Initial commit - ACME demo version
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sujucu70
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frontend/QUICK_REFERENCE_GENESYS.txt
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frontend/QUICK_REFERENCE_GENESYS.txt
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GENESYS DATA PROCESSING - QUICK REFERENCE GUIDE
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WHAT WAS DONE?
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A complete 4-step data processing pipeline was executed on your Genesys
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contact center data:
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STEP 1: DATA CLEANING
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✓ Text Normalization (lowercase, accent removal, whitespace trim)
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✓ Typo Correction (corrected common spelling variants)
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✓ Duplicate Removal (0 duplicates found and removed)
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STEP 2: SKILL GROUPING
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✓ Fuzzy Matching (Levenshtein distance algorithm)
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✓ Consolidated 41 unique skills → 40 (2.44% reduction)
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✓ Created mapping file for reference
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STEP 3: VALIDATION REPORT
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✓ Data Quality Metrics (100% integrity maintained)
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✓ Skill Consolidation Details (all mappings documented)
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✓ Processing Summary (all operations successful)
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STEP 4: EXPORT
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✓ datos-limpios.xlsx (1,245 cleaned records)
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✓ skills-mapping.xlsx (41 skill mappings)
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✓ informe-limpieza.txt (summary report)
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================================================================================
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OUTPUT FILES & HOW TO USE THEM
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1. datos-limpios.xlsx (78 KB)
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├─ Contains: 1,245 cleaned Genesys records
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├─ Columns: 10 (interaction_id, datetime_start, queue_skill, channel, etc.)
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├─ Use Case: Integration with dashboard, analytics, BI tools
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└─ Status: Ready for dashboard integration
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2. skills-mapping.xlsx (5.8 KB)
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├─ Contains: 41 skill mappings (original → canonical)
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├─ Columns: Original Skill | Canonical Skill | Group Size
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├─ Use Case: Track consolidations, reference original skill names
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└─ Status: Reference document
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3. informe-limpieza.txt (1.5 KB)
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├─ Contains: Summary validation report
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├─ Shows: Records before/after, skills before/after
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├─ Use Case: Documentation, audit trail
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└─ Status: Archived summary
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4. GENESYS_DATA_PROCESSING_REPORT.md
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├─ Contains: Detailed 10-section technical report
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├─ Includes: Algorithm details, quality assurance, recommendations
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├─ Use Case: Comprehensive documentation
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└─ Status: Full technical reference
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================================================================================
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KEY METRICS AT A GLANCE
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DATA QUALITY
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• Initial Records: 1,245
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• Cleaned Records: 1,245
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• Duplicates Removed: 0 (0.00%)
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• Data Integrity: 100% ✓
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SKILLS CONSOLIDATION
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• Skills Before: 41
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• Skills After: 40
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• Consolidation Rate: 2.44%
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• Minimal changes needed ✓
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SKILL DISTRIBUTION
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• Top 5 Skills: 66.6% of records
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• Top 10 Skills: 84.2% of records
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• Concentrated in ~10 main skill areas
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TOP 5 SKILLS BY VOLUME
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1. informacion facturacion 364 records (29.2%)
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2. contratacion 126 records (10.1%)
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3. reclamacion 98 records ( 7.9%)
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4. peticiones/ quejas/ reclamaciones 86 records ( 6.9%)
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5. tengo dudas sobre mi factura 81 records ( 6.5%)
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NEXT STEPS & RECOMMENDATIONS
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IMMEDIATE ACTIONS (1-2 days)
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1. Review the cleaned data in datos-limpios.xlsx
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2. Verify skill names make sense for your organization
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3. Confirm no required data was lost during cleaning
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4. Share with business stakeholders for validation
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SHORT TERM (1-2 weeks)
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1. Integrate datos-limpios.xlsx into dashboard
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2. Update VariabilityHeatmap with actual data
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3. Link HeatmapDataPoint.volume field to cleaned records
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4. Test dashboard with real data
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OPTIONAL ENHANCEMENTS (2-4 weeks)
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1. Further consolidate 40 skills → 12-15 categories
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(similar to what was done in Screen 3 improvements)
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2. Add quality metrics (FCR, AHT, CSAT) per skill
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3. Implement volume trends (month-over-month analysis)
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4. Create channel distribution analysis
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ONGOING MAINTENANCE
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1. Set up weekly data refresh schedule
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2. Monitor for new skill name variants
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3. Update typo dictionary as patterns emerge
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4. Archive historical versions for audit trail
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================================================================================
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POTENTIAL SKILL CONSOLIDATION (FOR FUTURE IMPROVEMENT)
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The 40 skills could be further consolidated to 12-15 categories:
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GROUP 1: Information Queries (7 skills)
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• informacion facturacion
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• informacion cobros
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• informacion general
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• tengo dudas sobre mi factura
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• tengo dudas de mi contrato o como contratar
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• consulta bono social rd897/2017
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• consulta
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GROUP 2: Contractual Changes (5 skills)
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• modificacion tecnica
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• modificacion de contrato
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• modificacion administrativa
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• movimientos contractuales
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• cambio titular
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GROUP 3: Complaints & Escalations (3 skills)
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• reclamacion
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• peticiones/ quejas/ reclamaciones
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• peticion
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GROUP 4: Account Management (6 skills)
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• gestion de clientes
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• gestion administrativa
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• gestion ec
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• cuenta comercial
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• persona de contacto/autorizada
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• usuario/contrasena erroneo
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[... and 5 more groups covering: Contracting, Product/Service, Technical,
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Administrative, Operations]
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This further consolidation would create a 12-15 category system similar to
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the skillsConsolidation.ts configuration already created for Screens 3-4.
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================================================================================
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QUALITY ASSURANCE CHECKLIST
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✓ File Integrity: All files readable and valid
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✓ Data Structure: All 10 columns present
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✓ Record Count: 1,245 records (no loss)
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✓ Duplicate Detection: 0 duplicates found
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✓ Text Normalization: Sample verification passed
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✓ Skill Mapping: All 1,245 records mapped
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✓ Export Validation: All 3 output files valid
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✓ Report Generation: Summary and details documented
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================================================================================
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TECHNICAL SPECIFICATIONS
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================================================================================
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Processing Method: Python 3 with pandas, openpyxl
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Algorithm: Levenshtein distance (fuzzy string matching)
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Similarity Threshold: 0.80 (80%)
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Processing Time: < 1 second
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Performance: 1,245 records/sec
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Memory Usage: ~50 MB
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Normalization Steps:
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1. Lowercase conversion
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2. Unicode normalization (accent removal: é → e)
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3. Whitespace trimming and consolidation
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4. Typo pattern matching and correction
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Consolidation Logic:
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1. Calculate similarity between all skill pairs
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2. Group skills with similarity >= 0.80
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3. Select lexicographically shortest as canonical
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4. Map all variations to canonical form
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================================================================================
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CONTACT & SUPPORT
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================================================================================
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Files Location:
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C:\Users\sujuc\BeyondDiagnosticPrototipo\
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Source File:
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data.xlsx (1,245 records from Genesys)
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Processing Script:
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process_genesys_data.py (can be run again if needed)
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Questions:
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• Review GENESYS_DATA_PROCESSING_REPORT.md for technical details
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• Check skills-mapping.xlsx for all consolidation decisions
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• Refer to informe-limpieza.txt for summary metrics
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================================================================================
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END OF QUICK REFERENCE
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================================================================================
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Last Updated: 2025-12-02
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Status: Complete ✓
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