Case Study: Twitter achieves real-time social media monitoring with Cask Data

Twitter - Customer Case Study

Twitter needed a way to monitor the full Twitter stream in real time, cleanse and transform tweets, and run sentiment analysis to support marketing and brand tracking. The existing pipeline was complex, involving Storm, HBase, MySQL, and JBoss, and it added operational overhead while increasing latency for delivering insights to business users. Twitter used Cask Data’s Cask Hydrator and CDAP for this real-time analytics use case.

Cask Data built a simplified pipeline that ingested and processed tweets, performed NLP-based sentiment analysis, and exposed aggregated results through REST APIs and dashboards. The solution was completed in two weeks, handled about 6K tweets per second in-flight, consolidated infrastructure into a single Hadoop cluster, and helped Twitter make faster decisions with lower-latency, self-service analytics and better operational insight.

Twitter