Big Data World Forum


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Big Data World Forum (BDWF is specially designed for data-driven decision makers, managers, and data practitioners, who are shaping the future of the big data.

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Big Data World Forum

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  2. 2. Turning Big Data Challenges into Big Opportunities Informatica for Big Data Wei Zheng Director, Product Management2
  3. 3. A Little About Us – Informatica The #1 Independent Leader in Data Integration• Founded: 1993• 2010 Revenue: $650 million $650• 5-year Average Growth Rate: $600 20% per year $550• Employees: 2,125+ $500 $450• Partners: 400+ • Major SI, ISV, OEM and $400 On-Demand Leaders $350• Customers: 4,280+ $300 • 84 of Fortune 100 $250 • 87%+ of Dow Jones $200 • Government Organizations in $150 20 countries 2005 2006 2007 2008 2009 2010 • # 1 in Customer Loyalty Rankings (5 Years in a Row) 3
  4. 4. The Informatica Platform Proven Value: Comprehensive, Unified, Open & EconomicalComprehensive Unified Open Economical Supporting the  Maximizing productivity  Accessing transaction or  Low Total Cost of  complete data  with  self‐service for  interaction data from  Ownership (TCO)  ‐ integration lifecycle business & IT any source including leveraging  Hadoop Adaptive data services  Mitigating risk by  Enabling any data  to  deliver data as a  working with what you  Fast Return on  integration project service from any  have now and in the  Investment (ROI) Delivering at any  projects future   Flexible deployment latency from years to  scaled to your business  microseconds Consistent interfaces  Open to any domain,  needs across all processing  architectural styles platforms  4
  5. 5. Big Data on Executive Agenda MARCH 22, 2011, 11:30 A.M. ET. Report to the President: Every Federal Agency Needs a Big Data Strategy February 4, 2011 How Vendors Are Lowering Big Data Barriers March 26, 2011 A Model for the Big Data Era Data-centric architecture is becoming fashionable again Today’s Leaders Are Racing to Uncover New Value and Opportunities for Competitive Insights and Improved Operations 5
  6. 6. Defining Big Data Definition: Big data is the confluence of the three trends consisting of Big Transaction Data, Big Interaction Data and Big Data Processing BIG TRANSACTION DATA BIG INTERACTION DATA Online Online Analytical Social Other Transaction Processing Media Data Interaction Data Processing (OLAP) & (OLTP) DW Appliances Call detail records, image, click stream data Scientific, genomic BIG DATA INTEGRATION Machine/Device BIG DATA PROCESSING 6
  7. 7. Value of Big Data IntegrationUnleash the full business potential of BigData to empower the data-centricenterprise 7
  8. 8. Informatica 9.1: Harnessing the Power of BigTransaction and Interaction Data Big Data Integration For All Data Authoritative and Trustworthy Data For All Purposes Self Service For All Users Adaptive Data Services For All Projects 8
  9. 9. Big Data Integration 9
  10. 10. Big Data IntegrationGain business value from Big Data Big Data Processing Enabling Solutions Extend Enterprise Near-universal connectivity Environment with Other Interaction data to Big Transaction Data Hadoop •Clickstream, •Scientific/genomic, Hadoop – Web Social Connectivity to Big •Sensor –processing, text mining, media Interaction Data including machine/device, fraud/risk analytics, •mobile, call detail social data image processing, records (CDR) Hadoop - sandbox, •Image files, texts Connectivity to Hadoop staging, archive Large scale processing – OLTP, OLAP Your information Big Interaction DataNew type of DW management appliances environment Big Transaction Data 10
  11. 11. Big Transaction DataMaximize availability and performance of big transaction data Uncover Better Universal new areas Actions & Access for growth & Operations efficiency All data including Reliable, complete Greater confidence OLTP, OLAP and information Continuous DW appliances No data discarded innovation Near-Universal Connectivity to Big Transaction Data Database Warehouse Appliances 11
  12. 12. Big Interaction DataAchieve a complete view with social and interaction data Turn insights on relationships, ? influences and behaviors Into opportunities Connectivity to Big Interaction Data including social data What What will she How influence Databases do with this connected does she Call Detailed Records, merchandise? Image Files, RFIDs is she? have with her Any Informatica MDM family and … Customer Product additional External Data Applications friends? Providers services? 12
  13. 13. Big Data ProcessingConnectivity to Hadoop and Future Integration Predictive Portfolio & Risk Sentiment Fraud Detection Smart Devices Analytics Analysis Analysis Hadoop Cluster Graphical IDE for Hadoop Development Future: Phase 2 Connectivity for •• Codeless & metadata driven Codeless & metadata driven Hadoop (HDFS) development development •• Prepare & integrate data on Hadoop Prepare & integrate data on Hadoop 9.1 HF1 – June 2011 •• Complete push down optimization Complete push down optimization •• Load data to Hadoop from any •• Metadata lineage Metadata lineage Load data to Hadoop from any source source •• Extract data from Hadoop to any Extract data from Hadoop to any Weblogs, Mobile target target Databases, Semi-structured Cloud Applications, Data, Sensor Data Data Warehouses Unstructured Enterprise Applications Social Data 13
  14. 14. Authoritative andTrustworthy Data 14
  15. 15. Multi-Style MDMSingle platform for all architectural styles and data domains Multi-domain Multi-style Customer Master Registry Product Master Analytic Chart of Accounts Co-existence Location Master Universal MDM Transactional … …Multi-deployment Multi-use Hub MDM Data Integration Federated MDM Data Quality MDM in the Cloud Data Services MDM as a Service … … 15
  16. 16. Reusable Data Quality PoliciesA Single Platform For Trusted Data Business/IT Collaboration/Data Governance Role-based, Unified, Process-drivenA Single Platform For Trusted DataOne Platform for Data Integration, Data Quality and MDM Business Data Stewards Architects Developers One One One MDM Data Quality Data Integration Re-usable/Consistent Data Quality Rules 16
  17. 17. Self-Service 17
  18. 18. Self Service Data Integration SQL or Web Service BI Report b We L or e DI Analyst SQ ervic S Batch ETL DI Developer Data WarehouseInformatica’s self-service data integration doubles productivity by eliminatingmanual steps and empowering analysts to do more on their own. Analysts candefine and validate source-to-target specifications in an intuitive browser-basedtool without a data architect or DBA. On top of that, once the analyst creates thesource-to-target specification, the mapping logic is automatically generated for adeveloper to deploy to production.”Sean Hickey, Manager Data Integration, T-Mobile 18
  19. 19. Self ServicePoint-of-Use Data and Context for Business Users SFDC Account with Data Controls Expand Hierarchy Account Hierarchy Data Control 19
  20. 20. Self ServicePre-Built Application Accelerators to Jumpstart Projects Tag content to Develop mappings augment based on business project entities rather than metadata individual tables • Improved analyst & developer productivity and collaboration • Save project time and cut costs Jumpstart mapping 20
  21. 21. Adaptive Data Services 21
  22. 22. Multi-Protocol Data ProvisioningReusable Data Services • Easily reuse DI logic/LDOs for any mode/protocol • Metadata-driven, visual, graphical env (i.e., no-code) • Execution & optimization separate from design-time • No re-development & re- building of LDOs • Reduce duplication of DI development & maintenance 22
  23. 23. Integrated Data Quality Apply Data Quality Rules at Point of Access, Dynamically • Provision data qualityData rules via data services–Quality Integrated Datav9.x.x Quality Read or Write • Use library of templates & data quality rules • Auto generate data quality transformations • In real-time – no pre or post-processing/staging • Enforce data quality rules at point of access 23
  24. 24. Informatica for Big Data Integration Business Imperatives Improve Mergers Increase Deliver Increase Improve Acquire & Outsource Governance Efficiency & Acquisitions Partner Analytical Business Business Retain Non-core Risk Reduce & Network Insight Agility Processes Customers Functions Compliance Costs Divestitures Efficiency Big Data Real-Time Complex Big Data Ultra Big Data Big Data Big Data Social /Big DataWarehousing & Customer Event Collection & messaging Services Archiving Consolidation SynchronizationOperational BI View Processing AggregationDeliver 5x Saved millions Rationalized Unite operations Increased Deliver cloud Turned human Reduce Time 25% savings in application monthly slot access to 177+ to Market byfaster & direct annually by across 200 brands review data center portfolio and revenues by 4% million 90% by On-access to improving over 100+ into automated footprint ($1M+) saved $1 million while expanding businesses Boardingcustomer, risk, trucking countries through alerts reduce latency by with 6 month target customer worldwide and New Dataclaims data in operations and migration of in seconds 83 percent to 340 payback. segments from 53 million Sourcesvariety of empowering business data for maritime microseconds, Reduced age of 40 to 160 across contacts. D&B Faster andsources – DW, business with from five systems security – enabling a 580 data by 87% for 500 sources in 360 app enabling a16 legacy, Hadoop-based to one through percent increase service real-time with updates with wide variety30000 data free-form geospatial and in throughput over monitoring & social and linkedin and of Datamarts, 10M questions using video tracking 1B transactions pattern machine data twitter Formatsclaims via data sensor, mobile per day and identification offeeds at 1/3 of and geospatial growing large scale datathe cost data 24
  25. 25. Business Benefits of Informatica 9.1 forBig Data • Big Data Integration to gain business value from Big Data • Authoritative and Trustworthy Data to increase business insight and consistency by delivering trusted data for all purposes. • Self-Service to empower all users to obtain relevant information while IT remains in control • Adaptive Data Services to deliver relevant data adapted to the business needs of all projects 25
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