Case Study: Fortune 50 Financial Institution achieves faster, more reliable security analytics and reporting with Cask Data

Fortune 50 Financial Institution - Customer Case Study

A Fortune 50 Financial Institution was struggling with a legacy Hadoop-based batch pipeline that took up to six hours to run, required frequent manual intervention, and made reporting and testing difficult. The team also faced challenges with day-boundary misalignment, slow recovery from failures, and the heavy effort needed to add new data sources, so it turned to Cask Data and Cask Hydrator.

Cask Data implemented independent, parallel pipelines to move SQL data into Time Partitioned Datasets, perform in-flight transformations with error handling, and then consolidate the data into a single dataset for aggregation and reporting. The result was a much simpler process that ran in about two hours instead of six, needed no manual intervention, and let in-house developers build and run the pipelines in scale within two weeks after only four hours of training.