ujusum:3-codage:2-sprints:9-sprint-9
Table des matières
Sprint 9-A.1 — Business Intelligence Core & Data Warehouse
Objectif
Construire la fondation analytique Enterprise unifiée.
Cette couche permet de centraliser :
CRM Properties Reservations Finance Marketing Loyalty Marketplace
dans un Data Warehouse unique destiné au reporting, aux KPI et à la Business Intelligence.
À l'issue de cette étape :
✓ Data Warehouse ✓ Fact Tables ✓ Dimensions ✓ ETL Pipelines ✓ KPI Engine ✓ Reporting Core ✓ Enterprise Analytics Foundation
Architecture cible
Operational Systems ├── CRM ├── Property ├── Reservation ├── Finance ├── Marketing ├── Loyalty └── Marketplace ↓ ETL / ELT Layer ↓ Data Warehouse ├── Facts ├── Dimensions ├── Aggregations └── KPI Engine ↓ Reporting ↓ Executive Dashboards
Sprint 9-A.1-A
Data Warehouse Schema
Étape 1 — DWFactReservation
Ajouter dans schema.prisma
model DWFactReservation {
id String
@id
@default(uuid())
tenantId String
reservationId String
customerId String
propertyId String
reservationDate DateTime
checkInDate DateTime
checkOutDate DateTime
nights Int
guests Int
grossRevenue Decimal
@db.Decimal(14,2)
netRevenue Decimal
@db.Decimal(14,2)
status String
createdAt DateTime
@default(now())
@@index([tenantId])
@@index([reservationDate])
@@index([propertyId])
@@index([customerId])
}
Étape 2 — DWFactRevenue
Ajouter
model DWFactRevenue {
id String
@id
@default(uuid())
tenantId String
revenueDate DateTime
propertyId String?
revenueType RevenueType
amount Decimal
@db.Decimal(14,2)
currency String
createdAt DateTime
@default(now())
@@index([tenantId])
@@index([revenueDate])
@@index([revenueType])
}
Étape 3 — DWFactMarketing
Ajouter
model DWFactMarketing {
id String
@id
@default(uuid())
tenantId String
campaignId String
campaignDate DateTime
impressions Int
opens Int
clicks Int
conversions Int
revenueAttributed Decimal?
@db.Decimal(14,2)
@@index([tenantId])
@@index([campaignDate])
}
Étape 4 — DWFactLoyalty
Ajouter
model DWFactLoyalty {
id String
@id
@default(uuid())
tenantId String
customerId String
transactionDate DateTime
pointsEarned Int
pointsRedeemed Int
rewardValue Decimal?
@db.Decimal(14,2)
@@index([tenantId])
@@index([transactionDate])
}
Étape 5 — DWFactReferral
Ajouter
model DWFactReferral {
id String
@id
@default(uuid())
tenantId String
advocateId String
referralDate DateTime
referrals Int
conversions Int
revenueGenerated Decimal?
@db.Decimal(14,2)
@@index([tenantId])
@@index([referralDate])
}
Sprint 9-A.1-B
Dimensions
Étape 6 — DWDimDate
model DWDimDate {
dateKey String
@id
fullDate DateTime
day Int
week Int
month Int
quarter Int
year Int
isWeekend Boolean
}
Étape 7 — DWDimCustomer
model DWDimCustomer {
customerId String
@id
segment String?
status String?
country String?
city String?
customerScore Float?
lifetimeValue Decimal?
@db.Decimal(14,2)
}
Étape 8 — DWDimProperty
model DWDimProperty {
propertyId String
@id
propertyType String?
category String?
city String?
country String?
capacity Int?
propertyScore Float?
}
Étape 9 — DWDimChannel
model DWDimChannel {
channelId String
@id
name String
category String
active Boolean
}
Étape 10 — Migration
npx prisma migrate dev \
--name bi_datawarehouse_core
Sprint 9-A.1-C
ETL Pipelines
Étape 11 — Structure
src/modules/analytics/etl ├── reservation-etl ├── revenue-etl ├── marketing-etl ├── loyalty-etl ├── referral-etl └── etl.module.ts
Étape 12 — Services
ReservationETLService RevenueETLService MarketingETLService LoyaltyETLService ReferralETLService DataWarehouseService
Étape 13 — Pipeline
Extract ↓ Transform ↓ Load ↓ Validate ↓ Aggregate
Étape 14 — Méthodes
extract() transform() load() validate() rebuildWarehouse()
Sprint 9-A.1-D
KPI Engine
Étape 15 — KPIEntity
Ajouter
model KPIEntity {
id String
@id
@default(uuid())
tenantId String
code String
name String
category KPICategory
formula String
active Boolean
@default(true)
createdAt DateTime
@default(now())
@@unique([tenantId, code])
@@index([tenantId])
}
Étape 16 — KPIValue
Ajouter
model KPIValue {
id String
@id
@default(uuid())
tenantId String
kpiCode String
periodDate DateTime
value Decimal
@db.Decimal(18,4)
createdAt DateTime
@default(now())
@@index([tenantId])
@@index([kpiCode])
}
Étape 17 — KPIs Standards
Revenue Occupancy ADR RevPAR Conversion Rate Customer LTV Retention Referral Revenue Marketing ROI
Étape 18 — KPIEngineService
Créer
kpi-engine.service.ts
Méthodes
calculateKPI() calculatePeriod() refreshKPIs() comparePeriods()
Sprint 9-A.1-E
Reporting Core
Étape 19 — ReportDefinition
Ajouter
model ReportDefinition {
id String
@id
@default(uuid())
tenantId String
name String
category ReportCategory
configuration Json
active Boolean
@default(true)
createdAt DateTime
@default(now())
@@index([tenantId])
}
Étape 20 — ReportExecution
Ajouter
model ReportExecution {
id String
@id
@default(uuid())
reportId String
executedAt DateTime
@default(now())
status ReportExecutionStatus
executionTimeMs Int?
fileUrl String?
@@index([reportId])
}
Étape 21 — Enums
enum KPICategory {
FINANCE
PROPERTY
CUSTOMER
MARKETING
LOYALTY
REFERRAL
}
enum ReportCategory {
EXECUTIVE
FINANCE
OPERATIONS
MARKETING
CRM
CUSTOM
}
enum ReportExecutionStatus {
PENDING
RUNNING
COMPLETED
FAILED
}
Étape 22 — ReportingService
Créer
reporting.service.ts
Supporter
PDF Excel CSV JSON
Sprint 9-A.1-F
Business Intelligence Module
Étape 23 — Structure
src/modules/business-intelligence ├── warehouse ├── etl ├── kpi ├── reporting ├── dashboards └── business-intelligence.module.ts
Étape 24 — Services
DataWarehouseService KPIEngineService ReportingService DashboardService AnalyticsAggregationService
Sprint 9-A.1-G
Executive Reporting
Étape 25 — Dashboards
Fournir
Executive Dashboard Revenue Dashboard Operations Dashboard CRM Dashboard Marketing Dashboard Growth Dashboard
Étape 26 — Agrégations
Calculer
Jour Semaine Mois Trimestre Année
Sprint 9-A.1-H
API BI
Étape 27 — Endpoints
GET /analytics/kpis GET /analytics/reports POST /analytics/reports GET /analytics/dashboard POST /analytics/warehouse/rebuild GET /analytics/warehouse/status
Étape 28 — Exemple
{
"revenue":1250000,
"occupancy":84.7,
"revpar":142.3,
"customerLtv":5240,
"marketingRoi":3.8
}
Sprint 9-A.1-I
Gouvernance
Étape 29 — Permissions
analytics.read analytics.kpi.read analytics.report.read analytics.report.create analytics.warehouse.manage analytics.admin
Étape 30 — Audit
WAREHOUSE_REBUILD_STARTED WAREHOUSE_REBUILD_COMPLETED KPI_REFRESHED REPORT_GENERATED DASHBOARD_VIEWED ETL_EXECUTED
Étape 31 — Jobs
Toutes les heures Incremental ETL Toutes les nuits Warehouse Refresh KPI Refresh Aggregation Refresh Report Cache Refresh
Préparation Sprint 9-A.2
Compatible avec :
Predictive Analytics Data Science Machine Learning Executive AI Forecast Engine
Définition de terminé
Le Sprint 9-A.1 est terminé lorsque :
✓ Data Warehouse créé ✓ Fact Tables créées ✓ Dimensions créées ✓ ETL Pipelines créés ✓ KPI Engine créé ✓ Reporting Core créé ✓ Fondation BI Enterprise opérationnelle
Livrables
DWFactReservation DWFactRevenue DWFactMarketing DWFactLoyalty DWFactReferral DWDimDate DWDimCustomer DWDimProperty DWDimChannel KPIEntity KPIValue ReportDefinition ReportExecution DataWarehouseService KPIEngineService ReportingService Enterprise Analytics Foundation
Sprint 9-A.2 — Predictive Analytics & Forecast Engine
Objectif
Construire la couche analytique prédictive Enterprise.
Cette couche permet :
Prévisions Machine Learning Détection des tendances Prévisions de revenus Prévisions de demande Prévisions de churn IA décisionnelle
afin de transformer la Business Intelligence descriptive en plateforme analytique prédictive.
À l'issue de cette étape :
✓ Forecast Models ✓ Predictive KPIs ✓ Demand Forecast ✓ Revenue Forecast ✓ Churn Forecast ✓ AI Analytics ✓ Predictive Analytics Platform
Architecture cible
Data Warehouse ↓ Forecast Engine ├── Demand Forecasting ├── Revenue Forecasting ├── Occupancy Forecasting ├── Churn Forecasting ├── Marketing Forecasting ├── Loyalty Forecasting └── AI Analytics ↓ Predictive KPI Engine ↓ Executive Intelligence
Sprint 9-A.2-A
Extension Prisma
Étape 1 — ForecastModel
Ajouter dans schema.prisma
model ForecastModel {
id String
@id
@default(uuid())
tenantId String
code String
name String
modelType ForecastModelType
version String
active Boolean
@default(true)
accuracyScore Float?
lastTrainingAt DateTime?
createdAt DateTime
@default(now())
@@unique([tenantId, code])
@@index([tenantId])
}
Étape 2 — ForecastPrediction
Ajouter
model ForecastPrediction {
id String
@id
@default(uuid())
tenantId String
modelId String
forecastType ForecastType
predictionDate DateTime
targetDate DateTime
predictedValue Decimal
@db.Decimal(18,4)
confidenceScore Float?
createdAt DateTime
@default(now())
@@index([tenantId])
@@index([forecastType])
@@index([targetDate])
}
Étape 3 — PredictiveKPI
Ajouter
model PredictiveKPI {
id String
@id
@default(uuid())
tenantId String
code String
forecastDate DateTime
predictedValue Decimal
@db.Decimal(18,4)
actualValue Decimal?
@db.Decimal(18,4)
accuracy Float?
createdAt DateTime
@default(now())
@@index([tenantId])
@@index([code])
}
Étape 4 — AnalyticsInsight
Ajouter
model AnalyticsInsight {
id String
@id
@default(uuid())
tenantId String
category AnalyticsInsightCategory
severity InsightSeverity
title String
description String
recommendation String?
impactScore Float?
createdAt DateTime
@default(now())
@@index([tenantId])
@@index([category])
}
Étape 5 — ChurnPrediction
Ajouter
model ChurnPrediction {
customerId String
@id
churnProbability Float
riskLevel ChurnRiskLevel
expectedRevenueLoss Decimal?
@db.Decimal(14,2)
calculatedAt DateTime
@updatedAt
}
Étape 6 — Enums
Ajouter
enum ForecastModelType {
TIME_SERIES
REGRESSION
CLASSIFICATION
ENSEMBLE
AI_MODEL
}
enum ForecastType {
DEMAND
REVENUE
OCCUPANCY
BOOKINGS
CHURN
MARKETING
LOYALTY
}
enum AnalyticsInsightCategory {
DEMAND
REVENUE
CUSTOMER
PROPERTY
MARKETING
RISK
}
enum ChurnRiskLevel {
LOW
MEDIUM
HIGH
CRITICAL
}
Étape 7 — Migration
npx prisma migrate dev \
--name predictive_analytics
Sprint 9-A.2-B
Predictive Analytics Module
Étape 8 — Structure
src/modules/predictive-analytics ├── forecasting ├── revenue ├── demand ├── churn ├── kpis ├── insights └── predictive-analytics.module.ts
Étape 9 — Services
ForecastModelService DemandForecastService RevenueForecastService ChurnForecastService PredictiveKPIService AnalyticsInsightService PredictiveAnalyticsDashboardService
Sprint 9-A.2-C
Forecast Models
Étape 10 — ForecastModelService
Créer
forecast-model.service.ts
Supporter
ARIMA Prophet XGBoost Random Forest Neural Network
Étape 11 — Méthodes
trainModel() validateModel() deployModel() evaluateAccuracy() retrainModel()
Étape 12 — Cycle ML
Collect ↓ Train ↓ Validate ↓ Deploy ↓ Predict ↓ Monitor
Sprint 9-A.2-D
Demand Forecast
Étape 13 — DemandForecastService
Créer
demand-forecast.service.ts
Prévoir
Demand Searches Reservations Occupancy
Étape 14 — Horizons
7 jours 30 jours 90 jours 12 mois
Étape 15 — Variables
Seasonality Events Marketing Historical Demand Market Trends
Sprint 9-A.2-E
Revenue Forecast
Étape 16 — RevenueForecastService
Créer
revenue-forecast.service.ts
Prévoir
Revenue ADR RevPAR Marketplace Revenue Loyalty Revenue
Étape 17 — Méthodes
forecastRevenue() forecastADR() forecastRevPAR() forecastProfitability()
Étape 18 — Exemple
Revenue Forecast 30 jours ↓ 1.82 M€ Confidence 91%
Sprint 9-A.2-F
Churn Forecast
Étape 19 — ChurnForecastService
Créer
churn-forecast.service.ts
Analyser
Customer Activity Loyalty Reservations Support Marketing Engagement
Étape 20 — Méthodes
predictChurn() detectRiskCustomers() estimateRevenueLoss() recommendRetentionActions()
Étape 21 — Classification
0-25% Low 26-50% Medium 51-75% High 76-100% Critical
Sprint 9-A.2-G
Predictive KPI Engine
Étape 22 — PredictiveKPIService
Créer
predictive-kpi.service.ts
Générer
Forecast Revenue Forecast Occupancy Forecast LTV Forecast Retention Forecast Conversion
Étape 23 — Mesurer
Forecast Accuracy Prediction Drift Model Reliability
Sprint 9-A.2-H
AI Analytics
Étape 24 — AnalyticsInsightService
Créer
analytics-insight.service.ts
Générer
Opportunities Risks Growth Signals Demand Changes Revenue Alerts
Étape 25 — Exemples
Occupation +18% prévue ↓ Tarification dynamique recommandée
Churn VIP +12% ↓ Campagne rétention recommandée
Sprint 9-A.2-I
Dashboard Prédictif
Étape 26 — PredictiveAnalyticsDashboardService
Créer
predictive-analytics-dashboard.service.ts
Afficher
Forecasts AI Insights Churn Risks Revenue Outlook Demand Outlook
Étape 27 — Endpoints
GET /analytics/predictive GET /analytics/forecasts GET /analytics/churn GET /analytics/insights GET /analytics/models POST /analytics/models/train
Étape 28 — Exemple
{
"forecastRevenue":1820000,
"forecastOccupancy":87.4,
"forecastBookings":1240,
"highRiskCustomers":82,
"insights":14
}
Sprint 9-A.2-J
Gouvernance
Étape 29 — Permissions
analytics.predictive.read analytics.forecast.manage analytics.models.train analytics.insights.read analytics.executive
Étape 30 — Audit
MODEL_TRAINED FORECAST_GENERATED CHURN_ANALYSIS_COMPLETED PREDICTIVE_KPI_REFRESHED ANALYTICS_INSIGHT_CREATED MODEL_DEPLOYED
Étape 31 — Jobs
Toutes les nuits Forecast Refresh Churn Analysis Predictive KPI Refresh Toutes les semaines Model Retraining Model Validation
Préparation Sprint 9-B.1
Compatible avec :
Executive Cockpit Board Reporting Enterprise Scorecards Cross-Domain Analytics Strategic Intelligence
Définition de terminé
Le Sprint 9-A.2 est terminé lorsque :
✓ Forecast Models créés ✓ Demand Forecast créé ✓ Revenue Forecast créé ✓ Churn Forecast créé ✓ Predictive KPI Engine créé ✓ AI Analytics créé ✓ Plateforme prédictive opérationnelle
Livrables
ForecastModel ForecastPrediction PredictiveKPI AnalyticsInsight ChurnPrediction ForecastModelService DemandForecastService RevenueForecastService ChurnForecastService PredictiveKPIService AnalyticsInsightService PredictiveAnalyticsDashboardService Predictive Analytics Platform
Sprint 9-B.1 — Executive Cockpit & Enterprise Scorecards
Objectif
Construire le cockpit exécutif Enterprise unifié.
Cette couche permet aux dirigeants, investisseurs, opérateurs et managers de piloter l'ensemble de la plateforme depuis une vue stratégique unique.
Cette couche agrège :
CRM Properties Reservations Finance Marketplace Marketing Loyalty Growth Predictive Analytics
afin de fournir :
Vision consolidée KPI stratégiques Scorecards Reporting Board Pilotage temps réel Décision assistée par IA
À l'issue de cette étape :
✓ Executive Dashboard ✓ Enterprise KPIs ✓ Scorecards ✓ Strategic Reporting ✓ Cross-Domain Analytics ✓ Board Reporting ✓ Executive Cockpit
Architecture cible
Business Intelligence ↓ Executive Analytics Layer ├── Enterprise KPIs ├── Strategic Scorecards ├── Cross-Domain Analytics ├── Predictive Insights ├── Board Reporting └── Executive Cockpit ↓ CEO COO CFO CMO Operations Investors
Sprint 9-B.1-A
Extension Prisma
Étape 1 — ExecutiveDashboard
Ajouter dans schema.prisma
model ExecutiveDashboard {
id String
@id
@default(uuid())
tenantId String
code String
name String
description String?
active Boolean
@default(true)
configuration Json
createdAt DateTime
@default(now())
updatedAt DateTime
@updatedAt
@@unique([tenantId, code])
@@index([tenantId])
}
Étape 2 — EnterpriseScorecard
Ajouter
model EnterpriseScorecard {
id String
@id
@default(uuid())
tenantId String
name String
periodStart DateTime
periodEnd DateTime
overallScore Float
generatedAt DateTime
@default(now())
@@index([tenantId])
@@index([generatedAt])
}
Étape 3 — EnterpriseMetric
Ajouter
model EnterpriseMetric {
id String
@id
@default(uuid())
tenantId String
metricCode String
metricName String
category EnterpriseMetricCategory
targetValue Decimal?
@db.Decimal(18,4)
currentValue Decimal?
@db.Decimal(18,4)
trend TrendDirection?
measuredAt DateTime
@@index([tenantId])
@@index([category])
@@index([metricCode])
}
Étape 4 — StrategicInsight
Ajouter
model StrategicInsight {
id String
@id
@default(uuid())
tenantId String
category StrategicInsightCategory
severity InsightSeverity
title String
description String
recommendation String?
impactScore Float?
generatedAt DateTime
@default(now())
@@index([tenantId])
@@index([category])
}
Étape 5 — BoardReport
Ajouter
model BoardReport {
id String
@id
@default(uuid())
tenantId String
reportPeriod String
reportDate DateTime
reportStatus BoardReportStatus
generatedFileUrl String?
createdAt DateTime
@default(now())
@@index([tenantId])
@@index([reportDate])
}
Étape 6 — Enums
Ajouter
enum EnterpriseMetricCategory {
REVENUE
OPERATIONS
CUSTOMER
PROPERTY
MARKETING
LOYALTY
MARKETPLACE
FINANCE
}
enum StrategicInsightCategory {
REVENUE
GROWTH
COST
RISK
CUSTOMER
MARKETPLACE
OPERATIONS
}
enum TrendDirection {
UP
DOWN
STABLE
}
enum BoardReportStatus {
DRAFT
GENERATED
PUBLISHED
ARCHIVED
}
Étape 7 — Migration
npx prisma migrate dev \
--name executive_cockpit
Sprint 9-B.1-B
Executive Module
Étape 8 — Structure
src/modules/executive ├── dashboards ├── scorecards ├── metrics ├── reporting ├── insights └── executive.module.ts
Étape 9 — Services
ExecutiveDashboardService EnterpriseScorecardService EnterpriseMetricService StrategicInsightService BoardReportingService CrossDomainAnalyticsService
Sprint 9-B.1-C
Enterprise KPIs
Étape 10 — EnterpriseMetricService
Créer
enterprise-metric.service.ts
Agréger
Revenue Occupancy ADR RevPAR LTV Retention Marketplace Revenue Marketing ROI NPS Growth Rate
Étape 11 — KPIs Stratégiques
Revenue Growth Profit Margin Occupancy Rate Customer Lifetime Value Retention Rate Referral Revenue Marketplace Contribution Forecast Accuracy
Étape 12 — Méthodes
refreshMetrics() calculateTrend() calculateTargetGap() generateExecutiveMetrics()
Sprint 9-B.1-D
Enterprise Scorecards
Étape 13 — EnterpriseScorecardService
Créer
enterprise-scorecard.service.ts
Calculer
Financial Score Customer Score Operations Score Growth Score Risk Score
Étape 14 — Pondération
Finance 30% Operations 25% Customer 20% Growth 15% Risk 10%
Étape 15 — Classification
90-100 Excellent 75-89 Healthy 50-74 Watch 0-49 Critical
Sprint 9-B.1-E
Cross-Domain Analytics
Étape 16 — CrossDomainAnalyticsService
Créer
cross-domain-analytics.service.ts
Corréler
Marketing ↔ Revenue Loyalty ↔ Retention Reviews ↔ Occupancy Referrals ↔ Revenue CRM ↔ Reservations
Étape 17 — Analyses
Causal Trends Correlations Segment Performance Executive Trends
Étape 18 — Exemple
Loyalty Score +12% ↓ Retention +8% ↓ Revenue +5.4%
Sprint 9-B.1-F
Strategic Reporting
Étape 19 — BoardReportingService
Créer
board-reporting.service.ts
Générer
Board Packs Investor Reports Executive Reports Management Reports
Étape 20 — Formats
PDF Excel PowerPoint JSON
Étape 21 — Sections
Executive Summary Financial Performance Operations Customers Growth Forecasts Risks
Sprint 9-B.1-G
Strategic Insights
Étape 22 — StrategicInsightService
Créer
strategic-insight.service.ts
Produire
Revenue Opportunities Cost Reduction Customer Risks Market Expansion Growth Signals
Étape 23 — Exemples
Occupancy +11% prévue ↓ Revenue +9% attendu
Churn VIP +6% ↓ Action recommandée
Sprint 9-B.1-H
Executive Dashboard
Étape 24 — ExecutiveDashboardService
Créer
executive-dashboard.service.ts
Widgets
Revenue Overview Occupancy Overview Customer Health Marketplace Health Forecast Center Strategic Insights
Étape 25 — Vues
CEO COO CFO CMO Operations Investors
Sprint 9-B.1-I
API Executive
Étape 26 — Endpoints
GET /executive/dashboard GET /executive/scorecards GET /executive/metrics GET /executive/insights GET /executive/reports POST /executive/reports/generate
Étape 27 — Exemple
{
"enterpriseScore":91,
"revenueGrowth":18.4,
"occupancy":86.7,
"customerRetention":92.1,
"forecastConfidence":89.4
}
Sprint 9-B.1-J
Gouvernance
Étape 28 — Permissions
executive.read executive.metrics.read executive.scorecards.read executive.reporting.generate executive.insights.read executive.admin
Étape 29 — Audit
EXECUTIVE_DASHBOARD_VIEWED SCORECARD_GENERATED BOARD_REPORT_GENERATED STRATEGIC_INSIGHT_CREATED METRIC_REFRESHED EXECUTIVE_REPORT_EXPORTED
Étape 30 — Jobs
Toutes les nuits Executive Metrics Refresh Strategic Insight Generation Scorecard Refresh Toutes les semaines Board Report Generation
Préparation Sprint 9-B.2
Compatible avec :
AI Executive Advisor Autonomous Analytics Decision Intelligence Strategic Planning Enterprise AI
Définition de terminé
Le Sprint 9-B.1 est terminé lorsque :
✓ Executive Dashboard créé ✓ Enterprise KPIs créés ✓ Scorecards créés ✓ Strategic Reporting créé ✓ Cross-Domain Analytics créé ✓ Board Reporting créé ✓ Executive Cockpit opérationnel
Livrables
ExecutiveDashboard EnterpriseScorecard EnterpriseMetric StrategicInsight BoardReport ExecutiveDashboardService EnterpriseScorecardService EnterpriseMetricService StrategicInsightService BoardReportingService CrossDomainAnalyticsService Executive Cockpit Platform
Sprint 9-B.2 — AI Executive Advisor & Decision Intelligence
Objectif
Finaliser la plateforme Enterprise Intelligence en ajoutant une couche décisionnelle autonome pilotée par l'IA.
Cette couche permet :
AI Executive Advisor Decision Intelligence Autonomous Insights Strategic Recommendations Scenario Simulation Executive Copilot
afin de transformer la plateforme en système d'aide à la décision de niveau Enterprise.
À l'issue de cette étape :
✓ AI Executive Advisor ✓ Decision Intelligence ✓ Autonomous Insights ✓ Strategic Recommendations ✓ Scenario Simulation ✓ Executive Copilot ✓ Enterprise Intelligence Platform
Architecture cible
Business Intelligence ↓ Predictive Analytics ↓ Decision Intelligence Layer ├── Executive Advisor ├── Strategic AI Engine ├── Scenario Simulator ├── Autonomous Insights ├── Recommendation Engine ├── Executive Copilot └── Decision Memory ↓ Executives ↓ Strategic Decisions
Sprint 9-B.2-A
Extension Prisma
Étape 1 — ExecutiveRecommendation
Ajouter dans schema.prisma
model ExecutiveRecommendation {
id String
@id
@default(uuid())
tenantId String
category RecommendationCategory
priority RecommendationPriority
title String
description String
expectedImpact String?
confidenceScore Float?
status RecommendationStatus
generatedAt DateTime
@default(now())
@@index([tenantId])
@@index([category])
@@index([priority])
}
Étape 2 — ScenarioSimulation
Ajouter
model ScenarioSimulation {
id String
@id
@default(uuid())
tenantId String
name String
scenarioType ScenarioType
assumptions Json
projectedImpact Json
confidenceScore Float?
createdAt DateTime
@default(now())
@@index([tenantId])
@@index([scenarioType])
}
Étape 3 — AutonomousInsight
Ajouter
model AutonomousInsight {
id String
@id
@default(uuid())
tenantId String
category AutonomousInsightCategory
severity InsightSeverity
title String
description String
recommendation String?
detectedAt DateTime
@default(now())
@@index([tenantId])
@@index([category])
}
Étape 4 — DecisionRecord
Ajouter
model DecisionRecord {
id String
@id
@default(uuid())
tenantId String
title String
decisionCategory DecisionCategory
recommendationId String?
outcome String?
impactScore Float?
createdAt DateTime
@default(now())
@@index([tenantId])
@@index([decisionCategory])
}
Étape 5 — ExecutiveCopilotSession
Ajouter
model ExecutiveCopilotSession {
id String
@id
@default(uuid())
tenantId String
userId String
startedAt DateTime
@default(now())
endedAt DateTime?
sessionSummary String?
decisionsGenerated Int
@default(0)
@@index([tenantId])
@@index([userId])
}
Étape 6 — Enums
Ajouter
enum RecommendationCategory {
REVENUE
COST
CUSTOMER
OPERATIONS
MARKETPLACE
GROWTH
RISK
}
enum RecommendationPriority {
LOW
MEDIUM
HIGH
CRITICAL
}
enum RecommendationStatus {
OPEN
ACCEPTED
REJECTED
IMPLEMENTED
}
enum ScenarioType {
REVENUE
OCCUPANCY
PRICING
MARKETING
EXPANSION
COST_REDUCTION
}
enum AutonomousInsightCategory {
OPPORTUNITY
RISK
ANOMALY
FORECAST
PERFORMANCE
}
enum DecisionCategory {
STRATEGIC
FINANCIAL
OPERATIONAL
CUSTOMER
GROWTH
}
Étape 7 — Migration
npx prisma migrate dev \
--name ai_executive_advisor
Sprint 9-B.2-B
Decision Intelligence Module
Étape 8 — Structure
src/modules/decision-intelligence ├── advisor ├── recommendations ├── simulations ├── insights ├── copilot ├── memory └── decision-intelligence.module.ts
Étape 9 — Services
ExecutiveAdvisorService DecisionIntelligenceService StrategicRecommendationService ScenarioSimulationService AutonomousInsightService ExecutiveCopilotService DecisionMemoryService
Sprint 9-B.2-C
AI Executive Advisor
Étape 10 — ExecutiveAdvisorService
Créer
executive-advisor.service.ts
Fournir
Business Analysis Executive Briefing Strategic Summary Priority Ranking Decision Support
Étape 11 — Questions
Répondre à
Pourquoi le revenu baisse ? Quels segments croissent ? Quels risques sont critiques ? Où investir ? Quelle action a le meilleur ROI ?
Étape 12 — Méthodes
generateExecutiveBrief() generateBusinessSummary() rankBusinessPriorities() answerExecutiveQuestion()
Sprint 9-B.2-D
Strategic Recommendations
Étape 13 — StrategicRecommendationService
Créer
strategic-recommendation.service.ts
Générer
Revenue Growth Cost Optimization Retention Improvement Expansion Opportunities Marketplace Optimization
Étape 14 — Priorisation
Impact Effort Risk ROI
Étape 15 — Exemple
Dynamic Pricing ↓ +12% revenu Confidence 91%
Sprint 9-B.2-E
Autonomous Insights
Étape 16 — AutonomousInsightService
Créer
autonomous-insight.service.ts
Détecter automatiquement
Anomalies Opportunités Risques Tendances Prévisions
Étape 17 — Exemples
Churn VIP +15% ↓ Alerte stratégique
Demande été +22% ↓ Capacité insuffisante
Sprint 9-B.2-F
Scenario Simulation
Étape 18 — ScenarioSimulationService
Créer
scenario-simulation.service.ts
Simuler
Prix Marketing Expansion Réduction coûts Commissions
Étape 19 — Méthodes
simulateRevenueImpact() simulatePricingChange() simulateExpansion() compareScenarios()
Étape 20 — Exemple
Tarifs +8% ↓ Revenu +11% Occupation -2%
Sprint 9-B.2-G
Decision Memory
Étape 21 — DecisionMemoryService
Créer
decision-memory.service.ts
Conserver
Décisions Actions Résultats KPIs impactés ROI réel
Étape 22 — Objectif
Permettre à l'IA d'apprendre :
Décisions gagnantes Décisions perdantes Effets réels Historique stratégique
Sprint 9-B.2-H
Executive Copilot
Étape 23 — ExecutiveCopilotService
Créer
executive-copilot.service.ts
Fonctions
Chat exécutif Analyse KPI Simulation Recommandations Explications
Étape 24 — Exemples
Pourquoi le revenu est-il inférieur aux prévisions ?
Que se passe-t-il si nous augmentons les prix de 5% ?
Quels sont les 3 plus grands risques ?
Sprint 9-B.2-I
Dashboard IA
Étape 25 — DecisionIntelligenceService
Créer
decision-intelligence.service.ts
Afficher
Strategic Recommendations Executive Insights Scenario Center Forecast Center Risk Center Decision Tracker
Étape 26 — Endpoints
GET /executive/ai/dashboard GET /executive/ai/recommendations GET /executive/ai/insights POST /executive/ai/simulations GET /executive/ai/decisions POST /executive/ai/copilot/chat
Étape 27 — Exemple
{
"recommendations":12,
"criticalRisks":3,
"growthOpportunities":7,
"forecastConfidence":89,
"executiveScore":94
}
Sprint 9-B.2-J
Gouvernance
Étape 28 — Permissions
executive.ai.read executive.ai.simulate executive.ai.copilot executive.ai.recommendations executive.ai.admin
Étape 29 — Audit
EXECUTIVE_BRIEF_GENERATED SCENARIO_SIMULATED AUTONOMOUS_INSIGHT_CREATED RECOMMENDATION_GENERATED DECISION_RECORDED COPILOT_SESSION_STARTED
Étape 30 — Jobs
Toutes les heures Insight Detection Toutes les nuits Recommendation Generation Scenario Refresh Decision Learning Executive Brief Generation
Clôture Enterprise Intelligence
À la fin du Sprint 9-B.2 :
✓ Data Warehouse ✓ Predictive Analytics ✓ Executive Cockpit ✓ Decision Intelligence ✓ AI Executive Advisor ✓ Executive Copilot ✓ Enterprise Intelligence
sont entièrement opérationnels.
Préparation Sprint 10
Compatible avec :
Platform API Public APIs SDKs Developer Portal Ecosystem Platform App Marketplace
Définition de terminé
Le Sprint 9-B.2 est terminé lorsque :
✓ AI Executive Advisor créé ✓ Decision Intelligence créée ✓ Autonomous Insights créés ✓ Strategic Recommendations créées ✓ Scenario Simulation créée ✓ Executive Copilot créé ✓ Enterprise Intelligence finalisée
Livrables
ExecutiveRecommendation ScenarioSimulation AutonomousInsight DecisionRecord ExecutiveCopilotSession ExecutiveAdvisorService DecisionIntelligenceService StrategicRecommendationService ScenarioSimulationService AutonomousInsightService ExecutiveCopilotService DecisionMemoryService Enterprise Intelligence Platform
ujusum/3-codage/2-sprints/9-sprint-9.txt · Dernière modification : 2026/06/11 02:41 de 83.202.252.200