Predictive Analytics: A New Wealth of Options
 

Predictive Analytics: A New Wealth of Options

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The Briefing Room with Gregory Piatetsky and Sybase, an SAP Company ...

The Briefing Room with Gregory Piatetsky and Sybase, an SAP Company
Slides from the Live Webcast on Apr. 17, 2012

Predicting the future happens all the time these days, in all kinds of business situations. And now, there are more options than ever for leveraging the power of predictive analytics. That's partly due to the rise of open-source projects like Hadoop and partly because of the maturation of traditional analytical platforms. The bottom line is that predictive power is now at the fingertips of a much broader audience.

Register for this episode of The Briefing Room to hear KDnuggets purveyor Gregory Piatetsky explain why data mining and predictive analytics are experiencing a renaissance. He'll be briefed by Joydeep Das of Sybase, an SAP Company, who will outline how Sybase IQ facilitates three approaches: the traditional "pull" model used by SAS, SPSS and other analytic workbenches; a newer "push" model where much of the heavy lifting takes place in the database; and a very novel hybrid "push-pull" model that leverages Hadoop.

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Predictive Analytics: A New Wealth of Options Presentation Transcript

  • 1. PREDICTIVE ANALYTICS WITH SAP SYBASE IQJOYDEEP DASPRODUCT MANAGEMENTAPRIL 17, 2012 CON FIDE N TIAL
  • 2. BUZZ IN THE INDUSTRY - I Unleashes Business Value New Strategies & Business Models Business Value* Operational Revenue Efficiencies Growth©  2012 SAP AG. All rights reserved. 2
  • 3. BUZZ IN THE INDUSTRY - II New Demands, New Opportunities Mining New Sources of Data •  Large volumes of data beyond structured •  Text, social, clickstream, geospatial •  Interactive, on-the-fly analysis •  New methodologies •  e.g. social network analysis Proliferation •  Increased usage by non-technical business users •  Embedded in applications •  e.g. recommendation engines in CRM •  Platform has to be accessible and support more users!©  2012 SAP AG. All rights reserved. 3
  • 4. SAP Sybase IQ A Powerful Platform For Predictive Analytics – Sample Case Study #1 Sybase  IQ  significantly  enhanced  AOK  Hessen’s  ability  to  handle  complex  business   predic0ons  involving  mul0-­‐dimensional  analysis  of  many  input  variables.   AOK  Hessen,  a  large  health  insurance  company,  searches  for  pa+erns  across  all  exis8ng  informa8on  –   medical  treatment,  prescrip8on,  insurance  benefits  –  simultaneously.   “The  divisions  currently  using  the  tool  run  a  significantly  greater  number  of  analyses  than  ever  before.   They  keep  discovering  new  ways  of  drilling  down  into  data  while  working  with  the  soCware.”     -­‐  Michael  Shimmelpfennig,  Service  Manager,  IT-­‐Business  Department©  2012 SAP AG. All rights reserved. 4
  • 5. SAP Sybase IQ A Powerful Platform For Predictive Analytics – Sample Case Study #2 Sybase  IQ  enables  Playphone  to  gain  significant  compe00ve  advantage  through  new   capabili>es  in  customer  targe0ng,  opera0onal  efficiency  and  fraud  detec0on.     Playphone,  a  leading  global  mobile  entertainment  and  media  company,  enables  customer  analy8cs  for   large  scale  marke;ng  campaigns  using  advanced  predic8ve  models  on  Sybase  IQ  -­‐  crunching  through   customer  behavior,  purchasing  history,  and  many  other  relevant  metrics.     “Sybase  IQ  is  a  brilliant  analy;cs  engine.  I  don’t  know  that  the  business  would  s8ll  be  here  today   without  our  Sybase  solu8ons.”     -­‐  Simon  Rose,  Director  Of  Infrastructure  ©  2012 SAP AG. All rights reserved. 5
  • 6. SAP Sybase IQ Our Objective Big Data Model Diversity Complex Alternatives Deal  With  It     Find buried signal in time! Or, get buried in Data!©  2012 SAP AG. All rights reserved. 6
  • 7. SAP Sybase IQ PlexQ Technology: Versatile With Multiple Options For Predictive Analytics Method I Method II Method III Pull Out Push Down Federated Push - Pull KXEN   IBM   SPSS     Panopticon   SAS   R   BI/DM Tools BI Tools Accelerated Access Drivers Hadoop   Data Mining Tools   Embedded libraries R   Fuzzy Logix   Visual Numerics   Full  Mesh  High  Speed  Interconnect©  2012 SAP AG. All rights reserved. 7
  • 8. SAP Sybase IQ Method I: Traditional Pull To Client Method I Pull Out IBM   Standard Drivers   Optimized Drivers   SPSS     SAS   R     Pervasive Method   Myriad Tools Accelerated Access Drivers   Available Skillset Data Mining Tools   Full  Mesh  High  Speed  Interconnect©  2012 SAP AG. All rights reserved. 8
  • 9. SAP Sybase IQ Overcoming Method I: Avoid Pull        Fetch  data  from  database   Compromise   on  at  least   Accuracy   one  key  area   Create  datasets  for  analy>cal   Time  consuming  process   packages   !   Could  run  into  memory  constraints  with  large  data  sets   Analyze  data  using  sta>s>cal  func>ons   Processing   Proprietary  plaMorms  make  it  very  difficult  to  embed   Time   on  proprietary  plaMorms   !   in  applica8ons   Data     Store  results  from  datasets  back  into   database   Volume   Another  8me  consuming  process  which  could  slow   !   down  the  delivery  of  results  to  end-­‐users                                          Generate  reports   Database Server Logic/Filtering Applied Outside Database Server Visualization Logic/Filtering Applied Inside Database Server Visualization©  2012 SAP AG. All rights reserved. 9
  • 10. SAP Sybase IQ Push down (Method II): Solution #1 with KXEN Factory Analysis Models per month Craftsman Analysis Fully automated modeling process •  Regression •  Classification •  Segmentation 200 200 2010 2015 •  Time series forecasting 0 5 •  Association rules Identify key variables KXEN   Generate Sybase IQ specific SQL code Executive and operational reports In-database Push down Easy to Use  Time to Market  More Models©  2012 SAP AG. All rights reserved. 10
  • 11. SAP Sybase IQ Push down (Method II): Solution #2 with Fuzzy Logix Fuzzy Logix Libraries Executed Inside Sybase IQ Visualization Application Algorithms Direct  Marke0ng:  Op>mize  the  performance  of   K-­‐  Means,  Correla>on,  PorKolio  Op>miza>on,   Internet  Marke>ng  Customer  Reten>on   PCA,  Logis>c  Regression   Marke0ng  Services:  Accelerate  the  speed  of   Sparse  Matrix  Calcula>ons,  Correla>on,   model  development  for  their  clients   Euclidean  Distance     Health  Insurance:  Risk  Management  and  Client   Sparse  Matrix  Calcula>ons,  Correla>on,   Management  Teams  -­‐  Scoring  models  to  assess   Euclidean  Distance     the  quality  and  efficiency  of  care     Banking:  Risk  Management   Correla>on,  Simula>on,  Regression,  Cubic   Spline,  Matrix  Opera>ons  ©  2012 SAP AG. All rights reserved. 11
  • 12. SAP Sybase IQ Push down (Method II): Solution #3 with Zementis Express  Complex  Computa0ons  In  Industry  Standard  Predic0ve  Modeling   Markup  Language  (PMML),  Plug  In  Models  Close  To  data  for  execu0on   Sybase  IQ   Server   Database   SQL   Applica>ons   Bridge   Predic>ons   Universal  Plug-­‐In     PMML UDFs   PMML   PMML   PMML   (models)   Zemen>s  PMML  Preprocessor   (models)   (models)   (convert  &  validate)  ©  2012 SAP AG. All rights reserved. 12
  • 13. SAP Sybase IQ Push down (Method II): Solution #3 with Zementis (contd) Delivers a wide range of model types for high performance scoring, including: •  Decision Trees for classification and regression •  Neural Network Models: Back-Propagation, Radial-Basis Function, and Neural-Gas •  Support Vector Machines for regression, binary and multi-class classification •  Linear and Logistic Regression (binary and multinomial) •  Naïve Bayes Classifiers •  General and Generalized Linear Models •  Cox Regression Models •  Rule Set Models (flat decision trees) •  Clustering Models: Distribution-Based, Center-Based, and 2-Step Clustering •  Scorecards (point allocation for categorical, continuous and complex attributes) •  Association Rules •  Also implements data dictionary, missing / invalid values handling and data pre-processing Handles most SAS models publishable in PMML from SAS Enterprise Miner©  2012 SAP AG. All rights reserved. 13
  • 14. SAP Sybase IQ Push down (Method III): Solution #1 Federated Push-Pull With “R” SQL  Queries     C++  UDF     “R”  Server   PUSH-­‐PULL  FEDERATION:   -­‐  UDF  Bridge  Between  Sybase  IQ  and  “R”  server   -­‐  Fire  SQL  against  Sybase  IQ  that  pushes  “R”  models  embedded  in  UDFs  to  “R”  server  for   execu>on   -­‐  UDFs  pulls  results  back  for  combining  with  rest  of  SQL  query  results  in  Sybase  IQ   -­‐  Supports  most  “R”  models  ©  2012 SAP AG. All rights reserved. 14
  • 15. SAP Sybase IQ Push down (Method III): Solution #2 Client Side Push-Pull •  Ideal for bringing together predictive analytics computations from different domains QUEST Toad for Cloud Databases •  Better performance when computation from each domain is pushed down to $ each branch and then pulled together Hadoop Sybase IQ Hive MR Job Results Predictive Analytics Job Results©  2012 SAP AG. All rights reserved. 15
  • 16. SAP Sybase IQ Push down (Method III): Solution #3 Data Federation Push-Pull •  Ideal for combining subsets of HDFS data with Sybase IQ data for operational analytics •  HDFS data not implicitly stored in Sybase IQ: Fetched into Sybase IQ In-memory tables on the fly as part of query fired at Sybase IQ Hadoop Distributed UDF Bridge File System Predictive Queries©  2012 SAP AG. All rights reserved. 16
  • 17. SAP Sybase IQ Push down (Method III): Solution #4 Query Federation Push-Pull •  Ideal for combining subsets of Hadoop MapReduce job results with Sybase IQ data for operational analytics •  Hadoop MapReduce results not implicitly stored in Sybase IQ: Fetched into Sybase IQ In-memory tables on the fly as part of query Hadoop fired at Sybase IQ MapReduce UDF Bridge Jobs Predictive Queries©  2012 SAP AG. All rights reserved. 17
  • 18. SAP Sybase IQ Push down (Method III): Solution #5 Federated Push-Pull Text Analytics FourSquare   Twitter Amazon   Facebook Kapow  So[ware   BLOB Web Text Index Service (ISYS) SAP BusinessObjects Sybase IQ Data Files Data Services iSYS-­‐Search   Document   Filters   1. Limit Textual Corpus 2. Extract Concepts/Entity Relationships 3. Mine Resulting Schemas©  2012 SAP AG. All rights reserved. 18
  • 19. SAP Sybase IQ A Versatile Platform For Predictive Analytics Data  Discovery   Applica>on  Modeling   Reports/Dashboards     Business  Decisions   (Data  Scien0sts)   (Business  Analysts)   (BI  Programmers)   (Business  End  Users)   Full  Mesh  High  Speed  Interconnect Infrastructure   Management   (DBAs)  ©  2012 SAP AG. All rights reserved. 19
  • 20. SAP Sybase IQ Summary – transform your business •  Predictive Analytics going mainstream •  Many options available •  SAP Sybase IQ has a broad and comprehensive support THANK YOU! Joydeep.Das@sap.com©  2012 SAP AG. All rights reserved. 20
  • 21. © 2012 SAP AG. All rights reserved.No part of this publication may be reproduced or transmitted in any form or for any SAP, R/3, SAP NetWeaver, Duet, PartnerEdge, ByDesign, SAP BusinessObjectspurpose without the express permission of SAP AG. The information contained Explorer, StreamWork, SAP HANA, and other SAP products and servicesherein may be changed without prior notice. mentioned herein as well as their respective logos are trademarks or registered trademarks of SAP AG in Germany and other countries.Some software products marketed by SAP AG and its distributors containproprietary software components of other software vendors. Business Objects and the Business Objects logo, BusinessObjects, Crystal Reports, Crystal Decisions, Web Intelligence, Xcelsius, and other BusinessMicrosoft, Windows, Excel, Outlook, and PowerPoint are registered trademarks of Objects products and services mentioned herein as well as their respective logosMicrosoft Corporation. are trademarks or registered trademarks of Business Objects Software Ltd. Business Objects is anIBM, DB2, DB2 Universal Database, System i, System i5, System p, System p5,System x, System z, System z10, System z9, z10, z9, iSeries, pSeries, xSeries, SAP company.zSeries, eServer, z/VM, z/OS, i5/OS, S/390, OS/390, OS/400, AS/400, S/390 Sybase and Adaptive Server, iAnywhere, Sybase 365, SQL Anywhere, and otherParallel Enterprise Server, PowerVM, Power Architecture, POWER6+, POWER6, Sybase products and services mentioned herein as well as their respective logosPOWER5+, POWER5, POWER, OpenPower, PowerPC, BatchPipes, are trademarks or registered trademarks of Sybase, Inc. Sybase is an SAPBladeCenter, System Storage, GPFS, HACMP, RETAIN, DB2 Connect, RACF, company.Redbooks, OS/2, Parallel Sysplex, MVS/ESA, AIX, Intelligent Miner, WebSphere,Netfinity, Tivoli and Informix are trademarks or registered trademarks of IBM All other product and service names mentioned are the trademarks of theirCorporation. respective companies. Data contained in this document serves informational purposes only. National product specifications may vary.Linux is the registered trademark of Linus Torvalds in the U.S. and other countries. The information in this document is proprietary to SAP. No part of this documentAdobe, the Adobe logo, Acrobat, PostScript, and Reader are either trademarks or may be reproduced, copied, or transmitted in any form or for any purpose withoutregistered trademarks of Adobe Systems Incorporated in the United States and/or the express prior written permission of SAP AG.other countries.Oracle and Java are registered trademarks of Oracle.UNIX, X/Open, OSF/1, and Motif are registered trademarks of the Open Group.Citrix, ICA, Program Neighborhood, MetaFrame, WinFrame, VideoFrame, andMultiWin are trademarks or registered trademarks of Citrix Systems, Inc.HTML, XML, XHTML and W3C are trademarks or registered trademarks of W3C®,World Wide Web Consortium, Massachusetts Institute of Technology. ©  2012 SAP AG. All rights reserved. 21