Sprint Network Forecast Analytics with Teradata & Hadoop

Case Study
Sprint, one of the largest wireless service providers in the United States and a major global internet carrier, wanted to augment their existing Network Forecast Analytics (NFA) warehouse with new and larger sets of data for better and broader insights. Sprint needed to enhance their existing NFA solution with new and larger sets of data in a timely manner without causing disruption. However, the challenge was to ingest large data volumes into Hadoop for pre-processing along with offloading existing ETL rules onto Hadoop and then moving the pre-processed data into Teradata for further analytics. Since the anticipated data volumes were quite large, Sprint needed a technology that was up to the task. In addition, a technology was needed that could integrate data across Hadoop & Teradata in a unified fashion. It was also necessary to have an enterprise-grade solution to have a seamless integration with the corporate processes in the production environment.