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Oracle Data Mining Update and Xerox Application Charlie Berger Sr. Director of Product Management, Life Sciences and Data ...
Agenda <ul><li>Oracle Data Mining Update </li></ul><ul><li>ODM/DM4J Demonstration </li></ul><ul><li>Xerox Application </li...
Oracle Business Intelligence Vision <ul><li>Multiple databases </li></ul><ul><li>Multiple servers </li></ul><ul><li>Multip...
Oracle Business Intelligence Vision <ul><li>Single database </li></ul><ul><li>Single server </li></ul><ul><li>Standard int...
What is Oracle Data Mining? <ul><li>Oracle Data Mining (ODM) sifts through massive amounts of data to  find hidden pattern...
<ul><li>Data mining embedded in  Oracle10 g   Database </li></ul><ul><ul><li>Simplifies process, eliminates data  movement...
Oracle Data Mining Business Intelligence Applications Information Producers Information Consumers <ul><li>Data Miners can…...
Information Consumers Key factors that influence customers likely to purchase a product Customers sorted in likelihood to ...
Oracle11 i  CRM Application CRM / Data Mining Integration <ul><li>Marketing analysts can design targeted campaigns without...
10 g   Oracle Data Mining Wide range of data mining algorithms <ul><li>Feature Selection </li></ul><ul><ul><li>Attribute I...
10 g  Additional Features <ul><li>Text Mining </li></ul><ul><ul><li>Ability to combine structured data  and unstructured d...
Oracle Data Mining/DM4J Demonstration
DM4J 2   New Features <ul><li>Access Data </li></ul><ul><ul><li>Import flat file to db wizard </li></ul></ul><ul><li>Visua...
Oracle Data Mining Enabling Data Mining Applications DM4J GUI add-ins provides wizards for building and evaluating models
Oracle Data Mining Enabling Data Mining Applications Data analysts can build and review data mining models Data analysts c...
Oracle Data Mining Enabling Data Mining Applications <ul><li>Comprehensive GUI for preparing data, building models, evalua...
Oracle Data Mining Enabling Data Mining Applications <ul><li>Automated, scheduled, and event-driven business intelligence ...
Multiple Examples of tumor tissue (public data from Whitehead/MIT) Oracle 10 g SVM Classification of Multiple Tumor Types ...
Oracle 10 g SVM Classification of Multiple Tumor Types 78.25% accuracy  Green=Correct   Red=Errors Oracle Data Mining’s SV...
TDWI <ul><li>“ Andrew Braunberg, a senior analyst with research  firm TDWI suggests that DM4J should  simplify the job of ...
Benefits of Oracle’s Approach <ul><li>Grid, RAC, integrated BI,… </li></ul><ul><li>SQL & PL/SQL available </li></ul><ul><l...
A Q & Q  U  E  S  T  I  O  N  S A  N  S  W  E  R  S
 
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  1. 2. Oracle Data Mining Update and Xerox Application Charlie Berger Sr. Director of Product Management, Life Sciences and Data Mining [email_address] Oracle Corporation Raj Minhas Research Scientist Xerox Corporation [email_address] Session id: 40262
  2. 3. Agenda <ul><li>Oracle Data Mining Update </li></ul><ul><li>ODM/DM4J Demonstration </li></ul><ul><li>Xerox Application </li></ul>
  3. 4. Oracle Business Intelligence Vision <ul><li>Multiple databases </li></ul><ul><li>Multiple servers </li></ul><ul><li>Multiple engines </li></ul><ul><li>Proprietary interfaces </li></ul><ul><li>Complex environment </li></ul><ul><li>Slow conversion of data to information </li></ul>Database Engine Data Integration Engine OLAP Engine Mining Engine Is to change this …
  4. 5. Oracle Business Intelligence Vision <ul><li>Single database </li></ul><ul><li>Single server </li></ul><ul><li>Standard interfaces </li></ul><ul><li>Simplified environment </li></ul><ul><li>Fast conversion of data to information </li></ul>Data Warehousing ETL OLAP Data Mining Oracle 10 g DB Into this …
  5. 6. What is Oracle Data Mining? <ul><li>Oracle Data Mining (ODM) sifts through massive amounts of data to find hidden patterns and information </li></ul><ul><ul><li>— valuable information that can help you better understand your customers and anticipate their behavior </li></ul></ul><ul><li>ODM insights can be revealing, significant, and valuable e.g. </li></ul><ul><ul><li>Predict which customers are likely to churn </li></ul></ul><ul><ul><li>Discover what factors are involved with a certain disease </li></ul></ul><ul><ul><li>Identify fraudulent behavior </li></ul></ul>
  6. 7. <ul><li>Data mining embedded in Oracle10 g Database </li></ul><ul><ul><li>Simplifies process, eliminates data movement, speeds analysis, deployment and delivers security and scalability </li></ul></ul><ul><li>Build models and applications simultaneously </li></ul><ul><ul><li>Build and evaluate models and automatically generate Java code </li></ul></ul><ul><li>Enhance applications with predictions and insights </li></ul><ul><ul><li>For example, build churn prediction applications and enable call centers with greater customer insight </li></ul></ul>Oracle Data Mining Overview & Differentiating Features Data Mining
  7. 8. Oracle Data Mining Business Intelligence Applications Information Producers Information Consumers <ul><li>Data Miners can… </li></ul><ul><ul><li>Discover patterns and insights hidden in the data </li></ul></ul>Oracle Data Mining <ul><li>CEOs can ask… </li></ul><ul><ul><li>How can I target the “right customers” to maximize profits? </li></ul></ul><ul><li>Managers can answer… </li></ul><ul><ul><li>Which customers are likely to be interested in which offers and why? </li></ul></ul><ul><li>Call Reps can… </li></ul><ul><ul><li>Suggest the right “offer” for the customer </li></ul></ul>
  8. 9. Information Consumers Key factors that influence customers likely to purchase a product Customers sorted in likelihood to purchase a product
  9. 10. Oracle11 i CRM Application CRM / Data Mining Integration <ul><li>Marketing analysts can design targeted campaigns without becoming data mining experts </li></ul><ul><ul><li>Build models, score lists </li></ul></ul><ul><ul><li>Discover patters & make predictions </li></ul></ul>Data mining increases effectiveness of targeted campaigns
  10. 11. 10 g Oracle Data Mining Wide range of data mining algorithms <ul><li>Feature Selection </li></ul><ul><ul><li>Attribute Importance </li></ul></ul><ul><li>Supervised learning (classification & prediction) </li></ul><ul><ul><li>Naïve Bayes </li></ul></ul><ul><ul><li>Adaptive Bayes Networks </li></ul></ul><ul><ul><li>Support Vector Machines </li></ul></ul><ul><li>Unsupervised learning (clustering and associations) </li></ul><ul><ul><li>Association Rules </li></ul></ul><ul><ul><li>Orthogonal Clustering </li></ul></ul><ul><ul><li>Enhanced k-means Cluster </li></ul></ul><ul><li>Feature Extraction </li></ul><ul><ul><li>Non Negative Matrix Factorization </li></ul></ul>Data Mining
  11. 12. 10 g Additional Features <ul><li>Text Mining </li></ul><ul><ul><li>Ability to combine structured data and unstructured data </li></ul></ul><ul><li>ODM API </li></ul><ul><ul><li>Java </li></ul></ul><ul><ul><li>PL/SQL </li></ul></ul><ul><li>Scoring engine </li></ul><ul><li>Similarity Searches </li></ul><ul><ul><li>BLAST (Life sciences: genes and proteins) </li></ul></ul>Data Mining
  12. 13. Oracle Data Mining/DM4J Demonstration
  13. 14. DM4J 2 New Features <ul><li>Access Data </li></ul><ul><ul><li>Import flat file to db wizard </li></ul></ul><ul><li>Visualize Data </li></ul><ul><ul><li>Data snapshot </li></ul></ul><ul><ul><li>Standard summary statistics </li></ul></ul><ul><ul><li>Attribute level histograms </li></ul></ul><ul><li>Transform Data </li></ul><ul><ul><li>Create View / Table </li></ul></ul><ul><ul><li>Random and Stratified sampling </li></ul></ul><ul><ul><li>Aggregation </li></ul></ul><ul><ul><li>Computed column </li></ul></ul><ul><ul><li>Normalization </li></ul></ul><ul><ul><li>Discretization </li></ul></ul><ul><ul><li>Table Splits </li></ul></ul><ul><ul><li>Filtering </li></ul></ul><ul><ul><li>Recode </li></ul></ul><ul><li>Modeling </li></ul><ul><ul><li>Building models </li></ul></ul><ul><ul><li>Testing models </li></ul></ul><ul><ul><li>Applying (scoring) models </li></ul></ul><ul><ul><li>Visualize results </li></ul></ul><ul><li>Deploy Models/Results </li></ul><ul><ul><li>Generate transformation code (PL/SQL) </li></ul></ul><ul><ul><li>View and generate transformation lineage </li></ul></ul><ul><ul><li>Generate model code (Java) </li></ul></ul><ul><ul><li>Integrate with Oracle tools </li></ul></ul><ul><ul><ul><li>JDeveloper </li></ul></ul></ul><ul><ul><ul><li>Oracle Warehouse Builder </li></ul></ul></ul><ul><ul><ul><li>Discoverer </li></ul></ul></ul>
  14. 15. Oracle Data Mining Enabling Data Mining Applications DM4J GUI add-ins provides wizards for building and evaluating models
  15. 16. Oracle Data Mining Enabling Data Mining Applications Data analysts can build and review data mining models Data analysts can build and review data mining models
  16. 17. Oracle Data Mining Enabling Data Mining Applications <ul><li>Comprehensive GUI for preparing data, building models, evaluating results and deploying models </li></ul>DM4J provides features to transform and prepare the data
  17. 18. Oracle Data Mining Enabling Data Mining Applications <ul><li>Automated, scheduled, and event-driven business intelligence applications can can be easily integrated into enterprise applications </li></ul>DM4J automatically generates the Java code
  18. 19. Multiple Examples of tumor tissue (public data from Whitehead/MIT) Oracle 10 g SVM Classification of Multiple Tumor Types DNA Microarray Data Oracle Data Mining 78.25% accuracy Green=Correct Red=Errors We feed multiple cancer types data into the Oracle DB: 16,063 genes, 144 cancer patients and 10 samples per class. We mine the data using Support Vector Machines and create the confusion matrix
  19. 20. Oracle 10 g SVM Classification of Multiple Tumor Types 78.25% accuracy Green=Correct Red=Errors Oracle Data Mining’s SVM models are able to accurately predict the multi-class tumor problem with 78.25% accuracy.               
  20. 21. TDWI <ul><li>“ Andrew Braunberg, a senior analyst with research firm TDWI suggests that DM4J should simplify the job of data analysts . Before Oracle released DM4J, Braunberg notes, analysts who used ODM had to write out all of the Java code that was required to build their predictive models. “This was a time-consuming process that slowed model development and deployment.” </li></ul><ul><li>With DM4J, Braunberg notes, Java code is automatically written as data analysts build their predictive models. Moreover, developers or data analysts can re-use this code in other Java-based applications. As a result, he anticipates, DM4J will “enhance analysts’ ability to create predictive models using Oracle Data Mining.”” </li></ul><ul><li>TDWI Brief: Oracle Data Mining gets GUI; IBM and Cognos' BI partnership April 9, 2003 http://www.dw-institute.com/research/display.asp?id=6632 </li></ul><ul><li>By Stephen Swoyer </li></ul>
  21. 22. Benefits of Oracle’s Approach <ul><li>Grid, RAC, integrated BI,… </li></ul><ul><li>SQL & PL/SQL available </li></ul><ul><li>Leverage existing skills </li></ul>Built on Oracle Technology <ul><li>Applications may be developed and deployed </li></ul>Runs on multiple platforms <ul><li>Supports most data mining problems </li></ul>Wide range of data mining algorithms <ul><li>Eliminates data movement and security exposure </li></ul><ul><li>Fastest: Data  Information </li></ul>Data Mining algorithms embedded in database Benefit Oracle Data Mining Feature
  22. 23. A Q & Q U E S T I O N S A N S W E R S

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