investing in high impact big data solutions

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Investing in High Impact Big Data Solutions Evangelos Simoudis, Ph.D. Senior Managing Director [email protected] blog.tridentcap.com @esimoudis

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My keynote presentation on investing in big data application companies. The presentation was made in December at the Brand Innovators conference in NY. (http://www.brandinnovatorsbigdata.com/)

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Page 1: Investing in High Impact Big Data Solutions

Investing in High Impact Big Data Solutions

Evangelos  Simoudis,  Ph.D.  Senior  Managing  Director  

[email protected]  

blog.tridentcap.com  

@esimoudis  

Page 2: Investing in High Impact Big Data Solutions

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My Journey through the Data World

’80s

’90s

’00s

’10s

Page 3: Investing in High Impact Big Data Solutions

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Big Data is a Big Deal

By creating actionable insights from big data we can solve many important problems

Log files

Text

Weather, GPS

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While industries differ in their ability to obtain value from big data …

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… important Big Data Applications can be developed in many of them

§  Healthcare: Outcomes analysis, cost containment

§  Pharmaceutical: Customized drug treatments

§  Financial Services: Fraud detection

§  Transportation and Logistics: Fleet optimization for fuel efficiency

§  Travel: Channel management

§  Energy: Yield management

§  Automotive: Supply chain optimization

§  CPG: Real-time consumer understanding

§  Retail: Real-time marketing across devices and channels

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10 Steps for Working with Big Data

Step 1 • Defining the problem

Step 2 • Determine the data to use (private and public)

Step 3 •  Identify the data sources

Step 4 •  Integrate the data

Step 5 • Clean the data

Step 6 • Create information-rich data sets

Step 7 • Model/Analyze the data

Step 8 • Experiment/present results

Step 9 •  Identify actionable insights

Step 10 • Disseminate the results

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Solving Big Data problems involves more that data scientists

Problem

Data

Insights & Actions

Connector/ Translator

Patterns

Problem definition

Business user Data scientist 70% of work

30% of work

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While we are falling behind in training enough data scientists to meet our projected needs …

… we are falling even further behind in training business people with deep analytic skills

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We can ultimately lose the battle with the big data we are generating and collecting unless we can better leverage the expertise we are developing

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We are good at harnessing the basic ingredients

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Venture investments to date reflect this emphasis

Step 1 • Defining the problem

Step 2 • Determine the data to use (private and public)

Step 3 •  Identify the data sources

Step 4 •  Integrate the data

Step 5 • Clean the data

Step 6 • Create information-rich data sets

Step 7 • Model/Analyze the data

Step 8 • Experiment/present results

Step 9 •  Identify actionable insights

Step 10 • Disseminate the results

= amount invested = value derived

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New investments must be able to provide better leverage of Connectors and Data Scientists

Insights & Actions

Connector/ Translator

Business user

Data scientist

20% of work 30% of work

Insight generation system

50% of work

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For this reason Trident Capital has been investing in big data scalable, vertical applications that generate actionable insights

§  Healthcare: cost containment

§  Transportation and Logistics: Fleet optimization

§  Energy: Yield management

§  Multi-industry: multi-channel customer lifecycle management

Advocate

Convert

Nurture

Capture

Retain

Attract

Big Data

Analytics Mobile Vertical

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Summary

1.  Big data is a big deal because it can be used to address many important problems

2.  Current approaches aren’t scalable and take to long to actionable insights

3.  Venture investments in big data must shift to areas of higher impact and value

4.  Trident Capital has been investing in big data applications that provide faster path to value and high ROI