NORMAL SERVICE

WILL NOT RETURN

JUST ASK WATSON

Cognitive Revolution

TODAY’S AGENDA…

Julien

Redmond

Samuel

Williams

Wireless

Smart Devices

Anywhere

Anytime

Anything

2015: One mobile

device for every

human

20011000 songs

2014900 million

GAME CHANGINGSINCE…

28 MAY 2010

On Demand

Unlimited

Processing

Power

Creating

New

Platforms

Cloud

Computing

15

Example:

Wine

Pairing

Example Wine

Pairing

Example:

Resume

Accelerated

learning platform…

OBSERVATION #ONE

Where it will lead

I don’t know.

However I

believe…

Recommendation

It is the intersection between AI + BI

OBSERVATION

#TWO

• Human

• Machine

• Expert

OBSERVATION

#THREE

Creating entirely new

possibilities… not yet

thought of

OBSERVATION

#FOUR

OBSERVATION #FIVE

Enabling entirely

different

approaches to:

• Building

applications

• Mine data

• Achieve

meaningful

outcomes

RIGHT BRAIN

CONCLUSIONS

1. Accelerated learning platform

2. This is the intersection between AI + BI

3. Human + Machine + Expert

4. Creating entirely new possibilities not yet

thought of

5. Enabling entirely different approaches to

building applications, mining data +

achieving business outcomes…. staying

competitive

IBM Watson

Analytics

Cognitive products

and servicesCognitive products and services can sense,

reason and learn so they can adapt and

develop new capabilities not previously

imaginable.

THE POSSIBILITIES OF COGNITIVE:

Elemental Path, a Watson ecosystem partner,

developed Cognitoy, a dinosaur toy, that answers its

playmate’s questions, and even learns their sense of

humor by listening to and adapting its personality to

play differently with each child.

Results: Cognitoy is able to take on a unique

personality that evolves over time based on the

child’s interactions and helps her learn rhyming,

spelling, vocabulary, mathematics and more.

WHERE WE ARE NOW:

Decision management

platforms will expand at a

CAGR of

By 2018

Apps with advanced and

predictive analytics

are growing

of all consumers will

regularly interact with

services based on cognitive.

50%

faster than apps without

predictive functionality.

65%

60%through 2019, in response

to the need for greater

consistency and

knowledge retention.

It’s an “always-on” world

A Do-It-Yourself mentality now prevails

Expectations from technology have never been higher

Our work and personal lives have blurred

Making decisions rapidly is no longer a goal; it’s an

imperative

The desire to make data-driven decisions is prevalent

Source: Analytics: The New Path to Value, a joint MIT Sloan Management Review and IBM Institute for Business Value study. Copyright © Massachusetts Institute of Technology

Access to required data sources is critical while maintaining governed

standards

34% can not find time to analyze data

38% have a limited understanding of

how to use analytics

Leveraging analytics still faces many obstacles

24% find it difficult to get data

Even a simple analytics project has multiple steps and people

Data Access

Data Preparation

Analysis

Validation

Collaboration

Reporting

Business

Analysts

Business

Users

Data Scientists

and

Statisticians

IT

And it’s rarely a straightforward process

Business

Users Data Scientists

and

Statisticians

IT

Data Access

Analysis

ValidationCollaboration

Reporting

Data Preparation

Business

Analysts

Think Ahead

Tell a StoryUnderstand Your

Business

Get Better Data

Mobile Ready Secure

Embedded information services provide

data access and refinement

Automated intelligence accelerates your

ability to answer questions

Predictive analytics reveals insights and

opportunities

Visualizations support your decisions and

communicate results

Put analytics in the hands of a broad range of users

Make data access and refinement easier

Deliver through the cloud for agility and speed

Business Analysts Data Scientists IT

Self-service analytics for business users and

experts alike

Business Users

Empowering the business for success

PrioritizingAccounts

Receivable

Employee Retention

HelpdeskCase

Analysis

CampaignPlanning and ROI

WarrantyAnalysis

Customer Retention

Finance HRITMarketing OperationsSales

“Which accounts are most likely to be paid?

How can collections be more efficient? How

does it affect revenue and profit when we lose

customers? How can the sales pipeline help

me forecast revenue?”

Justin Chen, Finance Manager

Justin ChenCustomer attrition

Watson Analytics analyzes

customer data to identify which

customers are likely to leave and

why and predicts the effect on

revenue. Justin can then

determine which customer

investments will lead to more

profitable growth.

Natural language dialogue

Cloud-based agility

Data discovery

Quick start intuitive interface

Mobile-ready

Unified analytics experience

Visual storytelling

Intelligent automation

Data access and refinement

Report and dashboard

creation

Integrated social business

Guided analytic

discovery

Single Analytics Experience

Fully Automated Intelligence

Natural Language Dialogue

Guided Analytic Discovery

Visit WatsonAnalytics.com and get started for free

1. A cognitive strategy

Determine what data you need, which experts will train the system;

where you must build more human engagement; which products,

services, processes and operations should be infused with cognition,

and which parts of the unstructured 80% of data you

most need to focus on to make discoveries for the future.

2. A foundation of data and analytics

Collect and curate the right data—data you own, data from

others, data available to all; both structured and unstructured. Apply

cognitive technologies to this data in order to sense, learn and

adapt, thereby creating competitive advantage.3. Cloud services optimized for industry,

data and cognitive APIs

The building blocks for products and services are code, APIs and

diverse data sets. The platform you choose to develop on, and the agile

development culture and methods you embrace, will be critical to your

success.

4. IT infrastructure tuned for

cognitive workloads

Architect a new kind of IT core—a heterogeneous infrastructure

that serves as the backbone of your enterprise. Do this rapidly

and affordably by harmonizing technologies from public, private

and hybrid cloud with distributed devices, IoT instrumentation

and your existing systems.

5. Security for a Cognitive Era

As cognition makes its way into cars, buildings, roadways, business

processes, fleets, supply chains—securing

every transaction, piece of data, and interaction becomes

essential to ensure trust in the entire system—and in your brand

and reputation.

Relationship

Extraction

Questions

&

Answers

Language

Detection

Personality

Insights

Keyword

ExtractionImage Link

Extraction

Feed

Detection

Visual

Recognition

Concept

Expansion

Concept

Insights

Dialog Sentiment

Analysis

Text to

Speech

Tradeoff

Analytics

Natural

Language

Classifier

Author

Extraction

Speech to

Text

Retrieve

&

Rank

Watson

News

Language

Translation

Entity

Extraction

Tone

Analyzer

Concept

Tagging

Taxonomy

Text

Extraction

Message

Resonance

Image

Tagging

Face

Detection

Answer

Generation

Usage

Insights

Fusion Q&A

Video

Augmentation

Decision

Optimization

Knowledge

Graph

Risk

Stratification

Policy

Identification

Emotion

Analysis

Decision

Support

Criteria

Classification

Knowledge

Canvas

Easy

Adaptation

Knowledge

Studio Service

Statistical

Dialog

Q&A

Qualification

Factoid

PipelineCase

Evaluation

The Waston that competed on

Jeopardy! in 2011 comprised what

is now a single API—Q&A—built

on five underlying technologies.

Since then, Watson has grown to

a family of 28 APIs.

By the end of 2016, there will

be nearly 50 Watson APIs—

with more added every year.

Natural Language

Processing

Machine Learning

Question Analysis

Feature Engineering

Ontology Analysis

CERTUS CUSTOMER EXAMPLES

Bringing technology, people and processes together

Certus are helping customers build an

Information Architecture that stores,

explores and analyses data in new

ways.

New Architecture to Leverage All Data and Analytics

Data inMotion

Data atRest

Data inMany Forms

Information

Ingestion and

Operational

Information

Decision

Management

BI and Predictive

Analytics

Navigation

and Discovery

Intelligence

Analysis

Landing Area,

Analytics Zone

and Archive

Raw DataStructured DataText AnalyticsData MiningEntity AnalyticsMachine Learning

Real-time

Analytics Video/Audio

Network/Sensor

Entity Analytics

Predictive

Exploration,

Integrated Warehouse,

and Mart Zones

Discovery

Deep Reflection

Operational

Predictive Stream Processing Data Integration Master Data

Streams

Information Governance, Security and Business Continuity

BigInsights HadoopData Platform

Sources

Information Server Data Integration

Watson Data Exploration BI / Analytics

Break the “Waterfall Style” Lifecycle• Empowers LOB to access data sooner

• Eliminates slow modeling prior to staging

Analytics Performance Booster• Leveraging Teradata for its strength

• Less wasted process, fewer batch windows

Lower Cost Staging, ELT and Deep Data• Commodity infrastructure for data platform

• Automated data transformation and governance

Fresh Capacity and Cost Avoidance• Recoup previously displaced disk

• Defer costly upgrades for production uses

Improving Integration for Analytics

Certus are using cutting edge

matching to give companies a 360

degree view of customers, students,

products or assets

Maximize 1:1 consumer relationshipsDeliver personalized offers aligned to unique behaviors, needs and desires

Brand reputationRight message every time in market

Marketing productivityIncreased breadth of digital channels,

emphasis on cross-sell / up-sell / right-

sell opportunities, understanding and

embracing ROMI

Deliver value across all touch pointsBuild opportunity for revenue growth throughout marketing value chain

360 Degree View of the CustomerUnderstanding, responding and maximizing each unique customer relationship

Optimize marketing mix Model and plan balancing needs of channels, probability of ROI success and resource constraints

Customer growth and retention Demanding customers, commoditized products and crowded competitive marketplace

Define MDM Value

Consuming Applications

Contact Warehouse CRM MarketingPortal

Kate Lamb

32 George Street

Perth, 6000

Kate Jones

Perth, WA 6000

12/06/1970

Catherine Jones

44 Station Street

Perth, WA

Mrs K Lamb

32 St. George

06/12/1970

Dr Katherine Lamb

23 George St

Perth, 6000

06/12/1970

Miss C Jones

Station Street, Perth

Western Australia, 6000

12/06/1970

Person Entity

Dr. Katherine Lamb

Composite View

Dr Katherine Lamb

32 George St, Perth, WA 6000

DOB: 12/06/1970

Probabilistic Matching

Household relationships

› Inspect potential household members and link to confirm relationships.

Employment Relationships

› Inspect relationships between companies and staff.

Joseph’sHousehold

Wife of

Daughterof

Sonof

Is the Subsidiary of

SuppliesProduct to

Is Married to

Is theOwnerof

Has anAccount

with

Is Employed by

Entity Relationships

Big Match › The same MDM Match engine runs on Hadoop to connect

more sources of information about the customer.

Increased engagement

Increased revenue

Decreased risk

Less ‘gut feel’

More data (when used effectively)

Increase on Churn retention rate (no

discounting required)

More newsletter article clicks

More articles read per session

Lookalike acquisition model

increasing conversion

Strong Ad revenue growth 20%

10%

Linkage: audience connectionsAny hard links across accounts, Consumer & Household, Fuzzy matching, Enrichment (Single Customer View)

MDM Value – News Corp

Presentation to IBM SolutionConnect Event Sydney 2014

Certus are helping customers put in

successful data stewardship models to

trust the results they get from reporting

and analytics.

Technology Driven

Process Driven

1) Define

Business

Problem

2) Obtain

Executive

Sponsorship

3) Conduct

Maturity

Assessment

4) Build

Roadmap

6) Build

Business

Glossary

7) Understand

Data

8) Create

Metadata

Repository

5) Establish

Organizational

Blueprint

9) Define

Metrics

11) Govern

Master Data

10) Govern

Data Quality

14) Govern

Analytics

13) Govern

Security &

Privacy

12) Govern

Lifecycle of

Information

15) Measure

Results

Business Glossaries that Extend to Big Data

Monitoring Quality and Stewardship Tasks

Data Quality Dashboard

› Data Quality Metrics across lines of business that makes quality relevant to everyone.

Stewardship Center

› Manage a team of stewards and allocates data quality investigation and data remediation tasks.

› Certus has helped

customers manage

data quality via a

policy driven

approach.

Data Quality Scorecards

57

How do I trust a report?

Quality and Lineage behind a report

Data lineage

track back,

quality of each

asset in lineage

Data Quality

trends over timeQuality Metrics

QSuper Success Story

IBM Insight Conference 2015

Operational Impact› Productivity improvements

through automation of data checking reporting.

› Data checking is consistency applied

› Increased confidence in data› Workloads can be managed and

anticipated› KPI’s can be applied

Regulatory Impact

› Risk and Compliance reporting is measurable and can be monitored

› Mitigating risk of penalties and fines through more accurate reporting

› Industry leader in data quality activities.

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