Teradata Consulting Services
Case study
Insurance enterprise cut Teradata infrastructure costs with BigQuery
Realigned data architecture cut annual infrastructure costs by $2.1M.
Pythian modernized Teradata pipelines to BigQuery to cut costs and enable AI.
A leading national insurer faced rapid growth in claims volume that outpaced its aging on-premises Teradata environment, driving up hardware refresh costs and stalling real-time analytics. Facing end-of-support deadlines and 20% annual license fee increases, the enterprise partnered with Pythian to execute a zero-disruption migration to Google BigQuery. Pythian refactored proprietary logic across 3,000+ BTEQ scripts and consolidated satellite databases into a unified cloud engine. Underwriting and claims specialists now access near real-time dashboards and production AI workflows, reclaiming 70% of maintenance hours for strategic risk modeling.
Pythian's deep experience across both legacy Teradata and modern cloud architectures ensured our proprietary business logic stayed intact while shifting our entire analytics engine to BigQuery."
Chief Data Officer
Insurance Enterprise
$2.1M
Annual savings
45%
Lower infrastructure costs
60%
Faster query performance
Accelerate your enterprise data warehouse modernization to unlock production AI.
The insurer's surging claims volume outpaced legacy hardware, creating cost overruns and analytical bottlenecks.
Pythian migrated a legacy Teradata warehouse to BigQuery with zero downtime, preserving business logic and enabling enterprise AI.
Modernizing our legacy warehouse allowed our team to focus on predictive risk modeling rather than spending 70% of their time managing overnight batch processing."
Chief Data Officer
Insurance Enterprise
Aging Teradata and labor shortages raised costs
On-premises Teradata hardware approached end-of-support dates alongside 20% annual licensing increases and acute DBA recruitment challenges.
Legacy BTEQ scripts blocked cloud migration
Over 3,000 BTEQ scripts, proprietary SQL extensions, and tangled batch jobs prevented a simple lift-and-shift migration.
Slow overnight batches delayed underwriting decisions
Overnight 14-hour batch processing runs left underwriting and claims teams working with day-old analytical data.
Isolated satellite databases fragmented enterprise analytics
Multiple satellite databases created disparate data sources, increasing storage overhead and blocking enterprise-wide analytics.
Uncovered legacy code dependencies to protect 24/7 operational continuity.
Pythian audited the complete Teradata estate, mapping dependencies across 3,000 BTEQ scripts, three satellite databases, and 40 upstream feeds. Engineers stabilized current workloads to maintain 24/7 business continuity while establishing a clean foundation for cloud architecture. Executing such a thorough review preserved every piece of critical business logic throughout the transition.
Eliminated hardware refresh costs through an elastic, consumption-based cloud core.
The team selected Google BigQuery to replace fixed-capacity hardware with serverless elasticity and consumption-based cost models. Pythian unified the core Teradata warehouse and satellite data silos into a single cloud platform. The architecture integrated Apache Airflow, Fivetran, dbt, Looker, and Vertex AI to support modern data operations.
Eliminated decade-old technical debt without interrupting daily business operations.
Engineers refactored Teradata-specific utilities, BTEQ scripts, and primary index data models into BigQuery-native SQL and Airflow orchestrations. Dual-run parallel validation tested every component against legacy output to verify strict calculation accuracy. The rigorous validation process eliminated technical debt without interrupting ongoing operations.
Accelerated underwriting decisions with real-time analytics and automated fraud detection.
Pythian deployed Looker self-service dashboards to replace 14-hour overnight batch reports with near real-time data feeds. Vertex AI integration enabled automated claims fraud detection and predictive risk workflows directly within production data pipelines. The enterprise then transitioned the environment to 24/7 Managed Services for long-term operational stability.
Modernize your data architecture to drive measurable business growth.
Harnessing the full power of the Google Cloud ecosystem.
As a Premier Google Cloud Partner, Pythian integrates Vertex AI and BigQuery to solve complex scale challenges.
Pythian is a proud Google Cloud Premier Partner. Lean into our deep expertise and 25+ years of data heritage. Our expertise spans the full Google ecosystem, helping customers harness the power of scalable cloud infrastructure, data analytics, and modern AI modeling to drive innovation. Discover how Pythian leverages Google BigQuery and Vertex AI to eliminate technical debt, reduce infrastructure spend, and build production-ready AI foundations for complex enterprise data estates.
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