Telco Big Data and Real Time Analytics Summit

I’ll be in London next week (3-5 Dec) at the Telco Big Data and Real Time Analytics Summit, it’s the first time this conference has run, and I think presents an important opportunity to cut through all the hype and BS we’re seeing on Big Data.  The conference itself is packed with operator presentations sharing their ‘at the coal-face‘ experiences from: Belgacom, BSkyB, Deustche Telekom, Du, EE (previously known as Everything Everywhere), France Telecom, OmanTel, Orange, P4(Play), Sprint, T-Mobile, Telefonica, Turkcell, Vodafone, etc.  As well as leaders in the implementation of Big Data and Real Time Analytics in Telecom like Guavus, who take what I consider a very practical, down to earth, and proven approach to helping operators use the insights they have available from their networks and services.

One of my pet peeves is when Big Data is used on slides, for example on something unrelated like DSRs (Diameter Signaling Routers), with no further explanation; they might as well say ‘some magic happens that we have no idea about’ rather than Big Data as it would be more accurate.  On the Monday I’ll be giving a pre-conference workshop providing a deep dive through Big Data and Real-Time Analytics in Telecoms, with the prime objective is cutting through all the hype and BS to help attendees understand what it really means to Telcos today and in the short-medium term.  I will be going through much of the technology and its application in web-scale applications, but critically looking at what it means to Telecoms given their specific situation and legacy environments.

Shown below is the outline of the workshop, it brought together several presentations and ended up at over 1000 slides, with lots of editing its down to 576 slides, not all will be presented during the day else the workshop will become an animation, some are reference.  I hope the workshop will provide a unique experience to understand the technologies behind all the hype, and more importantly what it really means to the majority of Telcos who are not green field.

“Introduction to Big Data and Real Time Analytics Workshop”

09:00    Registration

09:30    History and Overview: Understanding Big Data and Real-Time Analytics in Context

  • What do we mean by Big Data?
  • Why does Big Data matter?
  • Big Data Maturity
  • The 3Vs” Volume, Variety and Velocity
  • What are the Domains of Big Data?
  • Big Data Technologies
  • What Enterprises Think of Big Data
  • How Enterprise Verticals are Impacted by Big Data
  • Why Now?
  • Key Trends driving towards Big Data
  • History of Big Data
  • Taxonomy of Big Data Companies
  • Big Data Landscape
  • List of Companies in Big Data (and their Big Data revenues)
  • Big Data Market Sizing
  • Telecoms and Real-Time
  • O2 More: Proof we can do it!

10:45    Coffee Break

11:00    Quick Technology Review: Diving into a little detail on a few of the key technologies (only as deep as the architecture) to understand their history and capabilities / limitations

  • Hadoop
    • What is Hadoop?
    • Ecosystem
    • History
    • Design Axioms
    • Hadoop Distributed File System
    • MapReduce: Distributed Processing
    • Architecture
    • Data Schemas
    • Query Language Flexibility
    • Economics
    • Case Studies
  • Hadoop and Hbase in the Cloud (Amazon)
  • NoSQL and Cassandra + some use cases
  • Hbase versus Cassandra
  • Graph Database introduction

12:00 & 14:00 Application of Big Data

  • Hardware and Software Trends
    • Execution and Results Characteristics
    • Framework: Ecosystem, Application Services, Data Management
  • Real-Time Analytics
    • Use Cases
    • Extended RDMS versus MapReduce / Hadoop
    • Requirements, Trends, People and Organization Issues, Outlook
  • Big Data and the Cloud
    • Why the Cloud and Big Data?
    • Cloud benefits
    • Use Cases: Bankinter, Etsy, Razorfish
  • The Social Enterprise
    • Business Benefits
    • ALU example
    • Drivers
    • Social + Data Analysis = Business intelligence
    • AT&T Case Study
    • Lessons Learned
  • Telcos and Big Data
    • TMF Survey
    • Big Data Framework
    • Predictive / Adaptive Analytics
    • Decision Engineering
    • The Problem with Telecom
  • Telco Analytics
    • Customer Profiling
    • Next Product Tools
    • Marketing Mix Modeling
    • Cost of Acquisition Tools
    • Case Study

13:00ish Lunch (part way through the above session)

15:00    Ecosystem, Taxonomies and Suppliers: Understanding the many suppliers, technology camps, and approaches

  • Taxonomy of Big Data Companies
  • Big Data Landscape
  • Cloudera
  • Autonomy
  • Vertica
  • InfoChimps
  • Guavus
  • Matrixx

Case Studies

  • Real Time Analytics for Big Data Lessons from Facebook
    • Quick technology review
    • Facebook Real-time Analytics System
    • Goal
    • Actual Analytics
    • Solution
    • Memory, Collocate, Economics
  • Real Time Analytics for Big Data Lessons from Twitter
    • Requirements
    • Actual Analytics
    • Challenges
    • Performance
    • One data any API
    • Solution
    • Memory, Collocate, Economics
  • Other Case Studies
    • Orbitz, Hertz, Yelp

16:00 Global Enterprise and Telecom Survey on Big Data and Real-Time Analytics

  • Background
  • The Questions
  • The Importance of Analytics
  • Impact of Big Data on Analytics
  • Size of Data Sets, Number of Data Sources
  • Update Frequency
  • Integration of Data Sources
  • Data Set Responsibility
  • Types of Data, Types of Processing and Analytics
  • Challenges
  • Big Data Analytics Platforms
  • Benefits and Plans
  • Data Analytics Storage and IT Infrastructure Requirements
  • Increasing Interest in Hadoop MapReduce Framework Technology
  • Conclusions

17:00 Recommendations and Wrap Up