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 markets1. 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• 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 SingaporeeLinux Itanium Rocks! APAC Software Kit 1999 2001 2002 2003 2006 2009 2010 2012• Next-generation HPC/Cloud/Analytics 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.
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 Confidential200 Corporate Customers and Growing Revolution Confidential Finance & Insurance Healthcare & Life Sciences Academic & Gov’t Consumer & Info Svcs Manuf & Tech 12
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
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
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
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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