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Defining a Roadmap to Big Data Success

Robert Stackowiak, Oracle Vice President, Big Data

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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

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Data Data Data Management Data Management Results Results Apps Apps Packaged? Highly Custom

Today’s Typical Infrastructure

Factory Many Warehouses

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 100s billions sensors  Mainframe computers  Minicomputers & PCs  Relational Database

Hadoop & NoSQL databases

Platform History Evolution

Data Streams & Search

1880

1900

1920

1940

1960

1980

2000

2020

 Hollerith

Machine  Electronic computers  Internet browsers

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What’s Behind Many Use Cases for Hadoop & NoSQL Databases

• Streaming data feeds to enable better

/ new business decisions

• Lower cost for storage & analysis of all data (create data reservoir / data

lake)

• Faster discovery of important data

• Faster discovery of important data combinations via “schema on read”

• Predictive analytics on all kinds of data

• Better scale ETL processing (and data quality transformations)

Web Log

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Who Oracle is Talking to about the Internet of Things

• Aircraft Suppliers & Manufacturers

• Agribusiness

• Automotive Suppliers & Manufacturers

• Computer & Mobile Device Manufacturers

• Home & Commercial Appliance Manufacturers

• Industrial Manufacturers

• Insurance Companies

• IT Service Providers Manufacturers

• Energy Management Firms & Utilities

• Entertainment & Media

• Government Agencies

• Healthcare Providers

• IT Service Providers

• Oil & Gas

• Railroads & Trucking

• Retailers

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Typical Business Drivers in Financial Services

• Earnings Growth & Profit Margin

– Launch new services & expand into new markets

• Marketing & Customer 360

– Most relevant offers, customer loyalty growth

• Risk Management & Stress Testing

• Reputational Risk

– Understand customer sentiment toward company

• Risk Management & Stress Testing

– Understand risk, use non-traditional data in scoring

• Fraud Detection

– Correlate seemingly unrelated events to find fraud

• Money Trading and Transfer Compliance

– Monitor streaming data for illicit activities

• Anti-Money Laundering

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Typical Business Drivers in Retail

• Customer Experience

– Single view of customer (Omni-Channel) including item interest, purchases across channels, targeted loyalty offers

• Merchandise Sales

• Distribution & Warehouse Management – Optimally sized and located facilities, optimized

logistics

• Risk Analysis

• Merchandise Sales

– Category management including time to sale of items, product mix in stores and by region, impact of events and weather

• Point of Sales

– Market basket analysis, shopping cart abandonment

• Supplier & Partner Services Performance – Quality of goods and services, on-time delivery

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Typical Business Drivers in Manufacturing

• Parts Manufacturing Planning

– Ability to scale up / down based on demand

• Quality of Manufacturing & Warranty – QA, root cause and recall determination

• Promotions & Marketing

– Optimal spending with measurable results

• Risk Analysis

– Understand potential safety problems / liability

– QA, root cause and recall determination

• Supplier Performance – Quality and on-time delivery

• Distribution & Warehouse Management – Optimally sized and located facilities

• Customer Service Innovation – Differentiated levels of service

– Understand potential safety problems / liability

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Business Drivers in Transportation & Logistics

• Transportation Network Resource Assessment & Planning

– Predictive maintenance determination

– Ability to scale up / down based on demand • Route Optimization

• Promotions & Marketing

– Optimal spending with measurable results • Risk Analysis

– Understand potential driver / goods liability and • Route Optimization

– Most optimal pickup and delivery, crew staffing • Distribution Center / Warehouse Management

– Optimally sized and located facilities • Customer Service Innovation

– Differentiated levels of service

– Understand potential driver / goods liability and potential for driver churn

• Maintenance Analysis

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Business Drivers in Government

• Fraud Detection

– Predictive modeling of potential fraud in welfare, healthcare services, supplier contracts, etc.

• Supply Chain Management Logistics

• Threat and Safety Analysis

– Optimal deployment of police in reaction to changing crime patterns

– Smarter building inspections reducing health & fire risks

– Route optimization and optimized maintenance

– Optimally located supplies / distribution points • Transportation Network Resource Planning

– Manage traffic flows & plan improvements • Research

– Government funded healthcare / other research

fire risks

– Constituent Sentiment

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Silos

Silos StandardizeStandardize OptimizeOptimize Information as a

Platform

Information as a Platform

• One off tools/solutions

• Bottom-up

• Local business unit

driven

• Enterprise standard

tools/solutions

• Data warehouse and

dependent data marts

• Agile, flexible

architecture

• Advanced analytics &

real-time

recommendations

• All stage 3 capabilities

delivered as a platform (service/cloud)

• Access of tools and

Unified Information Architecture Maturity Phases

driven

• Many versions of truth

• Independent data

marts

• IT & LOB partnership

• Secure, consistent

access to all data

recommendations

• Analyze “just in time”

structured & streaming data together

• Internet of Things

introduced

• Access of tools and

data among broad subscriber group

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Today’s Evolving Analytics Infrastructure

Data

Data Fast DataFast Data

Events Actions 1 2 3 Streams Data Management Data Management Results Results Data Services Apps Apps Packaged Custom

Reservoir Factory Warehouse

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Data

Data Fast DataFast Data

Events Actions 1 2 3 Streams Data Management Data Management Results Results Data Services Apps Apps Packaged Custom ACCESS MANAGEMENT IDENTITY MANAGEMENT ACCESS MANAGEMENT IDENTITY MANAGEMENT

ORACLE STREAM EXPLORER ORACLE NOSQL DATABASE ORACLE STREAM EXPLORER

ORACLE NOSQL DATABASE

ORACLE / EXADATA BIG DATA APPLIANCE

ORACLE / EXADATA BIG DATA APPLIANCE

G O LD E N G A T E O R A C LE D A TA I N T E G R A T O R O R A C LE D A TA IN T E G R A T O R REAL TIME DECISIONS REAL TIME DECISIONS INDUSTRY DATA MODELS BI APPS INDUSTRY DATA MODELS BI APPS

Today’s Evolving Analytics Infrastructure & Oracle Products

Reservoir Factory Warehouse

People Smart Things Data Lab Data Lab Data Science Discovery Data Sets Business Business Analytics Analytics Visualization Reports

BIG DATA APPLIANCE ADVANCED ANALYTICS

BIG DATA SQL BIG DATA APPLIANCE ADVANCED ANALYTICS

BIG DATA SQL

BIG DATA DISCOVERY VISUAL ANALZER BIG DATA APPLIANCE

ORAAH

BIG DATA DISCOVERY VISUAL ANALZER BIG DATA APPLIANCE

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Oracle Big Data Cloud Services

Data

Data Fast DataFast Data

Events Actions 1 2 3 Streams Data Management Data Management Results Results Data Services Apps Apps Packaged Custom Data Preparation Integration Internet of Things Process Big Data Big Data SQL NoSQL Database Mobile

Java, JRuby, Node.JS Developer

Data Management Fast Data

Apps

Reservoir Factory Warehouse

People Smart Things Data Lab Data Lab Data Science Discovery Data Sets Business Business Analytics Analytics Visualization Reports Business Intelligence Data Visualization Big Data Discovery R, Spatial & Graph

Data Lab

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Assessing Readiness for Change

IT Readiness

–History of delivering to business specs

–Agile methodologies utilized

–Deliver right data at right time

Business Readiness

–Fact-based decision making

–Senior executive sponsorship & funding

–Business needs prioritized & key performance indicators understood Deliver right data at right time

–Proven available, serviceable & secure infrastructure

–Hadoop / NoSQL database skills

–Internet of Things skills (mid-tier)

Business needs prioritized & key performance indicators understood

–Data quality & tools align with analyst needs & skills

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IT Focus Visioning (IT & LOBs)

Use Case Hypothesis (LOBs)

A Methodology for Success

Implementation (IT, SI & LOBs)

Roadmap to Implementation

(IT & LOBs)

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Examples of Potential Use Cases

• Industry Big Data Whitepapers including IoT

– Communications Service Providers

– Financial Services & Banking

– Healthcare Payers

– Healthcare Providers

– Higher Education

– Logistics & Transportation

– Manufacturing

– Media & Entertainment

– Oil & Gas

– Pharmaceuticals & Life Sciences

– Retail

– Utilities

http://www.oracle.com/goto/EA

References

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