Overview

Solvon Insurance is a US based insurer, offering health, life, and motor coverage. Its analytics ran on a legacy Teradata warehouse where scaling meant a new hardware purchase each time, reports slowed when teams queried together, and each product line defined its data differently, so the same metric varied by source. Bacancy migrated the warehouse to Snowflake, gave each team its own compute, standardized the data across all three lines, and rebuilt every access rule with column-level security and masking. Analytics ran 60% faster, peak-hour failures ended, and the legacy warehouse was retired without disrupting operations.

Technologies Used

Snowflake
Teradata
dbt
Fivetran
Tableau
Git

Project Highlights

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Complete Teradata warehouse migrated to Snowflake with full data validation

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All confidential policyholder data migrated with encryption, masking, and RBAC

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Data Warehouse Migration delivered with no interruption to reporting or business operations

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Separate compute allocated to each workload for uninterrupted reporting and analytics

The Challenges

1

The Teradata warehouse ran on fixed capacity, with compute and storage locked together. As claims and policyholder data grew, adding more capacity meant a hardware upgrade each time.

2

The legacy warehouse could not handle many users at once. When claims processing and underwriting teams ran reports together, the system slowed, and some reports failed to load.

3

Data was fragmented across the health, life, and motor insurance products. Each line defined its fields differently, so the same metric often came out differently depending on the source.

4

The warehouse held sensitive policyholder data across every product line, which could not be exposed during the move, and every access rule had to be rebuilt on Snowflake exactly as before.

Solutions by Bacancy

1

Our Snowflake migration experts migrated the warehouse to Snowflake, separating storage and compute. This enabled storage to scale as data volumes grew, while compute was sized per job, eliminating the need for hardware upgrades.

2

Bacancy’s Snowflake developers assigned separate compute to claims, underwriting, and reporting. The three teams could run their reports at the same time without slowing each other down.

3

Our data engineers standardized the data during the migration. Every field was mapped to one definition, and the old BTEQ and ETL logic was rebuilt in dbt. The same metric matched across health, life, and motor insurance.

4

Through our insurance IT services, we encrypted policyholder data before migrating it to Snowflake and rebuilt every access rule using column-level security and masking, so each user saw only the claims and policy data that their role allowed.

Core Features

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Teradata to Snowflake schema and code conversion automation

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Dedicated compute for claims, underwriting, and reporting

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Automated data accuracy checks across all migrated records

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Role-based security and masking for regulated policyholder data

No. of Resource

04

No. of Resource

Time Frame

August 2025 - March 2026

Time Frame

Project Snapshot

Solvon Insurance Dashboard

Outcomes

60% faster analytics across claims, underwriting, and reporting workloads

Peak-hour report failures eliminated, even with every team querying at once

Policyholder metrics matched across health, life, and motor insurance product lines

Month-end reporting time dropped from hours on Teradata to minutes on Snowflake

Legacy Teradata warehouse fully retired, with zero disruption to daily operations

Manual data checks in spreadsheets replaced by automated validation

Technical Stack

Legacy Data Warehouse Teradata
Cloud data warehouse Snowflake
Code & schema conversion SnowConvert
Data transformation dbt
Data validation dbt tests
Data ingestion Fivetran
Orchestration dbt Cloud
BI/reporting Tableau
Scripting & automation Python
Security & governance Snowflake RBAC
Version control & CI/CD GitGitHub Actions

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