Munu Data Store (MDS)
The canonical data model for hospitality and retail analytics
Overview
Munu provides a comprehensive platform for running restaurants, bars, nightclubs, cafés, and retail venues. The platform covers the full operational stack: point of sale, master data management, sales transactions, inventory control, booking and reservations, and waste tracking. All components are designed to work together with shared entities and consistent data structures.
The Munu Data Store (MDS) extends this foundation by integrating external data sources into the same canonical model. Labour data from workforce management systems (Planday, Quinyx, Personalkollen), and in future releases: weather data, customer satisfaction scores, and accounting figures. Each external source is mapped and curated to align with MDS entities, enabling correlation across all operational and contextual data.
The result is a unified data layer ready for analytics, reporting, and business intelligence without additional transformation or mapping work.
Data Domains
| Domain | Description | Documentation |
|---|---|---|
| Master Data | Core reference entities (customers, articles, revenue units, users) | masterdata/ |
| Sales Data | Transaction data including orders, line items, and payments | salesdata/ |
| Labour Data | Workforce management: shifts, costs, and scheduling | labourdata/ |
| Inventory Data | Stock management, recipes, suppliers, and transactions | inventorydata/ |
| Booking | Reservation and table management | booking/ |
| Article Waste | Waste tracking and reporting | articlewaste/ |
Design Principles
- Source System Agnostic - Models accommodate data from any source system
- Master Data References - Consistent linking via canonical IDs across domains
- Separation of Concerns - Structural data separate from transactional data
- Daily Granularity - Time-based data organized by year/month/day
- snake_case Convention - All JSON property names use snake_case
Quick Links
Master Data
- Customers - Customer/tenant definitions
- Revenue Units - Outlets, restaurants, stores
- Articles - Products and menu items
- Users - System users and employees
Transactional Data
- Orders - Sales transactions
- Shifts - Labour and scheduling data
- Inventory Transactions - Stock movements
Getting Started
Each data domain documentation includes:
- Data Model Specification - Entity definitions and field descriptions
- Storage Structure - File organization and naming conventions
- Example JSON - Sample data in the canonical format
- Validation Rules - Data quality requirements
Version
Current Version: 1.0 Last Updated: 2025-12-10
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