FINVU_DATA_WAREHOUSE_IMPLEMENTATION_ROADMAP

COMPREHENSIVE_BUSINESS_UNDERSTANDING_COMPLETED ✅

REGULATORY_COMPLIANCE_FRAMEWORK

SAHAMATI_REPORTING = Daily + Monthly with specific metric breakdowns
RBI_REPORTING = Monthly comprehensive reports
RETENTION_REQUIREMENTS = 7-10 years for application logs, 6-12 months for server logs
DATA_SECURITY = Disk encryption + PII masking + data-blind compliance
DISASTER_RECOVERY = Hot-hot replication with <1 month recovery target

BUSINESS_OPERATIONS_CLARITY

REVENUE_MODEL = ₹3 (lending) + ₹0.10/month (PFM) with 2x growth target
CLIENT_PORTFOLIO = [Navi, Cred, Axis, ICICI, Bajaj Finance, RKB Finance]
COMPETITIVE_POSITION = Top 3 AA, targeting 40% market share vs OnemoneyAA's 70%
BUSINESS_DRIVERS = [Success Rate, FIP Health, UX Quality, API Availability]

TECHNICAL_ARCHITECTURE_INSIGHTS

CORE_SYSTEM = Single AA service with Kafka event streaming
EVENT_TRACING = Consent Handle → Session ID(s) → Events → txnid correlation
CHANGE_FREQUENCY = New event types ~6 months, minimal core changes
CURRENT_EVENTS = 80+ event types across 6 sources with special processors

CRITICAL_SUCCESS_FACTORS

PERFORMANCE_REQUIREMENTS

DRILL_DOWN_LATENCY = <3 seconds across 5 analytical levels
FUNNEL_ANALYSIS = 5-stage executive + 8-stage operational
MULTI_DIMENSIONAL = [TSP, Purpose Code, FI Type, License Type, Journey Type, User Type]
REAL_TIME_NEEDS = Customer Success, Support, Tech teams (7-day retention)

DATA_QUALITY_IMPERATIVES

JOURNEY_STITCHING = Complex event correlation across multiple sessions
EVENT_COMPLETENESS = All server events captured via Kafka
SCHEMA_FLEXIBILITY = Bronze layer JSON preservation for unknown events
BACKWARD_COMPATIBILITY = Support legacy + evolving event structures

MEDALLION_ARCHITECTURE_PHILOSOPHY

LAYER_RESPONSIBILITIES

Bronze = "Did we capture the event completely?"
Silver = "What does this event mean in business context?"  
Gold = "How does this impact our KPIs and metrics?"

ENGINEERING_PRINCIPLE:

• Bronze Layer: Engineering-focused staging and ingestion. Maximum data capture, minimal processing, complete event preservation
• Silver Layer: Business logic and event correlation. Journey stitching, context enrichment, schema evolution handling
• Gold Layer: Analytics and KPIs. Star schema, aggregations, regulatory reports, executive dashboards

IMPLEMENTATION_PHASES

PHASE_1_FOUNDATION (Month 1-2)

CLICKHOUSE_SETUP = UAT deployment with Kafka connectivity
BRONZE_LAYER = Raw event ingestion with JSON preservation (complete capture focus)
BASIC_MONITORING = Data freshness, completeness, system health
TEAM_TRAINING = Core team familiarization with new system

PHASE_2_CORE_ANALYTICS (Month 2-3)

SILVER_LAYER = dbt transformations for business logic (business context focus)
FACT_TABLES = Consent funnel journey + API events detailed
DIMENSION_TABLES = Enhanced customer, FIP, FIU, purpose code
DRILL_DOWN_CAPABILITY = 5-level analysis framework

PHASE_3_BUSINESS_INTELLIGENCE (Month 3-4)

GOLD_LAYER = Star schema with aggregated marts (KPI impact focus)
REGULATORY_REPORTS = Automated Sahamati + RBI report generation
PERFORMANCE_OPTIMIZATION = Query optimization for <3s requirement
CLIENT_DASHBOARDS = Multi-team dashboard deployment

PHASE_4_ADVANCED_FEATURES (Month 4-6)

REAL_TIME_MATERIALIZED_VIEWS = Live aggregations for hot data
HISTORICAL_BACKFILL = Cassandra data migration
POSTHOG_INTEGRATION = User journey correlation
AI_INSIGHTS = Anomaly detection, predictive analytics

RISK_MITIGATION_CHECKLIST

CDC_AND_DATA_SYNC ⚠️

☐ Kafka monitoring dashboard
☐ Daily reconciliation jobs vs Cassandra
☐ Schema evolution management
☐ Data quality validation framework

PERFORMANCE_SCALABILITY ⚠️

☐ Load testing with realistic data volumes
☐ Query optimization and indexing strategy
☐ Caching layer for common aggregations
☐ Partition strategy validation

BUSINESS_CONTINUITY ⚠️

☐ Parallel legacy system operation
☐ Rollback procedures documented
☐ Team-by-team migration plan
☐ Comprehensive runbooks

COMPLIANCE_AUDIT ⚠️

☐ Complete audit trail implementation
☐ Data lineage tracking
☐ Multi-tier backup strategy
☐ Disaster recovery testing

TEAM_COORDINATION_FRAMEWORK

BUSINESS_TEAM_REQUIREMENTS

OWNERS = Vishwa (Product), Dilip (COO)
METRIC_EVOLUTION = Client-driven + ecosystem evolution
REPORTING_NEEDS = Daily T-2 → End-of-day + Early morning
FUTURE_SERVICES = Support AI, FIU Dashboard, Performance differentiation

CORE_TEAM_DEPENDENCIES

EVENT_STREAMING = All server events guaranteed via Kafka
SCHEMA_CHANGES = Coordinated deployment for new event types
JOURNEY_MAPPING = Consent Handle → Session ID → Event correlation
OUTBOUND_TRACKING = txnid mapping for FIP interactions

DEVOPS_INFRASTRUCTURE

DISASTER_RECOVERY = Hot-hot replication maintained
DATA_SECURITY = Encryption + PII masking continued
RETENTION_POLICIES = Server logs (6-12M), App logs (7-10Y)
BACKUP_STRATEGY = Multi-tier with regulatory compliance

SUCCESS_METRICS

TECHNICAL_KPIS

QUERY_LATENCY = 95th percentile <3 seconds
DATA_FRESHNESS = <15 minutes from event to query
UPTIME = 99.99% availability target
DATA_ACCURACY = 100% reconciliation with source

BUSINESS_IMPACT_KPIS

ANALYST_PRODUCTIVITY = Hours saved per report
DECISION_LATENCY = Time from question to insight
CLIENT_SATISFACTION = Dashboard adoption + feedback
REGULATORY_COMPLIANCE = Timely report generation

NEXT_IMMEDIATE_ACTIONS

WEEK_1_PRIORITIES

1. ClickHouse UAT environment setup
2. Kafka-ClickHouse connectivity testing
3. Bronze layer schema design finalization
4. Team roles and responsibilities definition

WEEK_2_PRIORITIES

1. Event configuration analysis (eventConfig-aa.json)
2. Historical data sample extraction from Cassandra
3. dbt project structure initialization
4. Monitoring and alerting framework design

MONTH_1_DELIVERABLES

1. Working bronze layer with sample data
2. Basic funnel analysis capability
3. Performance baseline establishment
4. Risk mitigation plans activated

This comprehensive documentation now captures our complete deep business understanding and provides a clear path forward for the data warehouse implementation! 🎯