Overview
A Fortune 500 US-based specialty property and casualty (P&C) insurance provider partnered with Zensar to modernize and operationalize a governed Databricks Lakehouse foundation for Guidewire data across its multi‑family housing business. Operating in 21 countries through a complex B2B2C model, the organization needed a scalable, auditable, and cost‑efficient platform that could keep pace with increasing data volumes, more consumers, and regulated insurance workloads. In a market where underwriting agility and customer experience are increasingly data-driven, bringing Guidewire data into an intelligence layer is essential to remain competitive. What began as a focused initiative over two years ago has grown into a strategic, long‑term partnership – supporting multi‑team consumption of trusted datasets and enabling faster onboarding of new data domains and use cases.
Zensar’s Brief – Steps taken by Zensar
Designed and implemented a modern cloud‑native data engineering platform tailored for Guidewire insurance data.
Built robust ELT pipelines to standardize, curate, and operationalize policy, claims, and financial datasets.
Established governed data layers using Delta Lake to ensure consistency, reliability, and audit readiness.
Integrated version control and CI/CD practices to support controlled change and long‑term platform evolution.
Embedded with client teams to enable knowledge transfer, continuous improvement, and scalable delivery.
Beyond the Brief – How it helped the client
Reduced dependence on fragmented legacy pipelines and manual reconciliation.
Enabled trusted, reusable data assets to scale consumption across actuarial, finance, risk, and operations teams.
Accelerated onboarding of new data domains and analytics use cases while keeping governance consistent.
Established a foundation that continues to expand year over year with new workloads, consumers, and Guidewire initiatives.
Challenges
Scaling Guidewire analytics while maintaining cost discipline, compliance, and auditability in a regulated insurance environment.
The client faced growing complexity in managing and analyzing Guidewire data across a global operating model. Legacy ETL processes and tooling could not scale to increasing, compute‑intensive analytics workloads, and they slowed onboarding of new data domains and downstream consumers.
Their B2B2C ecosystem also introduced more partner touchpoints, digital channels, and connected technologies – creating new data opportunities and higher expectations for near‑real‑time insight. Regulatory requirements demanded strong lineage, auditability, and data quality controls – capabilities that were difficult to enforce consistently across disparate systems.
As the multi‑family housing business expanded, the organization needed a future‑ready data foundation to standardize pipelines, improve governance, and support continuous growth in volumes and usage without repeated re‑platforming.
Solutions
A governed Databricks Lakehouse built to scale insurance analytics, onboard new domains faster, and support long‑term growth.
Zensar implemented a governed Databricks Lakehouse on Azure to standardize ingestion, transformation, and consumption of Guidewire data at scale. ELT pipelines were developed using Databricks notebooks and Delta Lake on Azure Data Lake Storage, enabling reliable ingestion, transformation, and curation of core insurance datasets.
A repeatable bronze/silver/gold approach accelerated onboarding, with curated Delta layers creating trusted, reusable data assets that multiple teams could consume without duplicating pipelines. Governance, versioning, and operational discipline were embedded from day one, ensuring the platform could evolve safely as adoption grew across new use cases, higher volumes, and broader enterprise usage.
1.
Cloud-native data lake and analytics architecture
2.
Curated Delta Lake layers for Guidewire domain data
3.
Automated ELT pipelines with integrated testing and controls
4.
Git-based artifact management and controlled deployments
Solution enablers
1. Azure Data Factory (ADF)
2. Databricks
3. Azure Data Lake Storage (ADLS)
4. Delta Lake
Impact
Faster onboarding, fewer reruns, and governed, reusable data products that support expanding consumption across teams.
1.
Operational efficiency: Standardized pipelines and reusable transformations reduced rework and accelerated delivery by 5–10% or more in onboarding new datasets and handling changes.
2.
Cost optimization: Reduced manual reconciliation and duplicated effort, typically cutting analyst/ops time spent on reconciliations by 30–50% through trusted curated layers.
3.
Compliance and auditability: Built-in lineage, versioning, and data quality controls strengthened audit readiness and reduced production issues, often driving 20–40% fewer incidents and reruns.
4.
Scalability: Platform supports growing volumes and new Guidewire domains while scaling adoption, commonly supporting 1.5–3X more consumers/teams without proportional engineering growth.
Business outcome
Over two years after its initial implementation, the Zensar‑built Databricks Lakehouse platform remains a critical foundation for the client’s Multi‑Family Housing analytics strategy. The solution continues to grow in scope, supporting additional datasets, teams, and decision‑making workflows, while maintaining strong governance and predictable costs as usage expands. By shifting from reactive, fragmented data processes to a standardized, auditable data foundation, the client gained faster insight generation, an improved regulatory posture, and the confidence to onboard new analytics capabilities in line with business growth and evolving digital ecosystems. The engagement stands as a long‑term partnership focused on sustained value creation rather than a point‑in‑time technology deployment.