Data Warehouse Augmentation to Increase Storage Capacity and Speed Processing

March 1, 2017

Zaloni Verizon Telecommunications Case Study

Verizon, a leading wireless network provider that designs, builds and operates networks, information systems, and mobile communication technologies wanted to speed and enhance its data analytics capability and improve archiving and recovery using a scalable big data platform.  

Before the data lake: Nearly 90% of Verizon’s enterprise data warehouse (EDW) platform was used for extract, load and transform (ELT) processes. The company needed to free up CPU so that the EDW could be used for true data warehousing, as well as business intelligence practices. In addition, existing archival and restore processes were manual and high risk. Verizon needed disk-based and system-driven backups, as well as a solution to support longer data retention periods for historical data and enable ad hoc analytics and data mining.

With the data lake: Verizon’s new hybrid Hadoop and Teradata environment dramatically increased storage capacity and processing speed and reduced costs. This was done without impacting the division’s upstream/downstream business systems and ultimately the business end user experience. With timesaving, local data processing and all raw data – above and beyond what was in the EDW – stored on the Hadoop platform, data could easily be accessed for analytics if it became important in the future.

Results: The solution reduced CapEx by $33 million over five years, increased storage capacity 20x and achieved a 100x cost reduction per terabyte ($200K/TB for Teradata, $2K/TB for Hadoop).

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