As a presenter of advanced analytics proof of concepts to other corporations, I am questioned most frequently on the “how” by my audiences. Not the “how” about the technology or the data we used, but “how” we were able to gain momentum and support in a large corporate enterprise to incorporate new technology and practices in analytics. I will share with you how a major telecommunications company, Sprint, created a research team of just 8 people who were able to infect the Enterprise with new infrastructure, new data, and new analytics and transforming them into new business benefits.
When I speak with other companies on advanced analytics proof of concepts, the focus of their questions skips quickly past the “what” onto the “how” – how did we gain support, how did we find success, how did we decide which technology to select. I will share with you some of the lessons we learned as well as answer many of these questions. This discussion will showcase how Sprint, a major telecommunications company, went from issuing a research challenge to enabling the entire enterprise in the area of analytics. I’ll walk you through how we repurposed an existing team and started with our first Proof of Concept on Hadoop. We are now in the midst of setting up a multi-petabyte enterprise supported Hadoop system with multiple funded projects, are augmenting our research facilities, and have a long list of use case trials in the works.
Capture data “before” it is processed by the Enterprise databases
Merge streaming Data with static data from existing databases
Include geospatial tools from the start
Allow standard query language to allow anyone to access & use
Make it easy to create UDFs
Use off the shelf hardware and open source where possible
Use off the shelf visualization tools