Client was a fast-growing specialty insurance firm offering a broad portfolio of products and services. As part of its expansion strategy, the client had acquired multiple small insurance agencies across the U.S., each with its own legacy data systems and formats. Infojini partnered with the client to implement a robust, scalable Snowflake data platform to standardize data ingestion, improve reporting capabilities, and drive product innovation using advanced analytics.

Challenges:

• Heterogeneous Schemas: Variability in agency databases for policy, claims, customer, and agent data created complex mapping challenges.
• Diverse Data Formats: Required transformation pipelines for CSV, JSON, and Parquet formats.
• Data Onboarding Scalability: The client needed a repeatable model to integrate newly acquired agencies without custom engineering.
• Manual Reporting Bottlenecks: Lack of centralized access delayed business intelligence and cross-agency visibility.

Job Roles:

• Data Engineers: Created Snowflake schemas and ingestion workflows using Streams, Tasks, and Snowpipe.
• Cloud/DevOps Engineers: Set up AWS S3 staging zones, IAM policies, and Snowflake external stage connections.
• Data Analyst: Validated structured data against business rules, using Snowflake SQL and BI test queries.
• Business Analyst: Aligned reporting requirements with schema mappings across acquired datasets.
• Product Owner: Prioritized datasets for onboarding and led sprint planning.

Infojini’s Solution:

• Historical Data Migration Using Snowpipe: Extracted full historical data from agencies’ on-prem databases, staged it in structured S3 folders, and ingested it into Snowflake using Snowpipe.
• Unified Analytics with Star Schema Modeling: Designed consolidated data warehouse using a star schema optimized for analytics and reporting.
• Automated & Scalable Ingestion Using Snowpipe & Tasks: Snowpipe and Tasks automated data processing, allowing clients to easily onboard new insurance agencies.
• Power BI Integration for Real-time Dashboards: Connected Snowflake with Power BI to enable self-service access to real-time dashboards.
• Analytics Enablement with Data Marts: Developed data marts for POLICY_SALES, CLAIMS_ANALYTICS, and CUSTOMER_RETENTION, empowering business teams with insights on trends, performance, and optimization opportunities.

Results:

• 700K–1M policy, 300K–500K customer, and 1.5M–2M claims records ingested
• 30% reduction in data load time with automated ingestion and transformation
• Real-time dashboards empowered strategic insights into claims cycle and sales performance
• 15% faster new product launches due to actionable customer behavior and spending analysis
• Scalable ingestion model allowed plug-and-play onboarding for new acquisitions
• Power BI self-service enabled departments to run ad hoc reports without IT dependencies