Case Study: Fortune 500 E-Commerce Company achieves real-time Twitter sentiment analysis with Cask Data

Fortune 500 E-Commerce Company - Customer Case Study

A Fortune 500 E-Commerce Company needed a faster, less expensive data pipeline to ingest Twitter data in real time, cleanse and transform tweets, and perform sentiment analysis on marketing campaigns. Its legacy pipeline was too slow and costly, so it turned to Cask Data and Cask Hydrator, part of the Cask Data Application Platform (CDAP), to support the effort.

Using Cask Data, the company’s Java developers built the real-time pipeline in just two weeks with a drag-and-drop interface, added a custom sentiment analysis transform, and used CDAP’s Cube Plugin for multidimensional aggregations without writing code. The result was real-time processing at full Twitter firehose speed, a four-hour learning curve for the team, faster decision-making, lower costs, and a consolidated Hadoop-based infrastructure.