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Oracle’s Advanced AnalyticsMaking Big Data Analytics SimpleCharlie Berger, MS Engineering, MBASr. Director Product Management, Data Mining and Advanced Analyticscharlie.berger@oracle.com www.twitter.com/CharlieDataMineCopyright 2016 Oracle and/or its affiliates. All rights reserved.

Safe Harbor StatementThe following is intended to outline our general product direction. It is intended forinformation purposes only, and may not be incorporated into any contract. It is not acommitment to deliver any material, code, or functionality, and should not be relied uponin making purchasing decisions. The development, release, and timing of any features orfunctionality described for Oracle’s products remains at the sole discretion of Oracle.Copyright 2016 Oracle and/or its affiliates. All rights reserved.2

Predictive Analytics 101 Data, data everywhere – explosive growth Growth of data exponentially greater thangrowth of data analysts!Machine Learning/Data Analysisplatforms requirements: Be extremely powerful andhandle large data volumes Be easy to learn Be highly automated & conomist-data-data-everywhere.pdfCopyright 2016 Oracle and/or its affiliates. All rights reserved.

Machine Learning/Analytics Data Warehouse Hadoop Platform Sprawl– More Duplicated Data– More Data Movement Latency– More Security challenges– More Duplicated Storage– More Duplicated Backups– More Duplicated Systems– More Space and PowerCopyright 2014 Oracle and/or its affiliates. All rights reserved.

Vision Big Data Machine Learning/Analytics Platform for the Era of BigData and Cloud–Make Big Data ML/Analytics Model Discovery Simple Any data size, on any computer infrastructure—on-premise and/or cloud Any variety of data (structured, unstructured, transactional, geospatial), in anycombination–Make Big Data ML/Analytics Model Deployment Simple As a service, as a platform, as an application On-premise and/or cloudCopyright 2016 Oracle and/or its affiliates. All rights reserved.Oracle Cloud Advanced AnalyticsOracle Database12c5

What is Machine Learning, Data Mining & PredictiveAnalytics?Automatically sifting through large amounts of data tocreate models that find previously hidden patterns,discover valuable new insights and make predictions Identify most important factor (Attribute Importance) Predict customer behavior (Classification) Predict or estimate a value (Regression) Find profiles of targeted people or items (Decision Trees) Segment a population (Clustering) Find fraudulent or “rare events” (Anomaly Detection) Determine co-occurring items in a “baskets” (Associations)Copyright 2014 Oracle and/or its affiliates. All rights reserved. A1 A2 A3 A4 A5 A6 A7

Machine Learning, Predictive Analytics & Data MiningTypical Use Cases Targeting the right customer with the right offer How is a customer likely to respond to an offer? Finding the most profitable growth opportunities Finding and preventing customer churn Maximizing cross-business impact Security and suspicious activity detection Understanding sentiments in customer conversations Reducing medical errors & improving quality of health Understanding influencers in social networksCopyright 2014 Oracle and/or its affiliates. All rights reserved.

Oracle’s Advanced AnalyticsFastest Way to Deliver Scalable Enterprise-wide Predictive AnalyticsKey Features Parallel, scalable data mining algorithmsand R integration In-Database Hadoop—Don’t move thedata Data analysts, data scientists &developers Drag and drop workflow, R and SQL APIs Extends data management into powerfuladvanced/predictive analytics platform Enables enterprise predictive analyticsdeployment applicationsCopyright 2016 Oracle and/or its affiliates. All rights reserved.

Oracle’s Advanced AnalyticsFastest Way to Deliver Scalable Enterprise-wide Predictive AnalyticsKey Features Parallel, scalable data mining algorithmsand R integration In-Database Hadoop—Don’t move thedata Data analysts, data scientists &developers Drag and drop workflow, R and SQL APIs Extends data management into powerfuladvanced/predictive analytics platform Enables enterprise predictive analyticsdeployment applicationsDon’t move data; Data is LARGEMove the algorithms insteadCopyright 2016 Oracle and/or its affiliates. All rights reserved.

Oracle Advanced Analytics Database EvolutionAnalytical SQL in the Database New algorithms (EM,PCA, SVD) Predictive Queries SQLDEV/Oracle DataMiner 4.0 SQL script ODM 11g & 11gR2 addsgeneration and SQLAutoDataPrep (ADP), text Query node (R integration)mining, perf. improvements OAA/ORE 1.3 1.4 SQLDEV/Oracle Data Miner adds NN, Stepwise, Oracle Data Mining3.2 “work flow” GUIscalable R algorithms10gR2 SQL - 7 newlaunched Oracle Adv. AnalyticsSQL dm algorithms Integration with “R” and for Hadoop Connector Oracle Data Mining and new Oracle Data introduction/addition oflaunched with Oracle acquiresMiner“Classic”9.2i launched – 2Oracle R Enterprisescalable BDAThinking Machinewizards driven GUIalgorithms (NB Product renamed “Oracle algorithmsCorp’s dev. team and AR) via Java SQL statistical 7 Data Mining “Darwin” dataAdvanced Analytics (ODM functionsintroducedAPI“Partners”ORE)mining software199819992002200420052008Copyright 2016 Oracle and/or its affiliates. All rights reserved.20112014

Oracle’s Advanced AnalyticsFastest Way to Deliver Scalable Enterprise-wide ML/Predictive AnalyticsTraditional AnalyticsMajor Benefits Data remains in Database & Hadoop Model building and scoring occur in-database Use R packages with data-parallel invocations Leverage investment in Oracle IT Eliminate data duplication Eliminate separate analytical servers Deliver enterprise-wide applicationsOracle Advanced AnalyticsData ImportData MiningModel “Scoring”Data Prep. &TransformationavingsData MiningModel BuildingData Prep &Transformation GUI for ML/Predictive Analytics & code gen R interface leverages database as HPC engineData ExtractionModel “Scoring”Embedded Data PrepModel BuildingData PreparationHours, Days or WeeksCopyright 2016 Oracle and/or its affiliates. All rights reserved.Secs, Mins or Hours

Oracle’s Advanced Analytics (Machine Learning Platform)Multiple interfaces across platforms — SQL, R, GUI, Dashboards, AppsInformation ProducersUsersR programmersR ClientInformation ConsumersData & Business Analysts Business Analysts/MgrsSQL Developer/Oracle Data MinerOBIEEDomain End istributedalgorithmsOracle Database Enterprise EditionOracle Advanced Analytics - Database OptionSQL Data Mining, ML & Analytic Functions R Integrationfor Scalable, Distributed, Parallel in-Database ML ExecutionOracle CloudCopyright 2016 Oracle and/or its affiliates. All rights reserved.Oracle Database12c

Oracle Advanced Analytics Database OptionWide Range of In-Database Data Mining and Statistical Functions Data Understanding & Visualization––––––Summary & Descriptive StatisticsHistograms, scatter plots, box plots, bar chartsR graphics: 3-D plots, link plots, special R graph typesCross tabulationsTests for Correlations (t-test, Pearson’s, ANOVA)Selected Base SAS equivalents Data Selection, Preparation and Transformations–––––––Joins, Tables, Views, Data Selection, Data Filter, SQL time windows, Multiple schemasSampling techniquesRe-coding, Missing valuesAggregationsSpatial dataSQL PatternsR to SQL transparency and push down Classification Models–––––Logistic Regression (GLM)Naive BayesDecision TreesSupport Vector Machines (SVM)Neural Networks (NNs) Regression Models–– ––– –––* included free in every Oracle DatabaseAttribute Importance (Minimum Description Length)Principal Components Analysis (PCA)Non-negative Matrix FactorizationSingular Vector DecompositionText Mining– A Priori algorithmFeature Selection and Reduction– Special case Support Vector Machine (1-Class SVM)Associations / Market Basket Analysis– Hierarchical K-meansOrthogonal PartitioningExpectation MaximizationAnomaly Detection–Most OAA algorithms support unstructured data (i.e. customer comments,email, abstracts, etc.)Transactional & Spatial Data– Multiple Regression (GLM)Support Vector MachinesClusteringAll OAA algorithms support transactional data (i.e. purchase transactions,repeated measures over time, distances from location, time spent in area A,B, C, etc.)R packages—ability to run open source–Broad range of R CRAN packages can be run as part of database process via Rto SQL transparency and/or via Embedded R modeCopyright 2016 Oracle and/or its affiliates. All rights reserved.

You Can Think of Oracle Advanced Analytics Like This Traditional SQLSQL Statistical Functions - SQL &– “Human-driven” queries– Domain expertise– Any “rules” must be defined andmanagedSQL Queries– SELECT– DISTINCT– Automated knowledge discovery, modelbuilding and deployment– Domain expertise to assemble the “right”data to mine/analyze Statistical SQL “Verbs”– MEAN, STDEV– MEDIAN– AGGREGATE– SUMMARY– WHERE– CORRELATE– AND OR– FIT– GROUP BY– COMPARE– ORDER BY– ANOVA– RANKCopyright 2014 Oracle and/or its affiliates. All rights reserved. FREE!

In-Database Statistical Functions (SQL)Independent Samples T-Test A/B offer testing– Query compares the mean of AMOUNT SOLDbetweenMEN and WOMEN Grouped ByCUST INCOME LEVEL ranges– Returns observed t value and its related twosided significance ( .05 significant)SELECT substr(cust income level,1,22) income level,avg(decode(cust gender,'M',amount sold,null)) sold to men,avg(decode(cust gender,'F',amount sold,null)) sold to women,stats t test indep(cust gender, amount sold, 'STATISTIC','F')t observed,stats t test indep(cust gender, amount sold) two sided p valueFROM sh.customers c, sh.sales sWHERE c.cust id s.cust idGROUP BY rollup(cust income level)ORDER BY 1;Copyright 2014 Oracle and/or its affiliates. All rights reserved.

Correlation Functions The CORR S and CORR K functions supportnonparametric or rank correlation (findingcorrelations between expressions that areordinal scaled). Correlation coefficients take on a value rangingfrom –1 to 1, where:– 1 indicates a perfect relationship– –1 indicates a perfect inverse relationship– 0 indicates no relationshipselect CORR S(AGE, WEIGHT)coefficient,CORR S(AGE, WEIGHT,'TWO SIDED SIG')p value, substr(TREATMENT PLAN,1,15) as TREATMENT PLANfrom DMUSER.LYMPHOMAGROUP BY TREATMENT PLAN; The following query determines whether thereis a correlation between the AGE and WEIGHT ofpeople, using Spearman's correlation:Copyright 2016 Oracle and/or its affiliates. All rights reserved.

You Can Think of Oracle’s Advanced Analytics Like This Traditional SQLOracle Advanced Analytics - SQL &– “Human-driven” queries– Domain expertise– Any “rules” must be defined andmanagedSQL Queries– SELECT– DISTINCT– Automated knowledge discovery, modelbuilding and deployment– Domain expertise to assemble the “right”data to mine/analyze Analytical SQL “Verbs”– PREDICT– DETECT– AGGREGATE– CLUSTER– WHERE– CLASSIFY– AND OR– REGRESS– GROUP BY– PROFILE– ORDER BY– IDENTIFY FACTORS– RANK– ASSOCIATECopyright 2016 Oracle and/or its affiliates. All rights reserved.

Oracle Advanced Analytics Database OptionIn-Database ML/Data Mining Algorithms*—SQL &Classification Decision Tree Logistic Regression (GLM) Naïve Bayes Support Vector Machine (SVM) Random Forest& GUI AccessClusteringOracle Cloud Advanced AnalyticsOracle Database12cPredictive Queries Hierarchical k-Means Clustering Orthogonal Partitioning Clustering Regression Expectation-Maximization Anomaly Detection Feature ExtractionAttribute ImportanceFeature Extraction & Creation Minimum Description Length Nonnegative Matrix Factorization Unsupervised pair-wise KL div. Principal Component AnalysisA1 A2 A3 A4 A5A6 A7Regression Multiple Regression (GLM) Support Vector Machine (SVM) Linear Model Generalized Linear Model Multi-Layer Neural Networks Stepwise Linear RegressionAnomaly Detection 1 Class Support Vector MachineTime Series Single & Double Exp. Smoothing Singular Value DecompositionMarket Basket Analysis Apriori – Association RulesOpen Source R Algorithms Ability to run any R package viaEmbedded R mode* supports partitioned models, text miningCopyright 2016 Oracle and/or its affiliates. All rights reserved.

Oracle Advanced AnalyticsHow Oracle R Enterprise Compute Engines WorkOracle Database 12cOther RpackagesR- SQLOracle R Enterprise (ORE) packagesResults1R- SQL Transparency “Push-Down” R language for interaction with the database R-SQL Transparency Framework overloads Rfunctions for scalable in-database execution Function overload for data selection,manipulation and transforms Interactive display of graphical results andflow control as in standard R Submit user-defined R functions forexecution at database server under controlof Oracle Database2RResultsR EngineOracle R Enterprise packages3In-Database Adv Analytical SQL Functions 15 Powerful data mining algorithms(regression, clustering, AR, DT, etc. Run Oracle Data Mining SQL data miningfunctioning (ORE.odmSVM, ORE.odmDT, etc.) Speak “R” but executes as proprietary indatabase SQL functions—machine learningalgorithms and statistical functions Leverage database strengths: SQL parallelism,scale to large datasets, security Access big data in Database and Hadoop viaSQL, R, and Big Data SQLOther RpackagesEmbedded R Package Callouts R Engine(s) spawned by Oracle DB fordatabase-managed parallelism ore.groupApply high performance scoring Efficient data transfer to spawned Rengines Emulate map-reduce style algorithms andapplications Enables production deployment andautomated execution of R scriptsCopyright 2016 Oracle and/or its affiliates. All rights reserved.

Structured and Unstructured Data GrowthIDC Study: Structured Versus Unstructured Data: The Balance of Power Continues to Shift“80% of business-relevantinformation originates inunstructured form, primarily text.”Structured Versus Unstructured Data: The Balance of Power Continues to ShiftCopyright 2016 Oracle and/or its affiliates. All rights ured-and-unstructured-data-what-is-it/22

Unstructured DataOpportunity for Better Insights and Better Actionable Analytics Missing from most predictive models– Customer comments– Emails– Customer Service Rep notes– Pdfs, Ppts, Word documents, etc.– Tweets– Physician and Nurse notes– Article abstracts– Explanations– Free form written information that describesmore about a situation e.g. a customer’sinterest in “discount” and “sale” items, etc.than structured data possibly can. Absolutely! Youbet unstructureddata can a-challenge-or-asset/Copyright 2016 Oracle and/or its affiliates. All rights reserved.23

Oracle TextNative Capability of every Oracle Database Oracle Text uses standard SQL to index, search, and analyze text anddocuments stored in the Oracle database, in files, and on the web. Oracle Text supports multiple languages and uses advanced relevanceranking technology to improve search quality. Oracle Advanced Analytics uses Oracle Text to pre-process (“tokenize”)unstructured data for the OAA SQL data mining functionsCopyright 2016 Oracle and/or its affiliates. All rights reserved.

Rapidly Build, Evaluate & Deploy Analytical MethodologiesLeveraging a Variety of Data Sources and TypesTransactionalPOS dataSQL Joins and arbitrary SQLtransforms & queries – power of SQLModelingApproachesInline predictivemodel toaugment inputdataConsider: DemographicsGenerates SQL scripts Past purchasesand workflow API for Recent purchasesdeploymentUnstructured data Comments & tweetsalso mined byalgorithmsCopyright 2016 Oracle and/or its affiliates. All rights reserved.

Advanced SQL EngineFull-featured QueryProcessing EnginePROFITSQLSQLSQLSQL SQLSQLSQLSQL SQLSQLSQLSQLSQLSQLSQL SQLSQLSQLComprehensiveSQL LanguageAny data: SQLSophisticatedqueryoptimizationJoins, aggregations,filters, indexes, , InmemoryCopyright 2016 Oracle and/or its affiliates. All rights reserved.Any AnswerOperational, reporting,analytical, predictive

Oracle Advanced Analytics—On Premise or Cloud100% Compatibility Enables Easy Coexistence and MigrationCoExistence and MigrationSame ArchitectureOn-PremiseSame ML/AnalyticsOracle CloudSame StandardsTransparently move workloads and ML/analytical methodologies betweenOn-premise and public cloudCopyright 2016 Oracle and/or its affiliates. All rights reserved.27

Manage and Analyze All Data—SQL & Oracle Big Data SQLBig Data SQL Advanced AnalyticsOracle Big Data ApplianceOracle Database 12cData AnalystsSQL / RJSONStructured and Unstructured Data Reservoir JSON data HDFS / Hive NoSQL Spatial and Graph data Image and Video data Social MediaStore business-critical data in Oracle Customer data Transactional data Unstructured documents, comments Spatial and Graph data Image and Video data Social MediaData analyzed via SQL / R / GUI R Clients SQL Clients Oracle Data MinerCopyright 2016 Oracle and/or its affiliates. All rights reserved.

More Data Variety—Better Predictive Models Increasing sources ofrelevant data can boostmodel accuracy100%100%Naïve Guess orRandomRespondersModel with “Big Data” andhundreds -- thousands of inputvariables including: Demographic data Purchase POS transactionaldata “Unstructured data”, text &comments Spatial location data Long term vs. recent historicalbehavior Web visits Sensor data etc.Engineered Features – Derived attributes/variablethat reflect domain knowledge—key to best modelsModel with 20 variablesModel with 75 variablesModel with 250 variables0%Population SizeCopyright 2016 Oracle and/or its affiliates. All rights reserved.

Oracle Data Miner GUIEasy to Use for “Citizen Data Scientist” Easy to use todefine analyticalmethodologiesthat can beshared SQL DeveloperExtension Workflow APIand generatesSQL code forimmediatedeploymentCopyright 2016 Oracle and/or its affiliates. All rights reserved.31

Sharing, Automation and DeploymentImmediately Go to “Productionization” of Analytical Methodologies Share ODMr workflows Workflow API for 100% automation Immediate deployment of data analyst’smethodologies SQL Script Generation Deploy methodology as SQL scriptsCopyright 2016 Oracle and/or its affiliates. All rights reserved.

Fraud Prediction DemoAutomated In-DB Analytical Methodologydrop table CLAIMS SET;exec dbms data mining.drop model('CLAIMSMODEL');create table CLAIMS SET (setting name varchar2(30), setting value varchar2(4000));insert into CLAIMS SET values ('ALGO NAME','ALGO SUPPORT VECTOR MACHINES');insert into CLAIMS SET values ('PREP AUTO','ON');commit;begindbms data mining.create model('CLAIMSMODEL', 'CLASSIFICATION','CLAIMS', 'POLICYNUMBER', null, 'CLAIMS SET');end;/-- Top 5 most suspicious fraud policy holder claimsselect * from(select POLICYNUMBER, round(prob fraud*100,2) percent fraud,rank() over (order by prob fraud desc) rnk from(select POLICYNUMBER, prediction probability(CLAIMSMODEL, '0' using *) prob fraudfrom CLAIMSwhere PASTNUMBEROFCLAIMS in ('2to4', 'morethan4')))where rnk 5order by percent fraud desc;Copyright 2016 Oracle and/or its affiliates. All rights reserved.Automated Monthly “Application”! Justadd:CreateView CLAIMS2 30AsSelect * from CLAIMS2Where mydate SYSDATE – 30Time measure: set timing on;

OAA Oracle Data Mining SQL Sample ProgramsPredictive analytics EXPLAIN routine-- Cleanup old output table for repeat runsBEGIN EXECUTE IMMEDIATE 'DROP TABLE ai explain output';EXCEPTION WHEN OTHERS THEN NULL; END;/-------------------- Run the EXPLAIN routine to get attribute importance resultsBEGINDBMS PREDICTIVE ANALYTICS.EXPLAIN(data table name 'mining data build v',explain column name 'affinity card',result table name 'ai explain output');END;/------------------------- DISPLAY RESULTS--- List of attribute names ranked by their importance value.-- The larger the value, the more impact that attribute has-- on causing variation in the target column.-column attribute name format a40column explanatory value format 9.999SELECT attribute name, explanatory value, rankFROM ai explain outputORDER BY rank, attribute name;A1 A2 A3 A4 A5 A6 A7Copyright 2016 Oracle and/or its affiliates. All rights reserved.

OAA Oracle Data Mining SQL Sample ProgramsSample program for the DBMS DATA MINING package – Decision Tree-- Given demographic data about a set of customers, predict the-- customer response to an affinity card program using a classifier-- based on Decision Trees algorithm.-- CREATE A NEW MODEL--- Build a DT modelBEGINDBMS DATA MINING.CREATE MODEL(model name 'DT SH Clas sample',mining function dbms data mining.classification,data table name 'mining data build v',case id column name 'cust id',target column name 'affinity card',settings table name 'dt sh sample settings');END;/SELECT T.cust id, S.prediction, S.probability, S.costFROM (SELECT cust id,PREDICTION SET(dt sh clas sample COST MODEL USING *) psetFROM mining data apply vWHERE cust id 100011) T,TABLE(T.pset) SORDER BY cust id, S.prediction;Copyright 2016 Oracle and/or its affiliates. All rights reserved.

Oracle Advanced AnalyticsReal-Time Scoring, Predictions and Recommendations On-the-fly, single record apply with new data (e.g. from call center)Select prediction probability(FRAUD 1 SVM 1, 'Yes'USING 7800 as bank funds, 125 as checking amount, 20 ascredit balance, 55 as age, 'Married' as marital status,250 as MONEY MONTLY OVERDRAWN, 1 as house ownership)from dual;Social MediaCall CenterLikelihood to respond:Get AdviceBranchOfficeRMobileWebEmailCopyright 2016 Oracle and/or its affiliates. All rights reserved.

FiservRisk Analytics in Electronic PaymentsObjectives Prevent 200M in losses every year using data tomonitor, understand and anticipate fraudSolution “When choosing the tools for fraud management, speed is acritical factor. Oracle Advance Analytics provided a fast andflexible solution for model building, visualization and integrationwith production processes.”– Miguel Barrera, Director of Risk Analytics, Fiserv Inc.– Julia Minkowski, Risk Analytics Manager, Fiserv Inc . We installed OAA analytics for model developmentduring 2014 When choosing the tools for fraud management, speedis a critical factor OAA provided a fast and flexible solution for modelbuilding, visualization and integration with productionprocessesOracle Advanced Analytics3 monthsto run & deployLogisticRegression(using SAS)1 monthto estimate anddeploy Trees andGLMCopyright 2016 Oracle and/or its affiliates. All rights reserved. 1 week toestimate, 1week to installrulesin online application1 day to estimate anddeployTrees GLM models(using Oracle AdvancedAnalytics)

Ease of DeploymentData Miner Survey 2016 by Rexer AnalyticsWhile 6 out 10 data miners report the data is available for analysis within days ofcapture, the time to deploy the models takes substantially longer. For 60% of therespondents the deployment time will range between 3 weeks and 1year.Everyoneforgets aboutdeployment –but is mostimportantcomponent! 2014 Fiserv, Inc. or its affiliates.

TurkcellCombating Communications FraudObjectives Prepaid card fraud—millions of dollars/year Extremely fast sifting through huge data volumes; withfraud, time is moneySolution “Turkcell manages 100 terabytes of compressed data—or onepetabyte of uncompressed raw data—on Oracle Exadata. WithOracle Data Mining, a component of the Oracle AdvancedAnalytics Option, we can analyze large volumes of customer dataand call-data records easier and faster than with any other tooland rapidly detect and combat fraudulent phone use.”– Hasan Tonguç Yılmaz, Manager, Turkcell İletişim Hizmetleri A.Ş. Monitor 10 billion daily call-data records Leveraged SQL for the preparation—1 PB Due to the slow process of moving data, Turkcell ITbuilds and deploys models in-DB Oracle Advanced Analytics on Exadata for extremespeed. Analysts can detect fraud patterns almostimmediatelyOracle Advanced AnalyticsIn-Database Fraud ModelsExadataCopyright 2016 Oracle and/or its affiliates. All rights reserved.

UK National Health ServiceCombating Healthcare FraudObjectives Use new insight to help identify cost savings and meet goals Identify and prevent healthcare fraud and benefit eligibilityerrors to save costs Leverage existing data to transform business and productivity “Oracle Advanced Analytics’ data mining capabilities and OracleExalytics’ performance really impressed us. The overall solution isvery fast, and our investment very quickly provided value. We cannow do so much more with our data, resulting in significantsavings for the NHS as a whole”– Nina Monckton, Head of Information Services,NHS Business Services AuthoritySolution Identified up to GBP100 million (US 156 million) potentiallysaved through benefit fraud and error reduction Used anomaly detection to uncover fraudulent activity wheresome dentists split a single course of treatment into multipleparts and presented claims for multiple treatments Analyzed billions of records at one time to measure longerterm patient journeys and to analyze drug prescribing patternsto improve patient careOracle Exadata DatabaseMachineOracle AdvancedAnalyticsCopyright 2016 Oracle and/or its affiliates. All rights reserved. Oracle Exalytics In-MemoryMachineOracle Endeca InformationDiscoveryOracle Business Intelligence EE

DX MarketingCloud Based Predictive Analytics/Database MarketingObjectives Cloud-based solution Increase revenue Reduce time-to-market “Time to market has significantly improved from 4-6 weeks to lessthan a week with the result the company can bring new clients onboard faster. This has helped boost revenues by 25% in the sixmonths since using Oracle’s DBCS.”– DX MarketingSolutionOracle CloudOracle Advanced AnalyticsDX Marketing Expands Customer Acquisition with Oracle Cloud– YouTube videoCopyright 2016 Oracle and/or its affiliates. All rights reserved.

Zagrebačka Bank (biggest bank in Croatia)Increases Cash Loans by 15% Within 18 Months of DeploymentObjectives Needed to speed up entire advanced analytics process;data prep was taking 3 days; model building 24 hours Faster time to “actionable analytics” for Credit RiskModeling and Targeted Customer Campaigns “With Oracle Advanced Analytics we execute computations onthousands of attributes in parallel—impossible with open-sourceR. Analyzing in Oracle Database without moving data increasesour agility. Oracle Advanced Analytics enables us to make qualitydecisions on time, increasing our cash loans business 15%.”– Jadranka Novoselovic, Head of BI Dev., Zagrebačka BankSolution Zaba migrated from SAS to the Oracle AdvancedAnalytics platform for statistical modeling andpredictive analytics Increased prediction performance by leveraging thesecurity, reliability, performance, and scalability ofOracle Database and Oracle Advanced Analytics forpredictive analytics—running data preparation,transformation, model building, and model scoringwithin the database“We chose Oracle because our entire data modeling process runs onthe same machine with the highest performance and level ofintegration. With Oracle Database we simply switched on the OracleAdvanced Analytics option andneeded no new tools,”– Sinisa Behin, ICT coordinatorat BI Dev. Zagrebačka BankZabaBank Oracle Customer Snapshot on OTNCopyright 2016 Oracle and/or its affiliates. All rights reserved.

Market Basket & Advanced Analytics at Dunkin Brands “Exponential growth in combinations with each hierarchy.Objectives2 years of pre-computed Market Baskets and associatedsales measures for reporting. Nightly compute within ETLwindow data with 1 day latency.” Store development dashboards to identify opportunities 8 M daily transactions, 25M transaction detail lines 20 TB data warehouse size, sales data about 10 TB– Dunkin Brands, Mahesh Jagannath, Senior Manager,Business Intelligence Market basket analysis and customer loyalty & segmentation(Excerpts from Dunkin Brands presentation at Oracle Open World 2014) Solution Exadata Engineered Systesm Oracle Advanced Analytics Option Market Basket Analysis, Clustering, Classification,ClusteringAlgorithmSegmentation, Loyalty AnalysisCustomerDataProfilesExcerpts fro

Oracle's Advanced Analytics (Machine Learning Platform) Multiple interfaces across platforms — SQL, R, GUI, Dashboards, Apps Oracle Advanced Analytics -HQL Database Option SQL Data Mining, ML & Analytic Functions R Integration for Scalable, Distributed, Parallel in-Database ML Execution SQL Developer/ Oracle Data Miner R Client Applications