How Peloton Future-Proofed Its Analytics Platform for Growth and Performance

How Peloton Future-Proofed Its Analytics Platform for Growth and Performance

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About Peloton

Peloton is a global fitness technology company delivering connected fitness experiences to millions of members worldwide. Data plays a central role in powering personalization, operational insights, and business intelligence across the organization.

The Challenge: Scaling a Complex Analytics Environment

Peloton’s analytics platform, built on Amazon Redshift, had evolved into a complex ecosystem of data pipelines, transformations, and BI reporting.

As data volumes increased and reporting requirements became more advanced, the platform faced growing pressure around performance, scalability, and cost efficiency. At the same time, the environment supported business-critical analytics, making disruption during migration a significant risk.

The challenge was not just to modernize – but to do so while preserving existing workflows and maintaining continuity across interconnected systems, including Airbyte, Airflow, dbt, and Looker.

“The migration of our analytics platform from Amazon Redshift to Google BigQuery was a critical initiative for Peloton, and Onix proved to be an exceptional partner throughout. Their deep Google Cloud expertise and disciplined execution ensured a seamless transition. Onix’s Pelican tool enabled automated validation of 186 TB of historical data, giving us complete confidence at scale. The team also migrated thousands of database objects, modernized our dbt models, and repointed our Looker environment with minimal disruption. The result is a scalable, high-performance, and cost-efficient data platform built for growth. We highly recommend Onix for enterprise-scale cloud migrations.”

— David Glueck, VP – Data Science, Analytics & Governance

The Solution: Structured Migration to BigQuery

Onix led a seven-month migration from Amazon Redshift to Google BigQuery, following a phased, lift-and-shift approach to retain existing data models and business logic.

Architecture and Planning

The engagement began with a detailed architecture assessment and migration planning phase. Onix designed the future-state Google Cloud environment and defined a phased strategy to minimize risk and ensure continuity during the transition.

Migration at Scale

  • 11,962 tables and 5,144 views migrated
  • 101 stored procedures and 103 functions transitioned
  • 186 TB of historical data moved
  • 425 tables validated for data integrity

Pipeline and Workflow Transition

  • 6,297 dbt models refactored for BigQuery compatibility
  • 342 Airflow workflows reconfigured
  • Airbyte ingestion pipelines repointed to Google Cloud

Business Intelligence Continuity

  • 1,991 Looker objects repointed to BigQuery
  • 207 reports validated for accuracy

Automated Data Validation

Onix deployed Pelican to automate data validation between Redshift and BigQuery during parallel runs. This enabled large-scale dataset comparison, reduced manual effort, and ensured high confidence in data accuracy.

Deployment and Enablement

The migration concluded with production deployment of workloads along with documentation to support ongoing operations and platform management.

The Outcome

Peloton now operates on a modern, cloud-native analytics platform built on BigQuery:

  • Improved performance: Faster query execution and data processing
  • Scalability: Seamless support for growing data volumes and workloads
  • Cost efficiency: Optimized infrastructure and resource utilization
  • Operational simplicity: Streamlined pipelines, transformations, and workflows
  • Seamless transition: No disruption to existing dashboards or reporting

Looking Ahead

With its new analytics foundation in place, Peloton is well positioned to support advanced analytics, machine learning, and near real-time insights. The platform enables teams to focus less on infrastructure and more on using data to drive better member experiences and business outcomes.

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