Data Model - Item Detail

Item Detail Overview

The Item Detail data model defines the structure for product and service information. This model encapsulates item specifications, pricing, and detailed product information.

Data Model Structure

Parameter	Type	Description
name	String	Product or service name for transaction identification Format: UTF-8 encoded string Usage: Item identification, transaction records, and reporting Examples: "MacBook Pro", "T-shirt", "Consultation Service"
quantity	Number	Number of items or units in the transaction Format: Integer value (no decimal places) Usage: Inventory tracking, order fulfillment, and quantity validation Examples: 1, 20, 100
price	Number	Unit price for the item or service Format: Numeric value with appropriate decimal places Usage: Price calculation, total amount validation, and financial reporting Examples: 9000.28, 120.00, 500.00

Format Specifications

Quantity Format

• Format: Integer values only (no decimal places)
• Range: Positive integers greater than 0
• Examples: 1, 20, 100, 1000

Price Format

• Format: Numeric values with appropriate decimal places
• Precision: Varies by currency (see currency-specific requirements)
• Examples: 9000.28, 120.00, 500.00

Implementation Examples

{
  "name": "MacBook Pro 14-inch",
  "quantity": 1,
  "price": 9000.28
}

{
  "name": "Premium Cotton T-shirt",
  "quantity": 2,
  "price": 120.00
}

{
  "name": "Professional Consultation Service",
  "quantity": 1,
  "price": 500.00
}

{
  "name": "Office Supplies Package",
  "quantity": 100,
  "price": 25.50
}

Business Applications

E-commerce Transactions

• Product Catalog: Detailed product information for customer reference
• Order Management: Item-level tracking for order fulfillment
• Inventory Control: Quantity management and stock updates
• Pricing Strategy: Dynamic pricing and promotional calculations

Service Transactions

• Service Description: Clear identification of services provided
• Time Tracking: Quantity representing hours or service units
• Rate Management: Price per unit of service
• Billing Accuracy: Precise billing based on service details

Financial Reporting

• Revenue Analysis: Item-level revenue tracking and analysis
• Sales Performance: Product and service performance metrics
• Tax Calculation: Accurate tax calculation based on item details
• Audit Trail: Complete transaction history for compliance

Data Validation and Quality

Name Validation

• Length Limits: Reasonable length limits for product names
• Character Validation: Valid UTF-8 characters only
• Content Filtering: Appropriate content for business transactions
• Consistency: Consistent naming conventions across transactions

Quantity Validation

• Positive Values: Quantities must be positive integers
• Maximum Limits: Reasonable maximum quantities to prevent errors
• Inventory Check: Verify against available inventory where applicable
• Business Rules: Enforce business-specific quantity rules

Price Validation

• Positive Values: Prices must be positive numbers
• Currency Format: Prices must match currency-specific format requirements
• Range Validation: Prices within reasonable business ranges
• Precision Rules: Appropriate decimal precision for currency

Integration Considerations

Order Management Systems

• Item Synchronization: Real-time item data synchronization
• Inventory Updates: Automatic inventory updates based on transactions
• Price Consistency: Maintain price consistency across systems
• Catalog Management: Centralized product catalog management

Financial Systems

• GL Integration: General ledger integration for financial reporting
• Tax Calculation: Automated tax calculation based on item details
• Revenue Recognition: Proper revenue recognition for different item types
• Cost Analysis: Item-level cost analysis and profitability tracking

Reporting and Analytics

• Sales Analytics: Item-level sales performance analysis
• Customer Insights: Customer preference analysis based on item details
• Trend Analysis: Product and service trend identification
• Forecasting: Demand forecasting based on historical item data