Bitwise

Modernized Guidewire Data Processing from Azure Synapse to Databricks for a Leading US Insurer

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A leading US insurance carrier needed to modernize data processing for its Guidewire PolicyCenter, BillingCenter, and ClaimCenter platforms. The organization sought to migrate Azure Synapse and Azure Data Factory workloads to Databricks, creating a scalable, governed, and maintainable platform with improved performance, automated validation, and end-to-end operational traceability.

Client Challenges and Requirements

  • Legacy data workloads: Core Guidewire data was processed through Azure Synapse and ADF, limiting flexibility and maintainability.
  • Fragmented business logic: Processing logic was distributed across stored procedures, ADF pipelines, and dataflows.
  • Performance constraints: Dimension and fact data loads required faster and more efficient processing.
  • Manual validation: Data checks and reconciliation relied on manual effort without a reusable validation framework.
  • Limited auditability: Existing processes lacked consistent audit logging and run-level traceability.
  • Migration complexity: The new platform needed to preserve functional parity while converting diverse legacy components.

Bitwise Solution

  • Converted stored procedures, ADF pipelines, dataflows, and processing logic into PySpark and Spark SQL notebooks.
  • Replaced Synapse tables with Delta Lake tables governed through Unity Catalog.
  • Configured job orchestration and repeatable deployments using Databricks Asset Bundles and Databricks Jobs.
  • Built a reusable validation framework with column-level checks, record-count reconciliation, and duplicate detection.
  • Implemented audit logging and Job RunId tracking to provide end-to-end operational traceability.
  • Optimized dimension and fact data loads while maintaining functional parity with the legacy platform.
  • Modernized Guidewire PolicyCenter, BillingCenter, and ClaimCenter data processing on a scalable Databricks architecture.

Tools & Technologies We Used

Databricks

Azure Synapse Analytics

Azure Data Factory

Guidewire PolicyCenter, BillingCenter, and ClaimCenter

PySpark

Spark SQL

Interactive Notebooks

Delta Lake

Unity Catalog

Databricks Asset Bundles

Databricks Jobs

Audit Logging and Job RunId Tracking

Validation and Reconciliation Framework

Key Results

Improved performance: Accelerated dimension and fact data loads.

Reduced manual effort: Reusable migration and validation frameworks streamlined delivery and ongoing operations.

Automated validation: Replaced manual checks with repeatable data-quality and reconciliation controls.

Enhanced governance: Unity Catalog and Delta Lake strengthened control and consistency across Guidewire data.

Increased operational visibility: Audit logging and Job RunId tracking improved traceability and troubleshooting.

Maintained functional parity: Preserved legacy platform outcomes while modernizing the underlying architecture.

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Guidewire Data Modernization: Synapse to Databricks for a US Insurer