1. The document discusses big data and the need to generate actionable insights from large amounts of data. It notes big data can help solve important problems in healthcare, transportation, energy and other industries. 2. Current methods for working with big data are not scalable and take too long to produce insights. More focus is needed on generating insights faster through applications that better leverage data scientists and domain experts. 3. Trident Capital has invested in big data solutions that produce quicker, higher-value insights for specific industries like healthcare, transportation, and energy. These more targeted industry applications provide a faster path to return on investment.

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

2. My Journey through the Data World
’80s
’00s
’90s
’10s
2

3. Big Data is a Big Deal
Log files
Text
Weather,
GPS
By creating actionable insights from big data we can
solve many important problems
3

4. While industries differ in their ability to obtain value
from big data …
4

5. … 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
5

6. 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
6

7. Solving Big Data problems involves more that data
scientists
Data
Connector/
Translator
Problem
definition
Insights & Actions
Business user
Problem
70% of work
Patterns
Data scientist
30% of work
7

8. 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
8

9. 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
9

10. We are good at harnessing the basic ingredients
10

11. 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
11

12. New investments must be able to provide better
leverage of Connectors and Data Scientists
Connector/
Translator
Insight generation
system
Data scientist
Insights
&
Actions
Business user
20% of work
50% of work
30% of work
12

13. 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
Mobile
Attract
Vertical
Capture
Analytics
Nurture
Convert
Big
Data
Retain
Advocate
13

14. 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
14