Presented to Wall Street Technology Conference on opportunities with Big Data using a practical approach to creating a competitive advantage.

1. Moneyball Approach
to Big Data
Create a competitive advantage with Big Data
Rick Kawamura
@r_kawamura

2. Agenda
• Moneyball – The art of Winning
• What is Big Data?
• Big Data Evolution
• Big Data Opportunities
• Not all Big Data is alike
• Big Data Examples
• Top 10 Keys to Success starting out with Big Data
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3. Moneyball – The Art of Winning
Using a data-driven approach to outwit, outsmart, and outplay your competition
with unstructured Big Data
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4. What is Big Data?
Forrester:
… techniques and technologies that make handling data at extreme
scale affordable… to understand how to get value from the 95%
you are not thinking about right now. (Forester estimates firms
utilize less than 5% of available data). In this information age, the
firms that best turn information to their advantage will dominate
their competition.
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5. Big Data Evolution
Cloud
Silos Mobile
SaaS
EAI
Portals Vendor Web B2B
SOA
Consolidation Social
Globalization
Centralization
Machine
Consolidation App Explosion
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6. Big Opportunities
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7. Who is likely to reap the benefits of Big Data?
Finance and Insurance are well positioned
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8. Predictive Analytics
Strong credibility of Unstructured, Social Data
• Is Social Media credible?
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9. Improve Operating Margins
Integrating internal and external apps for profit
“We estimate that a retailer embracing big data
has the potential to increase its operating margin
by more than 60%”
- McKinsey
- IBM
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10. Financial Services
Regulatory Compliance, Personalized Service, Competitive Advantage
“… unlocking the insights in the data to better understand
customers, competitors and employees represents a significant opportunity
to gain competitive advantage. … leading firms are looking at using both
internal and external data, both structured and unstructured, to develop
personalized banking products.”
- Deloitte
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11. Top 10 Keys to Success starting out with Big Data
1. Honest evaluation of your Big Data goals and weaknesses
2. Desire to change and think different
3. The 3 Vs of Big Data are important – but it’s really about a 4th “V”, Value
4. Gain access to the data and applications you need
5. Use relevant data – internal, external, structured, unstructured
6. Data in real-time
7. Ability to turn data into intelligence
8. Actionable results
9. Hire the right people (before investing in tools and technology)
10. Beware the hungry bear – You may not be first (with Big Data), just don’t be last
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12. Thank You
@r_kawamura
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