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APAC Big Data Strategy 2013

       RK Hiremane
       APAC Product Marketing Manager
       Datacenter and Embedded Systems
Lighting Up Unused Data for Big Impact

 Acceleration of adoption of Hadoop

 Apache Hadoop deployed on Intel Xeon
                                                    2 years faster




                                                                           Units
                          Intel® Xeon processor growth from big data use

 2013            2014           2015           2016             2017
Where is the Opportunity?

• Telecommunications, financial services
• Government, healthcare
• Not just in the mature markets

1. Improve services to customers (& people)
2. New business opportunity to grow revenue
Democratize data analysis from edge to cloud


                                                Unlock value of Data

                                                Support Open Platforms

                                                Deliver software value




 Intel can deliver end-to-end from the edge intelligent systems to
                        the Datacenter/cloud
GTM Strategy

• OEMs
• System Integrators
• Independent Software Vendors
• Training partners
Flytxt Overview
     Vision, Mission & Achievements                                                                      Customers
   Our vision to create >10% economic value for Telcos from their
    data using Flytxt’s Big Data Solutions
   Decisioning Logic Units, derived from raw data through patent
    pending complex domain specific analytics technologies, drive
    the applications
   Red Herring Asia top 100 winner; NASSCOM Emerge 50; IEEE                                              Sample text
    Cloud Computing Challenge Winner
                                                                                                          Sample text


                         Company
   300+ employees. Management team with 150+ years in Telecom
    technology & business
   Dutch Company with its competencies centre at Trivandrum, India and
    offices at Delhi, Mumbai, Hong Kong, Dhaka, Lagos, Nairobi and Dubai




                                                                            6
                                                      Copyright © 2013 Flytxt B.V. All rights reserved                  2/27/2013
Flytxt

• Provide telcos with big data
  applications which increase demand,                    Correspondence
  revenue, loyalty, and customer                             Analysis
  satisfaction AND that reduce churn,       Descriptive                   Variance
  revenue leakage, fraud and direct          Analysis                     Analysis
  costs                                                       Big
                                                             Data
• Highly scalable platform: deployed        Clustering                 Deterministic
  across 400M+ subscribers                   Analysis                    Analysis

• Proven: 2% to 7% economic benefit                       Predictive
                                                           Analysis
  to customers
The team that introduced virtualization, grid and HPC x86 cluster computing to Singapore


eLinux


                                                         Itanium Rocks!

                                                         APAC
                                                         Software Kit

   1999        2001        2002           2003                 2006          2009         2010       2012


• Next-generation HPC/Cloud infrastructure provider. Customers include A*STAR, STEE, NEC, Singtel.
• More than a decade of experience architecting and implementing leading edge HPC and Grids, and now Cloud
  systems.
Dr. Zhao Pei
VP Business Development
Revolution Confidential




Laurence Liew
General Manager, APAC
Revolution Analytics
Revolution Confidential
    Revolution Analytics is the leading commercial provider of software
                              and support for the
                open-source R statistical computing language
      Enterprise-ready
      Multi-platform
      Scalable from desktop to big data
      Delivers high performance analytics
      Easier to build and deploy analytic applications


     Founded            2008                            Number of customers   200+
     Office Locations   Palo Alto (HQ), Seattle (Eng)   Investors             Northbridge Venture Partners,
                        Singapore (APAC HQ)                                   Intel Capital, Presidio Ventures
                        London (EMEA HQ)
     CEO                David Rich




                                                                                                                 11
Revolution Confidential


200 Corporate Customers and Growing                                       Revolution Confidential


         Finance & Insurance                          Healthcare & Life Sciences




  Academic & Gov’t             Consumer & Info Svcs                 Manuf & Tech




                                                                                               12
Revolution Confidential


Real-time
Big Data
Predictive
Analytics
Stack



                              13
A Use Case for Retail Segment                               Revolution Confidential




 Analyze and optimize marketing mix
    customer segmentation
    Revenue/ action attribution among channels and marketing
     programs
    Customized Next Best Action per individual prospect or customer;
     data granularity feeds the big data challenge




                                                                             14
BioScience: Genomics for Translational Medicine
                        Hadoop for Data Correlation & Discovery Insights
• Challenge: Derive new value added patient
  discovery services while bringing down genome
  processing costs
                                                                                 Data Ingest
• Solution: Dynamically partition & scale
  correlation of patient data to all public data
  using Hadoop and Hbase
• Benefits: Contributes to 800x reduction in cost
  to process 4 Million genome variants                                              Billions of Pre-
                                                                                 computed Correlations
• Infrastructure and Data Characteristics:
• 10 Node Hbase Cluster
                                                                  New Biomed Info-Products
• Billions of pre-computed correlations
    1 Genome  10 Million rows
    100 Genomes  1Billion rows
    1M Genomes  10 Trillion rows
    100M Genomes  1 Quadrillion 1,000,000,000,000,000 rows
Telco- China Mobile Group Guangdong
                          Hadoop & Xeon optimized Big Data storage & analytics
• Challenge: Dealing with large volume of data and
  delivering real time access to Call Data Records
  (CDR) for billing self service
• Solution: Chose Hadoop + Xeon over RDMS to
  remove data access bottlenecks, increase storage,
  and scale system
• Benefits: Lower TCO, 30x performance increase,
  stable operation, analytics on subscriber usage for
  targeted promotions
• Data Characteristics:
     – 30TB billing data/month
     – Real-time retrieval of 30 days CDRs
     – 300k records/second, 800k insert speed/sec
     – 15 analytics queries
     – 133 server nodes
Summary

• Accelerating the adoption of big data analytics
• Engaging with ecosystem and end-customers to unlock the value of data
• Delivering the full end-to-end capability of Intel from the edge intelligent
  systems to servers in the datacenter or cloud and with the Intel
  Distribution for Apache Hadoop
Public Sector- Smart Traffic Intelligent Transport System
                                       Hadoop for Predictive Analytics

• Challenge: Analyze city traffic to derive statistics                        Regional Data Collection

  for crime prevention, info sharing, and predictive
  traffic analysis
• Solution: Embed HBase client in camera for real-
  time inserts of structured/unstructured data                                                               App Servers

• Benefits:
                                                                   Distributed Processing Across District Nodes
• Automated queries for traffic violation
• Data mining of fake licenses <1 minute for all data
  captured for a week
• Predictive traffic forecasting
•    Data Characteristics:
                                                                    Derived                         Analytics Services
•    30000 + camera data collection points
•    Petabytes of traffic data & terabytes of images
•    2 billion HBase records
                                                                         Crime Prevention     Citizen Traffic Services

                                                                                                                         19

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APAC Big Data Strategy RadhaKrishna Hiremane

  • 1. APAC Big Data Strategy 2013 RK Hiremane APAC Product Marketing Manager Datacenter and Embedded Systems
  • 2. Lighting Up Unused Data for Big Impact Acceleration of adoption of Hadoop Apache Hadoop deployed on Intel Xeon 2 years faster Units Intel® Xeon processor growth from big data use 2013 2014 2015 2016 2017
  • 3. Where is the Opportunity? • Telecommunications, financial services • Government, healthcare • Not just in the mature markets 1. Improve services to customers (& people) 2. New business opportunity to grow revenue
  • 4. Democratize data analysis from edge to cloud Unlock value of Data Support Open Platforms Deliver software value Intel can deliver end-to-end from the edge intelligent systems to the Datacenter/cloud
  • 5. GTM Strategy • OEMs • System Integrators • Independent Software Vendors • Training partners
  • 6. Flytxt Overview Vision, Mission & Achievements Customers  Our vision to create >10% economic value for Telcos from their data using Flytxt’s Big Data Solutions  Decisioning Logic Units, derived from raw data through patent pending complex domain specific analytics technologies, drive the applications  Red Herring Asia top 100 winner; NASSCOM Emerge 50; IEEE Sample text Cloud Computing Challenge Winner Sample text Company  300+ employees. Management team with 150+ years in Telecom technology & business  Dutch Company with its competencies centre at Trivandrum, India and offices at Delhi, Mumbai, Hong Kong, Dhaka, Lagos, Nairobi and Dubai 6 Copyright © 2013 Flytxt B.V. All rights reserved 2/27/2013
  • 7. Flytxt • Provide telcos with big data applications which increase demand, Correspondence revenue, loyalty, and customer Analysis satisfaction AND that reduce churn, Descriptive Variance revenue leakage, fraud and direct Analysis Analysis costs Big Data • Highly scalable platform: deployed Clustering Deterministic across 400M+ subscribers Analysis Analysis • Proven: 2% to 7% economic benefit Predictive Analysis to customers
  • 8. The team that introduced virtualization, grid and HPC x86 cluster computing to Singapore eLinux Itanium Rocks! APAC Software Kit 1999 2001 2002 2003 2006 2009 2010 2012 • Next-generation HPC/Cloud infrastructure provider. Customers include A*STAR, STEE, NEC, Singtel. • More than a decade of experience architecting and implementing leading edge HPC and Grids, and now Cloud systems.
  • 9. Dr. Zhao Pei VP Business Development
  • 10. Revolution Confidential Laurence Liew General Manager, APAC Revolution Analytics
  • 11. Revolution Confidential Revolution Analytics is the leading commercial provider of software and support for the open-source R statistical computing language  Enterprise-ready  Multi-platform  Scalable from desktop to big data  Delivers high performance analytics  Easier to build and deploy analytic applications Founded 2008 Number of customers 200+ Office Locations Palo Alto (HQ), Seattle (Eng) Investors Northbridge Venture Partners, Singapore (APAC HQ) Intel Capital, Presidio Ventures London (EMEA HQ) CEO David Rich 11
  • 12. Revolution Confidential 200 Corporate Customers and Growing Revolution Confidential Finance & Insurance Healthcare & Life Sciences Academic & Gov’t Consumer & Info Svcs Manuf & Tech 12
  • 14. A Use Case for Retail Segment Revolution Confidential  Analyze and optimize marketing mix  customer segmentation  Revenue/ action attribution among channels and marketing programs  Customized Next Best Action per individual prospect or customer; data granularity feeds the big data challenge 14
  • 15. BioScience: Genomics for Translational Medicine Hadoop for Data Correlation & Discovery Insights • Challenge: Derive new value added patient discovery services while bringing down genome processing costs Data Ingest • Solution: Dynamically partition & scale correlation of patient data to all public data using Hadoop and Hbase • Benefits: Contributes to 800x reduction in cost to process 4 Million genome variants Billions of Pre- computed Correlations • Infrastructure and Data Characteristics: • 10 Node Hbase Cluster New Biomed Info-Products • Billions of pre-computed correlations 1 Genome  10 Million rows 100 Genomes  1Billion rows 1M Genomes  10 Trillion rows 100M Genomes  1 Quadrillion 1,000,000,000,000,000 rows
  • 16. Telco- China Mobile Group Guangdong Hadoop & Xeon optimized Big Data storage & analytics • Challenge: Dealing with large volume of data and delivering real time access to Call Data Records (CDR) for billing self service • Solution: Chose Hadoop + Xeon over RDMS to remove data access bottlenecks, increase storage, and scale system • Benefits: Lower TCO, 30x performance increase, stable operation, analytics on subscriber usage for targeted promotions • Data Characteristics: – 30TB billing data/month – Real-time retrieval of 30 days CDRs – 300k records/second, 800k insert speed/sec – 15 analytics queries – 133 server nodes
  • 17. Summary • Accelerating the adoption of big data analytics • Engaging with ecosystem and end-customers to unlock the value of data • Delivering the full end-to-end capability of Intel from the edge intelligent systems to servers in the datacenter or cloud and with the Intel Distribution for Apache Hadoop
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  • 19. Public Sector- Smart Traffic Intelligent Transport System Hadoop for Predictive Analytics • Challenge: Analyze city traffic to derive statistics Regional Data Collection for crime prevention, info sharing, and predictive traffic analysis • Solution: Embed HBase client in camera for real- time inserts of structured/unstructured data App Servers • Benefits: Distributed Processing Across District Nodes • Automated queries for traffic violation • Data mining of fake licenses <1 minute for all data captured for a week • Predictive traffic forecasting • Data Characteristics: Derived Analytics Services • 30000 + camera data collection points • Petabytes of traffic data & terabytes of images • 2 billion HBase records Crime Prevention Citizen Traffic Services 19