Ready to use data science clusters

Harness the power of AI through a simplified approach to clustering.

Financial services businesses often leverage clustering to improve their supervised machine learning algorithms. However, simple tasks such as launching, scaling, and terminating clusters to power data science platforms can be complicated and unreliable, severely limiting team productivity.

A unified analytics platform with ready to use data science clusters can help financial service customers across capital markets, banking, payments, insurance, and FinTech eliminate the need for disjointed tools. Data scientists no longer have to wait for an infrastructure team to provision and configure hardware for them, but instead, can be up and running in minutes so they can focus on building models that drive innovation. With optimized, highly elastic clusters at their fingertips, analysts and data scientists can now explore petabytes of data in real-time.

Ready-to-use data science clusters

Solutions

Databricks

Databricks Unified Analytics Platform offers real-time collaboration, one-click visualizations, and built-in data source connectors and integrations with BI tools. Databricks provides data science and engineering teams with ready-to-use clusters and various machine learning frameworks coupled with powerful collaboration capabilities to improve productivity across the machine learning lifecycle.

Databricks offers cluster management without human intervention. Databricks clusters located within the Databricks VPC access data directly from AWS S3. Refer to the diagram below to see how Databricks fully integrates with AWS services.

Databricks Unified Analytics Platform
FINRA

FINRA leverages Databricks and machine learning to detect fraudulent securities trading

FINRA was experiencing difficulty in their development and debugging their processes, which resulted in long development cycles due to segmented data scientist and engineering teams.

Databricks provided FINRA with an analytics platform that democratizes data and brings previously segmented teams together. As a result, overall time to market was reduced and operational efficiency improved.

Saman Michael Far's quote
With the Databricks environment and the notebooks and the richness of the languages and the possibilities of that, we have one cohesive end-to-end process with one single unified team working on these various aspects together.
- Saman Michael Far, Senior Vice President of Technology at FINRA
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