Hybrid Cloud, BigData and Consumerization The 2012 Trends

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Presentation by Danairat T.on " Tech Trends 2012" at Software Park on Jan 26, 2012

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Hybrid Cloud, BigData and Consumerization The 2012 Trends

  1. 1. Hybrid Cloud, BigData and ConsumerizationThe 2012 TrendsDanairat T.Enterprise Architect, ASEANdanairat.thanabodithammachari@oracle.com, +66-81-559-1446
  2. 2. The following is intended to outline our general productdirection. It is intended for information purposes only, and maynot be incorporated into any contract. It is not a commitment todeliver any material, code, or functionality, and should not berelied upon in making purchasing decisions.The development, release, and timing of any features orfunctionality described for Oracle’s products remain at the solediscretion of Oracle.
  3. 3. Oracle The world’s most complete, open, and integrated business software and hardware systemsType Public (NASDAQ: ORCL)Industry Computer software, HardwareFounded California, USA (1977)Founder(s) Larry Ellison, Bob Miner, Ed Oates 500 Oracle Parkway, RedwoodHeadquarters City, California, United StatesArea served Worldwide (145 countries)
  4. 4. Complete. Open. Integrated. Leader. • Database • Data Warehousing • Business Intelligence Applications • Enterprise Performance Management • System, Hardware, Storage • Middleware • Application Server • Identity Management • Customer Relationship Management • Human Capital Management • Supply Chain Management • Retail • Financial Services • Banking • Public Sector • Communications • Professional Services
  5. 5. Agenda • Introduction and Consumerization • Hybrid Cloud Computing • Big Data • Q&A
  6. 6. The Enterprise Reference Architecture Core Systems
  7. 7. The Enterprise Reference Architecture Access Channels Integration and Channel Systems Core Systems Enterprise Information Management
  8. 8. The Enterprise Reference Architecture Access Channels Integration and Channel Systems Insight Sales and and MarketingMonitoring Core Systems Enterprise Information Management
  9. 9. The Enterprise Reference Architecture Access Channels Integration and Channel Systems Insight Sales and Corporate Regulatory and Marketing Admin. ComplianceMonitoring Core Systems Enterprise Information Management
  10. 10. The Enterprise Reference Architecture Access Channels Integration and Channel Systems Insight Sales and Corporate Regulatory and Marketing Admin. ComplianceMonitoring Core Systems Enterprise Information Management System Security/ Monitoring Enterprise Infrastructure Auditing and andManagement Identity Management
  11. 11. The Enterprise Reference Architecture Access Channels Integration and Channel Systems Insight Sales and Corporate Regulatory and Marketing Admin. ComplianceMonitoring Core Systems Enterprise Information Management System Security/ Monitoring Enterprise Infrastructure Auditing and andManagement Identity Management
  12. 12. The Enterprise Reference Architecture Access Channels Integration and Channel Systems Insight Sales and Corporate Regulatory and Marketing Admin. ComplianceMonitoring Core Systems Enterprise Information Management Customer Data Product Data Payment Data Accounting Org. Hierarchy Enterprise Infrastructure User Centric System Process Centric Security/ Monitoring Auditing Data Centric and andManagement Decision Centric Identity Management H/W, Storage, OS, Database, AppServer Platform
  13. 13. Consumerization and Enterprise Systems• Social Network Application• Location Based Application• Smart Touch Phone• Tablets• Smart TV• WIFI Digital Camera• Portable 3G Router
  14. 14. Consumerization and Enterprise Systems• Social Network Application• Location Based Application• Smart Touch Phone• Tablets• Smart TV• WIFI Digital Camera• Portable 3G Router Consumerization and Mobile Workforce
  15. 15. Enterprise Systems Trend From Consolidation to Cloud Private Cloud App1 App2 App3 App1 App2 App3 Private PaaS Private IaaS Silo’d Grid• Physical • Virtual• Dedicated • Shared services• Static • Dynamic• Heterogeneous • Standardized appliances
  16. 16. Enterprise Systems Trend From Consolidation to Cloud Private Cloud App1 App2 App3 App1 App2 App3 App1 App2 App3 Private PaaS Private PaaS Private IaaS Private IaaS Silo’d Grid Private Cloud• Physical • Virtual • Self-service• Dedicated • Shared services • Policy-based• Static • Dynamic resource mgmt• Heterogeneous • Standardized • Chargeback appliances • Capacity planning
  17. 17. Server Virtualization and Platform VirtualizationCloud Is NOT Just Server Virtualization Server Virtualization Platform VirtualizationMake one physical resource look like many Make many physical resource look like one Consumers Consumers Single Virtual Platform Multiple Virtual Servers Virtualization Software Clustering GRID Software Single Physical Resource Multiple Physical Resources
  18. 18. Database Consolidation Approaches Three Options Using Oracle Database 11g Infrastructure Cloud Database Cloud DW CRM ERP DW ERP CRM DW ERP CRM DB DB DB DB DB DB DB OS OS OS Oracle VM Oracle VM OS OS OS OS Server Virtualization Database SchemaDeploy in dedicated VMs Share server pool Share database instances Server virtualization Real Application Clusters Real Application Clusters
  19. 19. Middleware Consolidation ApproachesThree Options Using Oracle WebLogic Custom ERP Custom CRM ERP Custom CRM ERP WebLogic WebLogic WebLogic WLS WebLogic Server Server WLS Server VO VO Server Virtualization Guest OS Option Guest OS Hypervisor Hypervisor OS OSServer Virtualization Server Virtualization Platform Virtualization with Guest OS with no Guest OS Shared App ServerDedicated App Servers Dedicated App Servers Shared Pool of Hardware Server virtualization Higher System Utilization
  20. 20. Oracle Private Cloud Applications Cloud Management Oracle Enterprise Manager Custom Apps Oracle Applications ISV Apps Application Performance Mgmt Platform as a Service Process Mgmt: Lifecycle Integration: Security: User Interaction: BPM Suite Management SOA Suite Identity Mgmt WebCenter Application Grid: WebLogic Server, Coherence, JRockit Configuration Exalogic Elastic Cloud Management Database Grid: Oracle Database, Database Options Application Exadata Database Machine Quality Mgmt Infrastructure as a Service Oracle Solaris Operating Systems: Oracle Enterprise Linux Oracle Linux Ops Center Oracle VM for SPARC (LDom) Solaris Containers Oracle VM for x86 Physical & Virtual Servers Systems Mgmt Storage
  21. 21. Oracle Private Cloud Applications Cloud Management Oracle Enterprise Manager Custom Apps Oracle Applications ISV Apps Application Performance Mgmt Platform as a Service Lifecycle Integration: Process Mgmt: Security: User Interaction: Management SOA Suite BPM Suite Identity Mgmt WebCenter Application Grid: WebLogic Server, Coherence, JRockit Configuration Exalogic Elastic Cloud Management Database Grid: Oracle Database, Database Options Application Exadata Database Machine Quality Mgmt Infrastructure as a Service Oracle Solaris Operating Systems: Oracle Enterprise Linux Oracle Linux Ops Center Oracle VM for SPARC (LDom) Solaris Containers Oracle VM for x86 Physical & Virtual Servers Systems Mgmt Storage
  22. 22. Enterprise Systems Trend From Consolidation to Cloud Public Clouds IaaS SaaS PaaS Private Cloud App1 App2 App3 App1 App2 App3 App1 App2 App3 Private PaaS Private PaaS Private IaaS Private IaaS Silo’d Grid Private Cloud• Physical • Virtual • Self-service• Dedicated • Shared services • Policy-based• Static • Dynamic resource mgmt• Heterogeneous • Standardized • Chargeback appliances • Capacity planning
  23. 23. Enterprise Systems Trend From Consolidation to Cloud Public Clouds Hybrid IaaS PaaS IaaS SaaS PaaS SaaS Private Cloud Virtual Private Cloud App1 App2 App3 App1 App2 App3 App1 App2 App3 App1 App2 App3 Private PaaS Private PaaS Private PaaS Private IaaS Private IaaS Private IaaS Silo’d Grid Private Cloud Hybrid• Physical • Virtual • Self-service • Federation with• Dedicated • Shared services • Policy-based public clouds• Static • Dynamic resource mgmt • Interoperability• Heterogeneous • Standardized • Chargeback • Cloud bursting appliances • Capacity planning
  24. 24. Big Data Defined Big Data: Techniques and Technologies that Make Handling Data at Extreme Scale Economical.Brian Hopkins and Boris Evelson, Forrester Research, “Expand Your Digital Horizons with Big Data” (September 2011)
  25. 25. What Makes it Big Data? SOCIAL BLOG 101100101001 001001101010 101011100101 SMART 010100100101 METERVOLUME VELOCITY VARIETY VALUE
  26. 26. Why Is Big Data Important NOW? US HEALTH CARE MANUFACTURING GLOBAL PERSONAL EUROPE PUBLIC US RETAIL LOCATION DATA SECTOR ADMIN Increase industry Decrease dev., Increase service Increase industry Increase net value per year by assembly costs provider revenue by value per year by margin by by $300 B –50% $100 B €250 B 60+%Source: * McKinsey Global Institute: Big Data – The next frontier for innovation, competition and productivity (May 2011)
  27. 27. Divided Solution Spectrum Data VarietyUnstructured Distributed NoSQL File Systems Flexible MapReduce Specialized Dynamic Solutions Developer Transaction Schema (Key-Value) Centric Stores SQL Schema DBMS DBMS Advanced Trusted ETL Analytics Secure (OLTP) (DW) Administered Information Density Acquire Organize Analyze
  28. 28. Bleeding Edge Solution Stack Data VarietyUnstructured HDFS Hadoop Dynamic MapReduce Schema Cassandra NoSQL “R” Flexible Specialized Developer Home Home Centric Schema RDBMS Grown Hive Grown ETL BI Information Density Acquire Organize Analyze
  29. 29. Oracle Engineered Systems Data VarietyUnstructured Dynamic Schema Big Data Analytic Schema Exadata Information Density Acquire Organize Analyze
  30. 30. “if you are serious about software you should build your own hardware ”Alan Kay
  31. 31. Integrated Solution Stack for Big Data InfiniBand InfiniBandACQUIRE ORGANIZE ANALYZE DECIDE
  32. 32. Government Trends• Everything as a Service Model • Database as a Service • Middleware as a Service • Software as a Service • Platform as a Service• Paradigm Shift from Reactive to A Proactive Government • Improve User Interactivity • Content Recommendation / Targeting (Concierge)• Provide a Platform for Collaboration (Agencies, Public & Apps Developers) • Real-time Data Sharing (e.g. Data.gov & Data.gov.sg) • Integration accessibility• Semantic Web & Mashups• Mobilization• Predictive Analytics
  33. 33. Government Trends• Everything as a Service Model • Database as a Service • Middleware as a Service • Software as a Service • Platform as a Service• Paradigm Shift from Reactive to A Proactive Government • Improve User Interactivity • Content Recommendation / Targeting (Concierge)• Provide a Platform for Collaboration (Agencies, Public & Apps Developers) • Real-time Data Sharing (e.g. Data.gov & Data.gov.sg) • Integration accessibility• Semantic Web & Mashups• Mobilization• Predictive Analytics
  34. 34. Predictive Analytics Architecture for Predictive AnalyticsUnstructured Oracle Big Data Web Analytics MachineStructured
  35. 35. Predictive Analytics Architecture for Predictive AnalyticsUnstructured Oracle Big Data Web Analytics Machine Transaction Data Data Feeds Oracle ExadataStructured Customer Machine Data
  36. 36. Predictive Analytics Architecture for Predictive AnalyticsUnstructured Oracle Big Data Web Analytics Machine Transaction Data Data Feeds Oracle ExadataStructured Customer Machine Data
  37. 37. Predictive Analytics Architecture for Predictive AnalyticsUnstructured Oracle Big Data Web Analytics Machine Analytics Tools Transaction Data Data Feeds Oracle ExadataStructured Customer Machine Data
  38. 38. Predictive Analytics Architecture for Predictive AnalyticsUnstructured Portal Oracle Big Data Web Analytics Machine Demographic Analytics sAnalysis Tools Transaction Data Customer Data Feeds Relationship Management Oracle ExadataStructured Customer Machine Data
  39. 39. Predictive AnalyticseGovernment Use Cases• Crisis Impact Analysis • For example, when there is a chemical spill, weather Information are obtained from rain sensors, wind sensors and facebook posts to ascertain the areas which will be impacted.• Flood Control • Make use of real-time data from sensors and facebook posts to predict areas that may experience flooding. Deployment of traffic control, drainage workers to manage situation• Transport Bus Sensors • Sensors are installed on buses and data is collected in real-time for display to commuters. (e.g. Wait Time, No. of passengers) • Based on collected real-time data, bus companies can also deploy more buses to certain routes in response to crowds

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