In-flight brand sentiment analysis of the Twitter Firehose
A Fortune 500 e-commerce company built a data pipeline that ingested their Twitter stream in real-time. The data was cleansed and transformed prior to conducting multi-dimensional aggregation and sentiment analysis on marketing campaigns based on tweets. The results were updated twice daily to HBase. However, the legacy pipeline suffered on two fronts: first, latency in the existing pipeline delayed the decision making process. Second, the existing data movement process proved to be costly in time and money.
CDAP value proposition(s)
The company’s in-house team of Java developers built a real-time pipeline in two weeks using the drag-and-drop visual interface in CDAP.
They developed a sentiment analysis transform using the API and then included it in the pipeline. Further, they added multidimensional aggregations without needing to write code using the Cube Plugin as a sink.