing analytics dashboard with interactive visualizations and financial projections.
Technology Stack:
Plotly Dash (Python framework)
Plotly Express / Plotly Graph Objects (Visualizations)
Dash Bootstrap Components (UI framework)
BigQuery Python Client (Data access)
Pandas (Data manipulation)
Key Features:
A. Executive Summary (Homepage)
TODO: Summary dashboard
B. Financial Performance
P&L Statement (monthly/quarterly/annual)
Cash Flow Waterfall
Gross Margin by Product Tier
Break-even Analysis
Unit Economics Dashboard
C. Production Analytics
Clone Production by Strain
Mother Plant Utilization
Batch Success Rates
Production Cycle Times
Capacity Planning Scenarios
D. Sales Analytics
Customer Tier Analysis
Top Customers by Revenue
Average Order Value by Tier
Sales Pipeline (if applicable)
Geographic Distribution
E. Investor Reports
Sources & Uses of Funds
ROI Projections
Payback Period Calculations
Scenario Analysis (conservative/base/optimistic)
Export to PDF functionality
Authentication:
Firebase Auth integration
Role-based access (Investors see different views than management)
Read-only access to data (no write operations)
Performance Optimization:
Query result caching (Redis or in-memory)
Materialized views in BigQuery (pre-aggregated data)
Lazy loading of heavy visualizations
Date range filters to limit data volume
Architecture Flow:
Navigation Menu
Platform
Solutions
Resources
Open Source
Enterprise
patosorio / pharma-genetics-erp Public
upload hr, inventory, pricing, sales, taxes mdules#2
Merged
Dec 1, 2025Dec 1, 2025
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upload hr, inventory, pricing, sales, taxes mdules
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Posted Apr 10, 2026
Developed an ERP and BI dashboard for a genetics cultivation business.
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Dec 1, 2025 - Apr 1, 2026
