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Smarter Computing


Understand the likely impact of Stream
Computing and Big Data on your Business
and Data Center
How to control costs, improve performance, and mitigate risk
throughout the data lifecycle
IT needs to reinvent itself in order to enter this new era of
computing


                           Entering New Era of Computing
                                     Driven by…

                                    • Insatiable
                                      Demand
  Centralized      Distributed                              Smarter
  Computing        Computing        • Unsustainable        Computing
                                      Economics

                                    • New
                                      Technologies

 Efficient        Innovative                           Efficient &
                                                       Innovative
 but …            but …

 Limited access   Fueled sprawl &
 & flexibility    increased TCO


                                                                       1
The information supply chain



            Transactional &
            Collaborative                                               Analyze                     Business Analytics
            Applications                                                                                  Applications
                                                                              Content
                                        Integrate                             Analytics

                                                                                   Big Data
                                      Master
                                       Data
                      Manage                                                           Cubes



                                                                                          Streams
                     Data
                                                          Data
    External           Content                         Warehouses
    Information
    Sources               Streaming
                        Information
                                                    Govern

                                                            Security &
                                      Quality   Lifecycle              Standards
                                                             Privacy




2
                                                                                                                     2
What is ‘BIG’ Data



       4 Billion                                       10x
    # of cell phone users worldwide        Growth in digital data every 5 years



        2 Billion                                       5%
     # of Internet users worldwide         New Information that is structured




“     When physical assets such as cell phones, traffic sensors, cameras, PCs, RFID tags etc.
    become elements of an information system with ability to capture, compute and communicate
        information themselves on a massive sensor scale using common TCP/IP protocol.
                                                       -- Internet of Things by McKinsey Global Institute, 2010
                                                                                                                  “
                                      The Industrial Revolution of Data.
                                                                            -- Dr. Joe Hellerstein, UC Berkeley


                                                                                                                  3
The opportunity for real-time analytic processing
is everywhere …

                                  Stock market
                                  • Impact of weather on
                                    securities prices
                                  • Analyze market data at   Law Enforcement,
                                    ultra-low latencies
                                                             Defense & Cyber Security
       Natural Systems                                       • Real-time multimodal surveillance
       • Wildfire management                                 • Situational awareness
       • Water management                                    • Cyber security detection


      Transportation                                               Fraud prevention
      • Intelligent traffic                                        • Detecting multi-party fraud
        management                                                 • Real time fraud prevention


      Manufacturing                                                 e-Science
      • Process control for                                         • Space weather prediction
        microchip fabrication                                       • Detection of transient events
                                                                    • Synchrotron atomic research
      Health & Life Sciences
      • Neonatal ICU monitoring                              Other
      • Epidemic early warning        Telephony              •   Smart Grid
        system                        •   CDR processing     •   Text Analysis
                                      •   Social analysis    •   Who’s Talking to Whom?
      • Remote healthcare
        monitoring                    •   Churn prediction   •   ERP for Commodities
                                      •   Geomapping         •   FPGA Acceleration




                                                                                                      4
Evolution of technology frontiers



                                                  Dat
                                                      a in
                                                             M ot
                                                                    ion


                                                                          Real Time Analytic Processing
                                                                          (RTAP) to improve business
                    Data at rest                                          response
                                      Analysis of historic data
                                      to improve business                        Stream
     Reporting and                    transactions                               Computing
     human analysis on
     historical data                         Data
                                             Warehousing                            2003
               Operational
               Databases                     1983
                    1970                     DB2 v1
1968                Relational
                    database
Hierarchical
database

          OLTP                            OLAP                                       RTAP
Online Transaction Processing      Online Analytical Processing           ‘Real-Time’ Analytical Processing



                                                                                                              6
The Big Data Challenge

•   Manage and benefit from massive and growing amounts of data
•   Handle uncertainty around format variability and velocity of data
•   Handle unstructured data
•   Exploit BIG Data in a timely and cost effective fashion




                                        COLLECT        MANAGE
                                   Collect          Manage




                                   Integrate
                                       INTEGRATE    Analyze
                                                      ANALYZE




                                                                        7
IBM offers a comprehensive and integrated set of solutions
for many types of BIG Data processing needs



                                   Str e
                                        ams
                     BigInsights              filte
Non-Traditional                                       rs in
                                                           com
                                                              i   ng d
Data                                                                  ata




                                                               ere
                     WAREHOUSE                            foSph lytic
                                                      s In S Ana
 Traditional                                       use    S
                                               s re or SP
                                             m se
 Data                                      a
                                       Stre ehou
                                           r
                                        Wa els
                                             d
                                         mo

                  Persistent                                            In-Motion
                  Data                                                  Data

                                                                                    9
The Big Data ecosystem: Interoperability is key




                                BigInsights



                                                  User results




                                      WAREHOUSE
Data Sources
 Data can flow into one or
 more of the environments
 (even simultaneously)


                                                                 10
IBM InfoSphere Streams


Stream         RTAP
Analytics
                                In-Motion
                                                       Ultra Low
                  Non-          Analytics
                                                       Latency Results
               Traditional /
              Non- Relational
               Data Sources




              OLAP / OLTP
Traditional
Analytics
               Traditional /
              Relational Data
                  Sources
                                                       At-Rest
                                            Database                     Results
                                                       Data
                                                       Analytics



                                                                             11
InfoSphere Streams for companies who need to …

                                                    Real-time delivery

                                             ICU                       Environment
• Deal with Gigabytes of data each         Monitoring                   Monitoring

  second                                 Algo              Powerful              Telco churn
                                        Trading            Analytics               predict
• Work with application, sensor                Cyber                       Smart
                                              Security     Government /     Grid
  and internet data, video/audio                         Law enforcement

• Deliver insight in microseconds
  to analytical applications
                                      Millions of
                                      events per                               Microsecond
• Support complex scenarios using                                                Latency
                                       second
  C++ or Java code
• Integrate with existing analytics
                                                         Traditional /
  & data warehousing investments                        Non-traditional
                                                         data sources




                                                                                               12
Cyber security example – Detecting botnets



                  Real-time                                            Data-at-rest
                  Analytics                                             Analytics
                                                                                    BigInsights
                                                      Custom
                            Retain                 Visualizations
                           Aggregate
                           + Results

              Real-time
              Window


      Real-time Data
      (Traffic Capture,
      Alerts, Logs, …)                                              Data-At-Rest Window


                                       Aggregated TRAFFIC + DNS + Secondary Information
                                                                                        Alerts etc.
                                                                             PCAP/
          Now                              Aggregated Past                    PCAP/
                                                                             Netflow
                                                                              Netflow
                                                                                         Alerts

          IBM Commercially Sensitive



                                                                                                15
IBM is uniquely positioned to help organizations handle their
“BIG Data” analysis and management challenges




     Integrate                Automate                   Secure



  • Scale to petabytes and thousands of users
  • Deep integration with Cognos and SPSS
  • Integrated analysis and analytic model consistency




                                                                  17
Thank You!
ibm.com/smartercomputing



                                             Automate




                                  Integrate                 Secure
                           Efficient and Innovative IT for Improved Economics




                                                                           19
Trademarks and disclaimers
Intel, Intel logo, Intel Inside, Intel Inside logo, Intel Centrino, Intel Centrino logo, Celeron, Intel Xeon, Intel SpeedStep, Itanium, and Pentium are trademarks or
registered trademarks of Intel Corporation or its subsidiaries in the United States and other countries./ Linux is a registered trademark of Linus Torvalds in the
United States, other countries, or both. Microsoft, Windows, Windows NT, and the Windows logo are trademarks of Microsoft Corporation in the United States,
other countries, or both. IT Infrastructure Library is a registered trademark of the Central Computer and Telecommunications Agency which is now part of the Office
of Government Commerce. ITIL is a registered trademark, and a registered community trademark of the Office of Government Commerce, and is registered in the
U.S. Patent and Trademark Office. UNIX is a registered trademark of The Open Group in the United States and other countries. Java and all Java-based
trademarks and logos are trademarks or registered trademarks of Oracle and/or its affiliates. Other company, product, or service names may be trademarks or
service marks of others. Information is provided "AS IS" without warranty of any kind.

The customer examples described are presented as illustrations of how those customers have used IBM products and the results they may have achieved. Actual
environmental costs and performance characteristics may vary by customer.

Information concerning non-IBM products was obtained from a supplier of these products, published announcement material, or other publicly available sources
and does not constitute an endorsement of such products by IBM. Sources for non-IBM list prices and performance numbers are taken from publicly available
information, including vendor announcements and vendor worldwide homepages. IBM has not tested these products and cannot confirm the accuracy of
performance, capability, or any other claims related to non-IBM products. Questions on the capability of non-IBM products should be addressed to the supplier of
those products.

All statements regarding IBM future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only.

Some information addresses anticipated future capabilities. Such information is not intended as a definitive statement of a commitment to specific levels of
performance, function or delivery schedules with respect to any future products. Such commitments are only made in IBM product announcements. The information
is presented here to communicate IBM's current investment and development activities as a good faith effort to help with our customers' future planning.

Performance is based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput or performance that
any user will experience will vary depending upon considerations such as the amount of multiprogramming in the user's job stream, the I/O configuration, the
storage configuration, and the workload processed. Therefore, no assurance can be given that an individual user will achieve throughput or performance
improvements equivalent to the ratios stated here.

Prices are suggested U.S. list prices and are subject to change without notice. Starting price may not include a hard drive, operating system or other features.
Contact your IBM representative or Business Partner for the most current pricing in your geography.

Photographs shown may be engineering prototypes. Changes may be incorporated in production models.

© IBM Corporation 2011. All rights reserved.
References in this document to IBM products or services do not imply that IBM intends to make them available in every country.

Trademarks of International Business Machines Corporation in the United States, other countries, or both can be found on the
World Wide Web at http://www.ibm.com/legal/copytrade.shtml.                                                                                    ZSP03491-USEN-00



                                                                                                                                                                   20

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Smarter Computing Big Data

  • 1. Smarter Computing Understand the likely impact of Stream Computing and Big Data on your Business and Data Center How to control costs, improve performance, and mitigate risk throughout the data lifecycle
  • 2. IT needs to reinvent itself in order to enter this new era of computing Entering New Era of Computing Driven by… • Insatiable Demand Centralized Distributed Smarter Computing Computing • Unsustainable Computing Economics • New Technologies Efficient Innovative Efficient & Innovative but … but … Limited access Fueled sprawl & & flexibility increased TCO 1
  • 3. The information supply chain Transactional & Collaborative Analyze Business Analytics Applications Applications Content Integrate Analytics Big Data Master Data Manage Cubes Streams Data Data External Content Warehouses Information Sources Streaming Information Govern Security & Quality Lifecycle Standards Privacy 2 2
  • 4. What is ‘BIG’ Data 4 Billion 10x # of cell phone users worldwide Growth in digital data every 5 years 2 Billion 5% # of Internet users worldwide New Information that is structured “ When physical assets such as cell phones, traffic sensors, cameras, PCs, RFID tags etc. become elements of an information system with ability to capture, compute and communicate information themselves on a massive sensor scale using common TCP/IP protocol. -- Internet of Things by McKinsey Global Institute, 2010 “ The Industrial Revolution of Data. -- Dr. Joe Hellerstein, UC Berkeley 3
  • 5. The opportunity for real-time analytic processing is everywhere … Stock market • Impact of weather on securities prices • Analyze market data at Law Enforcement, ultra-low latencies Defense & Cyber Security Natural Systems • Real-time multimodal surveillance • Wildfire management • Situational awareness • Water management • Cyber security detection Transportation Fraud prevention • Intelligent traffic • Detecting multi-party fraud management • Real time fraud prevention Manufacturing e-Science • Process control for • Space weather prediction microchip fabrication • Detection of transient events • Synchrotron atomic research Health & Life Sciences • Neonatal ICU monitoring Other • Epidemic early warning Telephony • Smart Grid system • CDR processing • Text Analysis • Social analysis • Who’s Talking to Whom? • Remote healthcare monitoring • Churn prediction • ERP for Commodities • Geomapping • FPGA Acceleration 4
  • 6. Evolution of technology frontiers Dat a in M ot ion Real Time Analytic Processing (RTAP) to improve business Data at rest response Analysis of historic data to improve business Stream Reporting and transactions Computing human analysis on historical data Data Warehousing 2003 Operational Databases 1983 1970 DB2 v1 1968 Relational database Hierarchical database OLTP OLAP RTAP Online Transaction Processing Online Analytical Processing ‘Real-Time’ Analytical Processing 6
  • 7. The Big Data Challenge • Manage and benefit from massive and growing amounts of data • Handle uncertainty around format variability and velocity of data • Handle unstructured data • Exploit BIG Data in a timely and cost effective fashion COLLECT MANAGE Collect Manage Integrate INTEGRATE Analyze ANALYZE 7
  • 8. IBM offers a comprehensive and integrated set of solutions for many types of BIG Data processing needs Str e ams BigInsights filte Non-Traditional rs in com i ng d Data ata ere WAREHOUSE foSph lytic s In S Ana Traditional use S s re or SP m se Data a Stre ehou r Wa els d mo Persistent In-Motion Data Data 9
  • 9. The Big Data ecosystem: Interoperability is key BigInsights User results WAREHOUSE Data Sources Data can flow into one or more of the environments (even simultaneously) 10
  • 10. IBM InfoSphere Streams Stream RTAP Analytics In-Motion Ultra Low Non- Analytics Latency Results Traditional / Non- Relational Data Sources OLAP / OLTP Traditional Analytics Traditional / Relational Data Sources At-Rest Database Results Data Analytics 11
  • 11. InfoSphere Streams for companies who need to … Real-time delivery ICU Environment • Deal with Gigabytes of data each Monitoring Monitoring second Algo Powerful Telco churn Trading Analytics predict • Work with application, sensor Cyber Smart Security Government / Grid and internet data, video/audio Law enforcement • Deliver insight in microseconds to analytical applications Millions of events per Microsecond • Support complex scenarios using Latency second C++ or Java code • Integrate with existing analytics Traditional / & data warehousing investments Non-traditional data sources 12
  • 12. Cyber security example – Detecting botnets Real-time Data-at-rest Analytics Analytics BigInsights Custom Retain Visualizations Aggregate + Results Real-time Window Real-time Data (Traffic Capture, Alerts, Logs, …) Data-At-Rest Window Aggregated TRAFFIC + DNS + Secondary Information Alerts etc. PCAP/ Now Aggregated Past PCAP/ Netflow Netflow Alerts IBM Commercially Sensitive 15
  • 13. IBM is uniquely positioned to help organizations handle their “BIG Data” analysis and management challenges Integrate Automate Secure • Scale to petabytes and thousands of users • Deep integration with Cognos and SPSS • Integrated analysis and analytic model consistency 17
  • 14. Thank You! ibm.com/smartercomputing Automate Integrate Secure Efficient and Innovative IT for Improved Economics 19
  • 15. Trademarks and disclaimers Intel, Intel logo, Intel Inside, Intel Inside logo, Intel Centrino, Intel Centrino logo, Celeron, Intel Xeon, Intel SpeedStep, Itanium, and Pentium are trademarks or registered trademarks of Intel Corporation or its subsidiaries in the United States and other countries./ Linux is a registered trademark of Linus Torvalds in the United States, other countries, or both. Microsoft, Windows, Windows NT, and the Windows logo are trademarks of Microsoft Corporation in the United States, other countries, or both. IT Infrastructure Library is a registered trademark of the Central Computer and Telecommunications Agency which is now part of the Office of Government Commerce. ITIL is a registered trademark, and a registered community trademark of the Office of Government Commerce, and is registered in the U.S. Patent and Trademark Office. UNIX is a registered trademark of The Open Group in the United States and other countries. Java and all Java-based trademarks and logos are trademarks or registered trademarks of Oracle and/or its affiliates. Other company, product, or service names may be trademarks or service marks of others. Information is provided "AS IS" without warranty of any kind. The customer examples described are presented as illustrations of how those customers have used IBM products and the results they may have achieved. Actual environmental costs and performance characteristics may vary by customer. Information concerning non-IBM products was obtained from a supplier of these products, published announcement material, or other publicly available sources and does not constitute an endorsement of such products by IBM. Sources for non-IBM list prices and performance numbers are taken from publicly available information, including vendor announcements and vendor worldwide homepages. IBM has not tested these products and cannot confirm the accuracy of performance, capability, or any other claims related to non-IBM products. Questions on the capability of non-IBM products should be addressed to the supplier of those products. All statements regarding IBM future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only. Some information addresses anticipated future capabilities. Such information is not intended as a definitive statement of a commitment to specific levels of performance, function or delivery schedules with respect to any future products. Such commitments are only made in IBM product announcements. The information is presented here to communicate IBM's current investment and development activities as a good faith effort to help with our customers' future planning. Performance is based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput or performance that any user will experience will vary depending upon considerations such as the amount of multiprogramming in the user's job stream, the I/O configuration, the storage configuration, and the workload processed. Therefore, no assurance can be given that an individual user will achieve throughput or performance improvements equivalent to the ratios stated here. Prices are suggested U.S. list prices and are subject to change without notice. Starting price may not include a hard drive, operating system or other features. Contact your IBM representative or Business Partner for the most current pricing in your geography. Photographs shown may be engineering prototypes. Changes may be incorporated in production models. © IBM Corporation 2011. All rights reserved. References in this document to IBM products or services do not imply that IBM intends to make them available in every country. Trademarks of International Business Machines Corporation in the United States, other countries, or both can be found on the World Wide Web at http://www.ibm.com/legal/copytrade.shtml. ZSP03491-USEN-00 20