Case Study: a leading insurance provider achieves enterprise-scale data delivery with Fractal

An insurer builds a scalable data preparation tool to give data scientists highly-granular data

A leading insurance company faced significant challenges in processing and delivering complex, large-scale data to its data science team. Their manual ETL processes created bottlenecks, and they struggled to handle massive volumes of deeply nested XML data with inconsistent schema variations. They partnered with Fractal to address these issues and build a sophisticated data delivery platform.

Fractal implemented a unified platform featuring intelligent data processing, automated field extraction, and scalable decompression to handle the complex data. The solution included a Python Flask-based data preparation tool, providing users with high granularity access and streamlined performance. This transformation provided the insurance company with automated ETL workflows for continuous data processing and granted its data science team complete granular access to all data elements.