TechFlow
TechFlow
Problem & Architecture Overview
TechFlow is a MySQL-based SaaS analytics system that converts transactional subscription data into business reporting. The project models customer, product, subscription, and revenue tables to support KPI analysis through optimized SQL queries and dashboards.
TechFlow is a MySQL-based SaaS analytics system that converts transactional subscription data into business reporting. The project models customer, product, subscription, and revenue tables to support KPI analysis through optimized SQL queries and dashboards.
Data Pipeline Design & Ingestion Flow
Raw SaaS data was distributed across interconnected operational tables with no analytics-ready structure. The architecture normalizes entities, defines reliable joins, and builds query patterns for customer growth, subscription performance, revenue distribution, and operational KPIs.
Raw SaaS data was distributed across interconnected operational tables with no analytics-ready structure. The architecture normalizes entities, defines reliable joins, and builds query patterns for customer growth, subscription performance, revenue distribution, and operational KPIs.
Failure Handling & Idempotency
The schema design emphasizes referential integrity, repeatable aggregations, and query-level checks to prevent inconsistent KPI outputs. Analytical views can be regenerated from normalized source tables without duplicating business logic across reports.
The schema design emphasizes referential integrity, repeatable aggregations, and query-level checks to prevent inconsistent KPI outputs. Analytical views can be regenerated from normalized source tables without duplicating business logic across reports.
Business & Operational Impact
The system demonstrates how relational data modeling and SQL analytics can turn SaaS operations into actionable intelligence. Stakeholders can track growth, retention, revenue performance, and product usage from a consistent analytical layer.
The system demonstrates how relational data modeling and SQL analytics can turn SaaS operations into actionable intelligence. Stakeholders can track growth, retention, revenue performance, and product usage from a consistent analytical layer.
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