Introduction and Business Understanding

Business Context 🏢

SPC’s data management team faces several challenges in processing operational logbook fisheries data. This chapter explores the current situation and sets the foundation for automation.

Current Process Overview 📋

%%{init: {'themeVariables': { 'fontSize': '22px' }}}%%
flowchart LR
  A[Manual Email Reception] --> B[Excel Format Variations]
  B --> C[Manual Processing]
  C --> D[Quality Issues]
  D --> E[Delayed Analysis]
  E --> F[Resource Intensive]

Current Challenges 🔍

The existing process involves several pain points:

• 📧 Manual email handling and file management
• 📊 Various Excel formats requiring individual attention
• ⏱️ Time-consuming manual processing steps
• ❌ Inconsistent validation procedures
• 🤹 Limited automation capabilities

User Stories 👥

1. Data Reception Automation 🔄

As a data management staff member, I want to automate the reception of fisheries data.

• 📫 Current: Manual email processing
• 🎯 Desired: Automated file reception
• ✨ Benefits: Reduced delays and handling time

➡️ See implementation details

2. Database Loading 💾

As a data manager, I need automated database loading.

• 📑 Current: Manual Excel processing
• 🎯 Desired: Automated database loading
• ✨ Benefits: Faster, more reliable processing

➡️ See technical architecture

3. Quality Assurance 🎯

As a data quality analyst, I want automated checking.

• 👁️ Current: Manual inspection
• 🎯 Desired: Automated validation
• ✨ Benefits: Consistent quality control

➡️ See data validation approach

Business Requirements 📋

Functional Requirements ⚙️

1. Data Reception 📥
   • Automated file reception system
   • Format validation
   • Secure transfer protocols
2. Processing 🔄
   • Automated data extraction
   • Format standardization
   • Error handling
3. Storage 💾
   • SQL Server database
   • Data versioning
   • Backup procedures

Non-Functional Requirements 🎯

1. Performance ⚡
   • Processing time < 2 hours
   • 99.9% uptime
   • Real-time monitoring
2. Security 🔒
   • Data encryption
   • Access control
   • Audit logging
3. Usability 👥
   • Intuitive interface
   • Clear error messages
   • Documentation

Success Criteria 🎯

• ⏱️ 90% reduction in processing time
• 📊 99% data accuracy rate
• 💪 80% reduction in manual effort
• 📈 100% data traceability
• 🔄 Real-time processing capability

➡️ Next Chapter: Data Reception and Understanding