85% cost reduction: A Case Study on how DataNimbus Designer accelerates workflows and reduces costs
About the organization A leading player in the general insurance industry, this organization serves both individual and corporate clients with a diverse portfolio of insurance products. Committed to innovation and customer-centric solutions, they continuously upgrade their technology stack to enhance operational efficiency and service quality. Business Challenges The organization sought to improve the efficiency of its ETL (Extract, Transform, Load) pipelines, particularly in processing complex JSON documents and optimizing Databricks compute costs. Key areas of concern for the organization were: High Compute Costs and Slow ETL runtimes –Extensive compute resource consumption led to prolonged runtimes and inflated operational costs in Databricks. Complex Data Parsing – Extracting insights from intricate JSON data structures posed a significant challenge for reporting and analysis. Hardcoded ETLs & Schema Management Issues – Hardcoded ETLs and st...