Reported impact
Business outcome
Oakbrook now has a platform that is faster, scalable, more reliable, and secure, leading to considerable cost efficiencies and valuable new business use cases. Over the first three years, the company projects that they will realize cost savings of 14% through productivity gains and optimized compute.
- Cost Reduction
- Productivity Improvement
- Revenue Growth
Solution
Oakbrook built its Databricks implementation around Delta Lake, Unity Catalog, Databricks Data + AI Platform, BigQuery. Stringent regulation and outdated approaches to consumer lending have made it more difficult for many consumers across the UK to obtain loans. However, fintech organizations such as Oakbrook Finance are revolutionizing the lending sector, bringing more agile decision-making driven by advanced data science models and analytics. Delta Lake stores curated lakehouse tables with ACID guarantees for downstream analytics and machine learning. Unity Catalog applies centralized governance, lineage, auditing, and access control across shared data assets. Databricks Data + AI Platform provides the shared lakehouse environment for ingestion, engineering, analytics, and AI workflows in this deployment. BigQuery acts as a remote analytics source queried alongside Databricks data.
Data flow
Source data and events are ingested through managed connectors, files, or streaming feeds into databricks, curated in Delta Lake tables, processed with Databricks compute and orchestration services, and exposed to downstream analytics and users. It connects with BigQuery.