austrade presentation - big data the new oil (microsoft draft)

Is the New

We need to find it, Extract it, Refine it, Distribute it and use it to drive Economic Prosperity Dr Andrew Seit

Healthy dose of Scepticism is always good in the mix.

Is the New

Or

Insight & Action

Wisdom

Knowledge

Information

Data

Valu

e of D

ata

Insight & Action

Wisdom

Knowledge

Information

Data

Valu

e o

f Data

Big Data

Insight & Action

Wisdom

Knowledge

Information

Data

Valu

e o

f Data

Big Data

Agenda

#1. Impact and Opportunity Big Data has created.

#2. Big Data Value Creation in Enterprise & Consumer

#3. Value Capture in Big Data for Government

Impact and Opportunity of Big Data

Start of the Revolution

Source: Mckinsey

Attack of The Exponential Age (Hockey Stick)

Attack of The Exponential Age (Hockey Stick)

Delta Cost has decrease:

• Storage• Computation• Mobile• Cloud (New Models)• SaaS, PaaS, IaaS

• Do More with Less …

The Hype Curve for Innovation

The internet of Things

Wearables

Australian burn 1,800 calories per day

These Data has gone from being highly macro …

… to very personal

Nick burns 1982 calories per day

.…to very Geospatially localized & Situational Aware

Big Data Just got Bigger …Recognised any of these Social Network?

Big Data Just got Bigger …Recognised any of these Social Network?

Big Data awareness goes all the way to the top:

Big Data awareness goes all the way to the top:

• Big Data Opens up new possibilities

• Privacy and securities needs to be revisited

• Talents and knowledge is short in supply

Key Questions C-Level asked most

Are we getting left behind by our competitors?

Can we use technology-enabled trends to change the

game?

What can we learn from other industries?

What is a good place to start in building this BD

technology position?

How can we sustain a pipeline of opportunities

over time?

How can our CompanyWin

With Technology?2

34

5

1

The ease of capturing big data’s value , and the magnitude of its potential, vary across sectors.

Source: Mckinsey

All Top Tier Consultants have their “Big Data Gigs”

When Big Data meets Analytics

Values&

Insights

AnalyticsAttributionAlgorithm

3A’s

VolumeVelocityVarietyVeracity

4V’s

From Data to Analytics to Result

Analytics

DeploymentCapture & ETL

Use case for Big Data

3.

4.

5.

1.2.

Real-time Common Operating Picture & Analytics

NSW RFS Common Operating Picture

Insurance (Flood, Fire, Hail, Earthquake)

Value Creation of Big Data in Enterprise & ConsumerVisualization of Business Outcome

Search and Recommendation is about to get a whole lot smarter ….

SocialVoiceMobile Search MAP (GIS)

Relevant Relevant

Profile, PreferencePersonalizationRecommendationsocial BehaviourTargeted Ads, Geospatial

SEARCH & DiscoveryFoundation Capabilities for Big Data

Matching Engine

Search And Discovery (Big Data scale)

Search And Discovery (Big Data scale)

• When Big Data Meet Machine Learning

= Deep Learning

• Google = Google Brain $$$$$

• Microsoft = Microsoft ML $$$$

• IBM = Watson (7 years) $$$$$$$

• LinkedIn = Image Machine learning $$

• Facebook = Deepface AI $$$

• DARPA = NLP (mixed languages) $$$$$

Deep Learning: Intelligence from Big Data

Augmented Intelligence (Watson) Computing

Augmented Intelligence (Watson) Computing

Visualization of Export Opportunities?

Visualization of Historical & Cultural Data

Visualisation & Interaction of Economic Complexity

Summary1. Exponential Growth in Data Created, Collected and Stored.

X10 increase in “Situation Awareness” with Big Data. Rethink intuitional approaches to decision process.

2. BD is not a “Silver Bullet” but a new philosophy of problem solving. It is not just a technology answer but a holistic approach we should be seeking.

3. Private sector and Enterprise are attacking this “Fog-of-Data” with “Evidence-Based Decisions” , increasing both the tempo and speed of decisions.

4. Big Data will have Top-line and bottom-line implications for companies and far reaching effects on the economy.

Key Issues need to be addressed

• Privacy concerns

• Data security issues

• Intellectual ownership and liability issues

Big Data

Policies

• Deployment of Technologies

• Legacy system or inconsistent data formats

• Ongoing innovation (Collaborative & Open)

Technology and Technique

• Access to “Foreign” data

• Integrating with own proprietary data

• It’s Social, IOT, mobile, Cloud,

Data Available

(Real-time)

• Talent Shortage, Stop looking start Grooming

• Leadership that understands Big Data

• Align workflows and Incentives

Organization Change and

Talent

Conclusion/Next steps

1. Big Data is the New Oil. Secret-sauce is in the extraction process

2. From Data to Wisdom, that journey is gain through learning, trying and experimenting.

3. Big Data offers New possibilities and enrichment of current opportunities while creating new ones.

4. Start Now, Start Small, Iterate Fast (not to lose sight on the Privacy and security issues)

(Democratization of tools, data, technology)

Andrew.Seit@gmail.com

Q&A