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APAC Big Data Strategy 2013
APAC Product Marketing Manager
Datacenter and Embedded Systems
RK Hiremane
Lighting Up Unused Data for Big Impact
2013 2014 2015 2016 2017
Acceleration of adoption of Hadoop
Apache Hadoop deployed on Intel Xeon2 years faster
Intel® Xeon processor growth from big data use
Uni
ts
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
Sample text
Flytxt Overview
2/27/2013Copyright © 2013 Flytxt B.V. All rights reserved6
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
Sample text
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 Cloud Computing Challenge Winner
Vision, Mission & Achievements Customers
Company
Flytxt
• Provide telcos with big data applications which increase demand, revenue, loyalty, and customer satisfaction AND that reduce churn, revenue leakage, fraud and direct costs
• Highly scalable platform: deployed across 400M+ subscribers
• Proven: 2% to 7% economic benefit to customers
Big Data
Descriptive Analysis
Clustering Analysis
Predictive Analysis
Deterministic Analysis
Correspondence Analysis
Variance Analysis
The team that introduced virtualization, grid and HPC x86 cluster computing to Singapore
• 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.
1999
eLinux
2001 2002 2003 2006 2009
Software Kit
APAC
Itanium Rocks!
2010 2012
Dr. Zhao PeiVP Business Development
Revolution Confidential
Laurence LiewGeneral Manager, APACRevolution Analytics
Revolution Confidential
11
Enterprise-ready Multi-platform Scalable from desktop to big data Delivers high performance analytics Easier to build and deploy analytic applications
Revolution Analytics is the leading commercial provider of software and support for the
open-source R statistical computing language
Revolution Analytics is the leading commercial provider of software and support for the
open-source R statistical computing language
Founded 2008
Office Locations Palo Alto (HQ), Seattle (Eng)Singapore (APAC HQ)London (EMEA HQ)
CEO David Rich
Number of customers 200+
Investors Northbridge Venture Partners, Intel Capital, Presidio Ventures
Revolution Confidential
Consumer & Info SvcsConsumer & Info Svcs
200 Corporate Customers and Growing
12
Finance & InsuranceFinance & Insurance Healthcare & Life SciencesHealthcare & Life Sciences
Manuf & TechManuf & TechAcademic & Gov’tAcademic & Gov’t
Revolution Confidential
Revolution Confidential
13
Real-time Big DataPredictive Analytics Stack
Revolution ConfidentialA Use Case for Retail Segment
14
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
BioScience: Genomics for Translational MedicineHadoop for Data Correlation & Discovery Insights
• Challenge: Derive new value added patient discovery services while bringing down genome processing costs
• 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
• Infrastructure and Data Characteristics: • 10 Node Hbase Cluster• Billions of pre-computed correlations
1 Genome 10 Million rows100 Genomes 1Billion rows
1M Genomes 10 Trillion rows
100M Genomes 1 Quadrillion 1,000,000,000,000,000 rows
Billions of Pre-computed Correlations
New Biomed Info-Products
Data Ingest
Telco- China Mobile Group GuangdongHadoop & 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 SystemHadoop for Predictive Analytics
19
• Challenge: Analyze city traffic to derive statistics for crime prevention, info sharing, and predictive traffic analysis
• Solution: Embed HBase client in camera for real-time inserts of structured/unstructured data
• Benefits: • Automated queries for traffic violation
• Data mining of fake licenses <1 minute for all data captured for a week
• Predictive traffic forecasting
• Data Characteristics: • 30000 + camera data collection points• Petabytes of traffic data & terabytes of images• 2 billion HBase records
App Servers
Regional Data Collection
Distributed Processing Across District Nodes
Derived Analytics Services
Crime Prevention Citizen Traffic Services