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Oracle's BigData solutions

Oracle's BigData solutions consist of a number of new products and solutions to support customers looking to gain maximum business value from data sets such as weblogs, social media feeds, smart meters, sensors and other devices that generate massive volumes of data (commonly defined as ‘Big Data’) that isn’t readily accessible in enterprise data warehouses and business intelligence applications today.

Oracle's BigData solutions

  1. 1. Big Data – The New Information Luis Campos Big Data Solutions Director, Oracle EMEA @luigicampos1 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
  2. 2. Big Data – The New Information Challenges and Technology Advances AGENDA - Where’s the new information? - Where could it be? - If in the right place, what could be achieved? - New Technologies and the role of Oracle Corp. - Challenges of the main industries. - The Role of Switzerland in the Big Data space3 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
  3. 3. Where’s the New Information? New Sources New Analytics New Integrations New from Any Data on All Data of Data Orchestrations Any Computing model4 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
  4. 4. What does “New Data” really means? Absorb Any Data, Any Source All Dimensions of Data = 360º5 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
  5. 5. What does “All Data” really means? Stop Throwing Any Data, Data Away Any Source = Know More About What’s Going On in your Business6 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
  6. 6. What does “Any Data” really means? Any Data, Any Source Tap Any Data = New Revenue Streams7 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
  7. 7. Next Step: Reduced It Any Data, Full Range of All Data Any Source Analytics Filtered Cleaned8 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
  8. 8. Oracle Big Data Reference Architecture Source Data Layer Information Access Enterprise Data Warehouse Performance Processes Management Staging Data Layer BI Abstraction & Query Federation COTS/ERP Strongly Typed Foundation Layer Alerts, Data Dashboards, Performance Layer Reporting External Enterprise Data Data with full history Quality Embedded Services Data Marts Social/Text Weakly Typed Data Information Discovery Sensors Knowledge Discovery Layer Advanced Streaming Analysis & Data Mining Sandbox Rapid Dev Sandbox Data ScienceSecurity and Metadata Data Integration 9 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
  9. 9. Translated into Oracle Product Architecture Source Data Layer Information Access Enterprise Data Warehouse Performance Processes Management Staging Data Layer BI Abstraction & Query Federation COTS/ERP Strongly Typed Foundation Layer Data Oracle Oracle BI Dashboards, Alerts, External Database Enterprise Data Performance Layer Reporting Foundation Data -Advanced Analytics & OLAP with full history Quality Embedded - Spatial and Graph Data Marts Endeca Services Social/Text - Industry Models Oracle Weakly Typed Information Information Data Sensors Big Data Discovery Discovery Appliance Endeca Information Knowledge Discovery Layer Advanced Discovery Analysis & Streaming Data Mining Sandbox Rapid Dev Sandbox Data ScienceSecurity and Metadata Data Integration Oracle Big Data Connectors 10 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
  10. 10. Big Data Appliance Hadoop Ecosystem for the Enterprises Oracle Big Data Appliance 18 Nodes 648TB, 288 CPUs 12 Nodes (U)Cloudera Dist. Hadoop 6 Nodes Oracle NoSQL 216TB, 96 CPUs BD Connectors11 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
  11. 11. Oracle’s Big Data Connectors Unlock the power of Hadoop integration Hadoop Oracle Database Oracle Big Data Connectors12 Copyright © 2012, Oracle and/or its affiliates. All rights reserved.
  12. 12. (1) Oracle Data Integrator Application Adapters for Hadoop Transforms Via MapReduce(HIVE) Benefits  Consistent tooling across BI/DW, SOA, Integration and Big Data Oracle Data Integrator Activates  Reduce complexities : graphical tooling Oracle Loads Loader for Hadoop  Improves productivity Oracle Database Improving Productivity and Efficiency for Big Data13 Copyright © 2012, Oracle and/or its affiliates. All rights reserved.
  13. 13. (2) Oracle SQL Connector for Hadoop Accessing HDFS Data from Oracle Database Access or load into theFeatures database in parallel using external table mechanism HDFS Oracle DatabaseAccess and analyze data in SQL Queryplace on HDFSQuery and join data on ODCH ExternalHDFS with database ODCH Table ODCHresident data HDFSLoad into the database Clientusing SQL if requiredAutomatic load balancing tomaximize performance14 Copyright © 2012, Oracle and/or its affiliates. All rights reserved.
  14. 14. (3) Oracle R Connector for Hadoop R Analytics leveraging Hadoop and HDFS Oracle R Client Linearly Scale a Robust Set of R Algorithms MAP MAP MAP MAP Hadoop Leverage MapReduce for R Calculations REDUCE REDUCE Compute Intensive HDFS Parallelism for Simulations15 Copyright © 2012, Oracle and/or its affiliates. All rights reserved.
  15. 15. What is ?• Brings R’s statistical functionality to the Oracle Database• Eliminates R’s memory constraints • Allows R to run on very large data sets• Oracle R is architected for enterprise production infrastructure • Automatically exploits database parallelism without requiring parallel R programming• Oracle R leverages the latest R algorithms and packages • R is an embedded component of the DBMS server• Part of Oracle Advanced Analytics (+ODM)
  16. 16. Oracle R ArchitectureR workspace console Function push-down Oracle statistics engine OBIEE, Web – data transformation & Services statistics Development Production Consumption• Leverages SQL for data prep, analysis and enhanced statistics engine• R engine runs on database nodes for production enablement of R models• Leverages Exadata—Oracle R workloads run in-database and can be bound to database nodes for workload isolation• Enriches OBIEE dashboards with Oracle R statistics and analytics
  17. 17. Oracle Data Mining (ODM) Data mining can answer questions that cannot be addressed through simple query and reporting techniques.• Data Mining: Insight from discovering relationships • Knowledge about what happened in the past • Characterization, segmentation, comparisons, discrimination • Descriptive models of patterns• Predictive Analytics: Making better decisions and forecasts • Knowledge about what is happening right now and in the future • Classification and prediction of patterns • Rule-and-model driven
  18. 18. Data Mining – Some Definitions Supervised Learning Problem Classification Sample ProblemClassification Predict customer response to an affinity card programRegression Predict customer’s ageAttribute Importance Find the most significant predictors, data preparation A1 A2 A3 A4 A5 A6 A7
  19. 19. Data Mining – Some Definitions Unsupervised Learning Problem Classification Sample ProblemAnomaly Identify customer purchasing behavior that isDetection significantly different from the normAssociation Find the items that tend to be purchasedRules together and specify their relationship – market basket analysisClustering Segment demographic data into clusters and rank the probability that an individual will belong to a given clusterFeature Group the attributes into generalExtraction characteristics of the customers F1 F2 F3 F4
  20. 20. Endeca Information Discovery Sandbox and Production mode Endeca Information Discovery Studio Endeca MDEX Server Intergration Suite21 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
  21. 21. Information Discovery on Big Data To Be Released Complements Hadoop Soon Oracle Endeca Information Discovery  Data Variety - structured and unstructured data  Massive scalability  No model required  In-memory analytics  Batch execution  Interactive  Business users Filters Deep Large-Scale Fast Self-service Processing Persists Information Discovery22 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
  22. 22. What is the world doing today Large Spanish Clothes Manufacturer • Automation • Sensory Event Processing • Quality Assurance23 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
  23. 23. What is the world doing today Second Largest Bank in United States of America • Analysis of data xLoB: Loans, Insurance, on-line banking, card products • Market assessment • Risk Analysis • Revenue lift for new & existing products24 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
  24. 24. Telco Industry Deep, Big and Fast Deep • SNA*, Find Influencers, RA** Big • Network Optimization, • CDR Analysis Fast • Sentiment Analysis • Location Based Services • Click stream Analysis© 2012 Oracle Corporation – Proprietary and Confidential * Social Network Analysis (Rate plan optimization) ** Revenue Assurance
  25. 25. Retail Industry Marketing, Merchandising and Supply Chain Marketing • In-store behaviour analysis • Sentiment Analysis + Microsegmentation Merchandising • Assortment optimization Supply Chain • Distribution and logistics optimization • Informing supplier negotiations© 2012 Oracle Corporation – Proprietary and Confidential
  26. 26. Oil and Gas Use Cases Hadoop and Seismic Data Processing27 Copyright © 2012, Oracle and/or its affiliates. All rights reserved.
  27. 27. Life Sciences / Pharmaceutical Life Sciences • DNA Sequencing, Diseases Correlation Pharmaceutical • Clinical Trial – meds simulation© 2012 Oracle Corporation – Proprietary and Confidential
  28. 28. The Role of Switzerland in the Big Data space  Scientific Research  Data Science  Financial Industry  Telco  Public Sector© 2012 Oracle Corporation – Proprietary and Confidential
  29. 29. Danke / Merci / Grazie30 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
  30. 30. 31 Copyright © 2013, Oracle and/or its affiliates. All rights reserved.
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Oracle's BigData solutions consist of a number of new products and solutions to support customers looking to gain maximum business value from data sets such as weblogs, social media feeds, smart meters, sensors and other devices that generate massive volumes of data (commonly defined as ‘Big Data’) that isn’t readily accessible in enterprise data warehouses and business intelligence applications today.

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