Enterprise Lakehouse Modernization for Large-Scale Platform MigrationEnterprise Lakehouse Modernization for Large-Scale Platform Migration
Accelerated customer migration by restoring trust in historical and financial data
Enabled near-real-time reporting across high-volume transactional datasets
Improved data consistency through unified batch and streaming pipelines
Reduced operational friction caused by legacy ETL complexity
Established a scalable foundation for advanced analytics and ML workloads
Provided a governed data backbone supporting ongoing platform evolution
Business Objective
Our client, a fitness technology company, was migrating thousands of customers from a legacy platform to a next-generation ecosystem while preserving complete historical data accuracy. Any inconsistency in financial or operational data could impact reporting, billing, and customer trust.
At the same time, the business required near-real-time reporting and precise reconciliation across large volumes of transactional data, leaving no room for delays or discrepancies during the transition.
The Transformation
Exadel designed and delivered a Databricks-centered lakehouse platform using a Medallion architecture to unify batch and near-real-time processing.
Case Studies
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Real Results
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