Machine Learning Data Management Platforms

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1 Machine Learning Data Management Platforms Move the Algorithms; Not the Data! Charlie Berger, MS Engineering, MBA Sr. Director Product Management, Machine Learning, AI and Cognitive Analytics

2 Safe Harbor Statement The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle s products remains at the sole discretion of Oracle. 2

3 Today Google Now Provides Tailored Local Updates Get Droid alerts/updates: Local news Local weather Your stated interests Your sports teams National news updates

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5 Imagine these scenarios Meet old Girlfriend at Coffee Shop Wake up, read Droid alert about meeting a old girlfriend in the coffee shop who will be getting married, but hasn t told anyone yet. Change of address Adopt a dog Facebook pictures Tweets Online ring purchase by close contact When you meet your old girlfriend at the coffee shop this morning, act surprised to learn she is getting married

6 The Near Future Big Data, Interconnected World + Machine Learning Datafication of EVERYTHING Digital exhaust GPS Tweets Geo-tags Facebook posts, pics, friends LinkedIn RFID Medical records

7 The Core Ingredients of Good Machine Learning Domain Knowledge + Data Machine Learning Algorithms Insights, Predictions A1 A2 A3 A4 A5 A6 A7

8 Most Important Factor in Machine Learning? Deployment!!

9 2001: A Space Odyssey The Dawn of Man scene Our adoption of machine learning and artificial intelligence is about at this stage the BEGINNING!

10 CLASSIFYING CUSTOMERS Features Basic Query Basic Analytics Machine Learning Age / Gender Marketing Preferences RFM (Recency, Frequency and Monetary Value): Purchases in the Last 3/6/12 mo. Behavioral Customer Segment Probability to Buy New Product X Known Known Known Unknown Unknown Mail and 1 item / $35 in the last 3 mo Retired Cosmopolitan 2 items / $150 in the last 6 mo Affluential Executive and Facebook 3 items / $75 in the last 3 mo New Home Mom and Google+ 3 items / $225 in the last 12 mo Young Successful startup 31% 45% 55% 21% 72% Mail, and Twitter 9 items / $250 in the last 6 mo Executive product collector Copyright 2017, Oracle and/or its its affiliates. All All rights reserved.

11 DX Marketing Cloud Based Predictive Analytics/Database Marketing Objectives Cloud-based solution Increase revenue Reduce time-to-market Time to market has significantly improved from 4-6 weeks to less than a week with the result the company can bring new clients on board faster. This has helped boost revenues by 25% in the six months since using Oracle s DBCS.. DX Marketing Solution Oracle Cloud Oracle Advanced Analytics DX Marketing Expands Customer Acquisition with Oracle Cloud YouTube video

12 UK National Health Service Combating Healthcare Fraud Objectives Use new insight to help identify cost savings and meet goals Identify and prevent healthcare fraud and benefit eligibility errors to save costs Leverage existing data to transform business and productivity Solution Identified up to GBP100 million (US$156 million) potentially saved through benefit fraud and error reduction Used anomaly detection to uncover fraudulent activity where some dentists split a single course of treatment into multiple parts and presented claims for multiple treatments Analyzed billions of records at one time to measure longerterm patient journeys and to analyze drug prescribing patterns to improve patient care Oracle Advanced Analytics data mining capabilities and Oracle Exalytics performance really impressed us. The overall solution is very fast, and our investment very quickly provided value. We can now do so much more with our data, resulting in significant savings for the NHS as a whole Nina Monckton, Head of Information Services, NHS Business Services Authority Update: 300M confirmed fraud 400+M additional potential identified Now moving to Cloud Oracle Exadata Database Machine Oracle Advanced Analytics Oracle Exalytics In-Memory Machine Oracle Endeca Information Discovery Oracle Business Intelligence EE

13 Zagrebačka Bank (biggest bank in Croatia) Increases Cash Loans by 15% Within 18 Months of Deployment Objectives 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 Risk Modeling and Targeted Customer Campaigns Solution Zaba migrated from SAS to the Oracle Advanced Analytics platform for statistical modeling and predictive analytics Increased prediction performance by leveraging the security, reliability, performance, and scalability of Oracle Database and Oracle Advanced Analytics for predictive analytics running data preparation, transformation, model building, and model scoring within the database With Oracle Advanced Analytics we execute computations on thousands of attributes in parallel impossible with open-source R. Analyzing in Oracle Database without moving data increases our agility. Oracle Advanced Analytics enables us to make quality decisions on time, increasing our cash loans business 15%. Jadranka Novoselovic, Head of BI Dev., Zagrebačka Bank We chose Oracle because our entire data modeling process runs on the same machine with the highest performance and level of integration. With Oracle Database we simply switched on the Oracle Advanced Analytics option and needed no new tools, Sinisa Behin, ICT coordinator at BI Dev. Zagrebačka Bank ZabaBank Oracle Customer Snapshot on OTN

14 Caixa Bank (the leading financial group in Spain) Caixa Bank Leads Innovation with Big Data Technology Objectives Need to serve 14M customers every day through multichannels Need to find new and better ways to interact with customers in the digital age. Solution In order to meet today s business needs and better serve our customers and improve their experience, it is important to embrace big data to enable new analytic capabilities and manage more information, Jordi Fontanals, chief operations officer (and former CIO) of CaixaBank in Barcelona, Spain, and winner of the Oracle Excellence Award - CIO of the Year Europe, Middle East, Africa Caixa Bank chose the Big Data Solution from Oracle Exadata, Advanced Analytics, Big Data Appliance, Exalytics Migrated all their previous analytics platforms to an Oracle architecture on hardware running Intel processors Can now provide personalized offers for an individual vs previously only by a segment Predictive models to help risk management Sources:

15 StubHub Customer Life Time value scoring and Demand Forecasting Objectives Develop R models directly against Exadata DW Use of R scripts developed by statisticians for scoring Customer Life Time value and Demand Forecasting models built using open-source R packages on Solaris M5K DW Solution "Oracle R Enterprise together with Oracle Active Data Guard technology enabled StubHub to offer an environment for data scientists to work directly with database resident data using the open source R language scripts as is. That enabled us to create an agile platform for data science reusing our existing data warehouse infrastructure and processes, and has demonstrated future possibilities for expansion Yadong Chen, Principal Architect, StubHub Oracle Database on Solaris Sparc, Active Data Guard and Oracle Advanced Analytics Data scientists build models directly on EDW Models versioned and stored in-db enabling collaboration and repeatability/auditability. R scripts developed by statisticians can be used as is in production, scoring in seconds Enables forward planning in Marketing & Sales Copyright 2014 Oracle and/or its affiliates. All rights reserved.

16 Machine Learning and Advanced Analytics Functionality Overview Copyright 2016, Oracle and/or its affiliates. All rights reserved.

17 Dilbert on Big Data 1

18 Machine Learning/Analytics + Data Warehouse + Hadoop/Spark Platform Sprawl Inherent Problems Complexity Data Movement Duplicated Data Data Latency Security exposures Duplicated Storage Duplicated Backups Duplicated Systems Dupicated Space and Power

19 Traditional vs. Oracle Machine Learning/Predictive Analtyics Traditional Move the data Don t move the data! 1

20 Traditional vs. Oracle Machine Learning/Predictive Analtyics Traditional Move the data Move the algorithms Simpler, Smarter Data Management + Analytics / Machine Learning Architecture

21 Oracle s Machine Learning/Advanced Analytics Fastest Way to Deliver Scalable Enterprise-wide Predictive Analytics Key Features Parallel, scalable machine learning algorithms and R integration In-Database + Hadoop Don t move the data Data analysts, data scientists & developers Drag and drop workflow, R and SQL APIs Extends data management into powerful advanced/predictive analytics platform Enables enterprise predictive analytics deployment + applications

22 Oracle s Machine Learning/Advanced Analytics Platforms Machine Learning Algorithms Embedded in the Data Management Platforms Analytics Producers Analytics Consumers Data Scientists, R Users, Citizen Data Scientists BI Analysts, Managers Functional Users (HCM, CRM) Data Management + Advanced Analytical Platform Big Data SQL Big Data Cloud Service Oracle Machine Learning Big Data Cloud ORAAH Machine Learning Algorithms, Statistical Functions + R Integration for Scalable, Parallel, Distributed Execution Database Cloud Oracle Machine Learning Database Edition Machine Learning Algorithms, Statistical Functions + R Integration for Scalable, Parallel, Distributed, in-db Execution

23 Manage and Analyze All Your Data Data Scientists, R Users, Citizen Data Scientists Architecturally, Many Options and Flexibility SQL / R Boil down the Data Like Big Data SQL / R Object Store Engineered Features Derived attributes that reflect domain knowledge key to best models e.g: Counts Totals Changes over time 2

24 Rapidly Build, Evaluate & Deploy Analytical Methodologies Leveraging a Variety of Data Sources and Types SQL Joins and arbitrary SQL transforms & queries power of SQL Transactional POS data Modeling Approaches Inline predictive model to augment input data Unstructured data also mined by algorithms Consider: Demographics Past purchases Recent purchases Comments & tweets Generates SQL scripts and workflow API for deployment

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29 Machine Learning & Advanced Analytics Getting Started

30 Getting Started Oracle ML/AA Resources & Links Oracle Advanced Analytics Overview Information Oracle's Machine Learning and Advanced Analytics 12.2c and Oracle Data Miner 4.2 New Features preso Oracle Advanced Analytics Public Customer References Oracle s Machine Learning and Advanced Analytics Data Management Platforms white paper on OTN Oracle INTERNAL ONLY OAA Product Management Wiki and Beehive Workspace (contains latest presentations, demos, product, etc. information) YouTube recorded Oracle Advanced Analytics Presentations and Demos, White Papers Oracle's Machine Learning & Advanced Analytics 12.2 & Oracle Data Miner 4.2 New Features YouTube video Library of YouTube Movies on Oracle Advanced Analytics, Data Mining, Machine Learning (7+ live Demos e.g. Oracle Data Miner 4.0 New Features, Retail, Fraud, Loyalty, Overview, etc.) Overview YouTube video of Oracle s Advanced Analytics and Machine Learning Getting Started/Training/Tutorials Link to OAA/Oracle Data Miner Workflow GUI Online (free) Tutorial Series on OTN Link to OAA/Oracle R Enterprise (free) Tutorial Series on OTN Link to Try the Oracle Cloud Now! Link to Getting Started w/ ODM blog entry Link to New OAA/Oracle Data Mining 2-Day Instructor Led Oracle University course. Oracle Data Mining Sample Code Examples Send an now to charlie.berger@oracle.com and my away message will send you many of these links Additional Resources, Documentation & OTN Discussion Forums Oracle Advanced Analytics Option on OTN page OAA/Oracle Data Mining on OTN page, ODM Documentation & ODM Blog OAA/Oracle R Enterprise page on OTN page, ORE Documentation & ORE Blog Oracle SQL based Basic Statistical functions on OTN Oracle R Advanced Analytics for Hadoop (ORAAH) on OTN Analytics and Data Summit, All Analytics, All Data, No Nonsense. March 20-22, 2018, Redwood Shores, CA

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