Analytics discussion with Case Studies: Join 100+ Telecom Council members members, telcos, vendors, startups, and VCs to discuss Analytics, and to share learnings from real-world implementations.

  • Date: 6/2/2016 08:30 AM
  • Location: VMware, Palo Alto CA (Map)

Agenda, Attendee List, & Presentation files available to Telecom Council members in the library.



Silicon Valley, California, Jun 2 2016/Meeting Recap/  It may be no surprise that FICO invented “the FICO score,” but when you consider the larger implication of their 1989 Big Data Roll-Out—as Sr. FICO Scientist, Jehan Athwal, had us do at our Case Studies discussion at VMware- 

you realize that a personal FICO score did not merely act as a passport into ever-larger financial transactions for each of us, it also increased the security of a market needing greater visibility for merchants and vendors attempting to grow themselves.  Those three-digit numbers opened a new world for us all. This is what the visibility of Big Data accomplishes: immediate conceptualization of the numerically obtuse.

No better example yesterday than Kentik’s visual reporting on its capacity to expose network relationships for Networking Engineering & Operations.  Making what has to be the most complex routing for any of us to conceptualize–paths of data traffic from originator to recipient around the world–into what we can only be described as concurrent interlacing ribbons of transmission: these are a must-see.  Request the deck from Jim Frey.

With Peter Jarich, VP at Current Analysis, providing context for the overall discussion and contributions from:

  • Art2Wave: real-time AI increases adoption of Wi-Fi as a Service
  • Cask Data (with assistance from Microsoft): accelerating cloud adoption
  • MapR:  Industrial Internet Case Study
  • Pluribus Networks: surpassing legacy networking monitoring tools
  • Daitan Group: identifying new monetization opportunities

–this was one of those meetings you didn’t want to end.

But end it did, with startup ThinkCX pitching a solution which identifies subscribers most likely to bolt from service provides long before they do it, by identifying key social media behavior–sort of a new FICO Consumer Loyalty Score.

Note: R&D in Mapping was occurring in the back of the room with MapR’s doppelganger, MapD, a big data startup, still showing off its real-time drill-down into an immense amount of data instantly–search for your past political donations in this election year: