moneyball approach to big data
DESCRIPTION
Presented to Wall Street Technology Conference on opportunities with Big Data using a practical approach to creating a competitive advantage.TRANSCRIPT
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Moneyball Approachto Big DataCreate a competitive advantage with Big Data
Rick Kawamura@r_kawamura
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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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Moneyball – The Art of Winning
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Using a data-driven approach to outwit, outsmart, and outplay your competition with unstructured Big Data
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What is Big Data?
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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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Big Data Evolution
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EAI
SOA
Silos
Portals
Centralization
Vendor Consolidation
Consolidation App Explosion
Web
Globalization
SaaSMobile
Cloud
Social
B2B
Machine
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Big Opportunities
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Who is likely to reap the benefits of Big Data?
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Finance and Insurance are well positioned
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Predictive Analytics
• Is Social Media credible?
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Strong credibility of Unstructured, Social Data
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Improve Operating Margins
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“We estimate that a retailer embracing big data has the potential to increase its operating margin by more than 60%”
- McKinsey
- IBM
Integrating internal and external apps for profit
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Financial Services
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“… 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
Regulatory Compliance, Personalized Service, Competitive Advantage
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Top 10 Keys to Success starting out with Big Data
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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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Thank You@r_kawamura
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