1. Gaining competitive advantage through
Big Data assets and investments
A pragmatic approach on how to get started
to extract business value from Big Data footprint
netStar Partners
Capital & Business Breakthroughs
October, 2013 Slideshare 1 of 2

2. Content
2
 Introduction
 Do or die board questions about Big Data management
 What is Big Data? The 4V´s
 When & where is its value?
 The data
 The processes
 Big Data opportunities
 Some examples
 3 Potential approaches- Proposed approach

3. Introduction
3
 What executives think Big Data is?
Source :The Financial Brand | Big Data: Big Opportunity in Banking ... or Big B.S.?, Nov 2012 IBM I Survey Results
7% Data in
social media
10% Great
volumes of data 8% New
trendy buzz
word
15% Real time
info
13% Non
traditional
sources of data
16% New data,
new analysis
18% More
information

4. Introduction
4
 Big Data is the dynamic/mobile/interactive footprint of the technological
revolution that is changing customer behavior and competitive landscape

5. Introduction
5
 If you have think that the undergoing technological revolution is impacting or
may impact your business,……..
… Big Data management is a MUST!!!!
Data can tell youWhat!!
Managers have to decideWhy andWhat to do!!

6. Content
6
 Introduction
 Do or die board questions about Big Data management
 What is Big Data? The 4V´s
 When & where is its value?
 The data
 The processes
 Big Data opportunities
 Some examples
 3 Potential approaches- Proposed approach

7. Do or die board questions about Big Data management
7
1. How will Big Data change the basis of competition in our industry?
2. Does our business plan reflect the full potential of Big Data to improve our performance?
3. Is our portfolio of Data management initiatives aligned with the opportunities & threats?
4. What will it take to exceed our customer expectations using Big Data?
5. How will Big Data improve our operational & strategy agility?
6. Do we have the capabilities required to deliver value from Big Data opportunities?
7. Who is accountable for Big Data? & How we hold them to account?

8. Content
8
 Introduction
 Do or die board questions about Big Data management
 What is Big Data?The 4V´s
 When & where is its value?
 The data
 The processes
 Big Data opportunities
 Some examples
 3 Potential approaches- Proposed approach

9. What is Big Data? The 4 V´s
9
1. Volume
2. Variety
3. Velocity – Real time
4. Value
Vast amounts of varied,
fast-moving information
that can be processed and
analyzed to create
significant value for an
organization

10. Today
•Relevance, impact,
perspective
•Data availability
•Process of dealing
with the data
•Use of results-action
orientation
In the
future
• Future relevance,
impact, perspective
• Emerging critical data
• New processes and
tools
• New uses, interactive
and online uses of
results- Future action
orientation
The volume of data
matters
• Sampling vs all
• Multiple sources increase the
value
The variety of data
matters
• Many sources
• Structured &
unstructured
• Public vs proprietary
The velocity of data
matters
• Real time vs batch
What is Big Data? When & where is its value?
10
Company
value

11. In the future
ExternalInternal
Structured Un-Structured
DataTypes
DataSources
Mobile / GPS / GIS
Credit Info;Travel Info
Census; Real State DB
RFIDTags
Health profiles
Life events records
Presence reports
Twitter
G+; facebook; Foursquare;
Linkedin, ….Blogs,
External sensor data
IoT Interactions
Voice & media digitalization
….
Feeds in web
Online forums
Internal Social networks
Sharepoint Docs
Sensor Data
InternalVoice & media digital
…
What is Big Data? The data
11
TODAY
ExternalInternal
Structured Un-Structured
Data types
Datasources
Mobile / GPS
GIS
Credit Info
Travel History
Census & Public surveys
Real State Records
….
Twitter
G+; facebook; …
Linkedin, ….
Blogs
…..
HR files
Sales info
Commercial
transactions/Payments
CRM; ERP
Finance
Warehouse
…..
Web Feeds
Online company forums
Internal Social networks
Sharepoint
….
Source: IDCs Digital Universe Study, sponsored by EMC , June 2011. & netStar Partners analysis

12. What is Big Data? The processes
12
Clear
objectives
Outputs /
performance
Team / Talent
(Business
/Analytical/Techn)
Governance
Tools *
(Intelligent Sw and
models/Scale out
Infrastruc./Large DB)
Methodology -
Test & learn from
doing
Success comes from Action

13. What is Big Data? The processes
13
Intelligent software &
models
• Machine learning
• Natural languages processing
• A/B Testing
• Predictive modeling….
Large datasets
• Unstructured or semi
structured
• Continuously streaming
• information
• Volumes in the multiple
tera to peta bytes range
and beyond…
Scale out
infrastructure
• Massively distributed
• Linear scalability
• Commodity hardware
Source : At the Big Data Crossroads. Thomas H. Davenport. Amadeus 2013 . // & netStar Partners analysis
Other suitable technologies may
include:
• association rule learning,
• classification,
• cluster analysis,
• crowdsourcing,
• data fusion and integration,
• ensemble learning,
• genetic algorithms,
• neural networks,
• pattern recognition,
• anomaly detection,
• regression,
• sentiment analysis,
• signal processing,
• supervised and unsupervised
learning,
• simulation,
• time series analysis and
visualization.

14. Content
14
 Introduction
 Do or die board questions about Big Data management
 What is Big Data? The 4V´s
 When & where is its value?
 The data
 The processes
 Big Data opportunities
 Some examples
 3 Potential approaches- Proposed approach

15. 0 10 20 30 40 50 60 70
Other
Production performance
Client behavior analysis
Planning and predicting
Better cost analysis
Risk management
Market trends
Understanding business changes
Fraud detection
Churn management
Real time decision making
Capturing sales & marketing opps
Client segmentation
Clear business vision
Personalized marketing using social media trends
% of Positive answers
Big Data opportunities
15
 Areas for Big Data benefit
Source: Booz & Co Benefitting from Big Data 2012

16. Big Data opportunities. Some examples
16
Industry Some Big Data opportunities
Consumer goods &
retail Industry
• Sales trends accuracy- Accurate forecasting
• Pricings settings and personalized pricing offerings
• Store locations decisions
• Marketing at individual level
• Promotion effectiveness / Cross selling
• On time vouchers
Energy /Utilities • Smart meter data management
• Asset management and optimization
• Manage multisite generation networks
• In house/In building cross selling management
• Cross selling (gas/water/electricity)
• and promotional effectiveness
Financial services • Risk scoring management / Credit card fraud management
• Dynamic pricing
• Optimal ATM & branch locations
• Customized promos based on bank statements
• Data exchange models for SME clients
Insurance services • Claims fraud
• Reimbursement optimization
• Usage behavior: i.e. driving behavior, lifestyle impact on life cycle

17. Big Data Opportunities. Some examples
17
Industry Some Big Data Opportunities
Telecoms • Dynamic pricing
• Enterprise behavioral analysis
• Churn predictively and management actions (Using lifetime value analysis)
Smart cities • Flow learning's of people, vehicles and its interactions
• Real event impacts on city economy(Flows/expenditures/…)
• City new services developments based on info management
• Traffic predictive models (Based on events/weather/…)
Hospitality/Travel
sector
• New business models based in information aggregation, understanding and
learning by Big Data algorithms (i.e. Kayak, …)
• Hotel sites optimizations and franchise decision making
• Customer audience targeting for new travel experiences
• Advertising efficiency web ads (facebook services?/internal web services)
• Airline personal recognition services, services excellence and recovery
programs, and new offers that inspire and motivate
• Optimal pricing prediction in hospitality business. Revenue improvement
via cross selling hotel / restaurant/ services / tourism services
• New services definition in Hospitality business learning from customers
experiences outside he hotels. New cross selling offers within the chain
based in travelers internal and external to the hotel experiences

18. Content
18
 Introduction
 Do or die board questions about Big Data management
 What is Big Data? The 4V´s
 When & where is its value?
 The data
 The processes
 Big Data opportunities
 Some examples
 3 Potential approaches- Proposed approach

19. Confidential19
See document
netStar Partners Slideshare - How to get
started in get business value from Big Data 2
of 2 Oct 2013
In Slideshare
3 Potential approaches

20. Big Data
20
57% of Business leaders agreed strongly that most of their
competitors are using Big Data to their Strategic Advantage (1)
53% of large companies undertook a Big Data initiate
during 2012 – 43% of them predicted ROI greater than 25%- (2)
What about you?
(1) CapGemini Study over 600 Business leaders 2013
(2) Tata Consultancy Services (TCS) in a Global Study including 1217 Large Companies

21. ThanksJaime.nistal@netstarpartners.es
21
MANAGING DIRECTOR
Jaime Nistal
jaime.nistal@netstarpartners.es
Mobile: +34 629 25 61 62
netStar Partners
Capital & Business Breakthroughs