This document discusses how big data can enable the travel and tourism industries. It defines big data as large datasets characterized by their volume, velocity, variety, and veracity. Big data comes from a variety of sources as people leave digital traces online and through mobile technologies. The benefits of big data for businesses include improved customer experience personalization, optimized marketing and products, predictive analytics, and risk management. The big data market is expected to double from 2014 to 2018. Future developments include improvements in data processing, centralized data repositories, and analytics solutions in the public cloud to reduce costs and security risks. Big data can deliver business insights, innovation, better customer relationships, and continuously improved experiences for the tourism industry.

1. 1
Identifying the New Frontier of Big Data as an
“enabler” for Travel & Tourism industries:
Reality, Future Trends and Insights
Mohsen HAMOUDIA
Bilbao – Spain 3-5 February 2016

2. 2
Summary
The opinions expressed in this presentation are of the sole author
responsability. They do not engage the International Institute of
Forecasters nor Orange Business Services
• The Digitalisation is changing the Behaviour
• The Big Data World
• The benefits of Big Data
• Perspectives and future developments

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• Cloud
• Mobility
• Big Data / Analytics
• Social Business
• Dedicated Industry
solutions
Digitalisation is changing the behaviour
Source: IDC, 2015

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What is Big Data ?
Big Data characterizes two aspects:
• the data itself, with particular features and they are usually considered as
“unstructured” and are thus difficult to handle and analyse.
The four Vs of big data :
• Volume: data generated are usually produced in large amounts
• Velocity: they are generated at a fast pace, in some cases all the time or
frequently
• Variety: generated data are usually of different format or type. It can be in
the form of text, video, picture, sound, website, …
• Veracity: truthfulness and accuracy of data. Databases should be
cleaned up frequently.
• the methods and techniques used to handle and analyse these particular
data. Specific “big data” techniques then have to be used. Most of these
techniques are actually an extension of traditional data mining solutions, even
if new technical bases such as Hadoop or MapReduce have also been
developed recently for big data only.

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Various kinds of data sources
Travellers leave different digital traces behind on the web and when using
mobile technologies. Through every traveller, big amounts of data are
available about anything that is relevant within the holiday stages: prior,
during and after.

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Mega, Giga, Tera, Peta,
Exa, Zetta, Yotta. Next!
• Much of all data arises as the by
product of our interactions with the
digital world ;
• but, increasingly, more innovation is
data-native, designed intentionally to
capture and deliver operational
metrics.
IBM has stated that in 2012 there were
2.5 exabytes of data generated every
day. That’s 2.5 billion gigs. About 75% of it
was coming from unstructured text, voice,
and video
EMC estimates that in 2013 there
were 4.4 zettabytes of data in the
“digital universe,” projected to
grow to 44 zettabytes by 2020.
IDC claims that the world’s data
doubles every year.

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Software
Data management
Processing tools
Natural language
Machine learning
Massively distributed
Linear scalability
Commodity hardware
Infrastructure
high computing
power
Storage
Servers
….
Services
Skills/Training
Consulting
Process
Management
BIG DATA
Large Datasets
The big data world
Unstructured (80-85%)
Continuously streaming information
Huge and diversified volume
(around 7 zettabytes in 2015)

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• A new generation of distributed processing tools and intelligent software
can handle the data issue
• Hadoop, an open-source software toolset based on the MapReduce
framework, is widely used
Unstructured Incomplete dataScatteredMultiple formats
Structured data
Converting unstructured data into structured data
Source:Markess,2015

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CMOs and CIOs are embracing and incorporating
Big Data usages in their business processes
France, 2014 - 220 decision Makers (O/W 31 CMO/CIO)
(in % of Decision Makers - Remaining = don’t know, no projects, no interested)
Source: From Markess Survey, CMO 2015

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The benefits of Big Data for Customer’s processes
• Survey conducted by Markess in 2015
• France, 2014 - 150 decisions makers (IT, Marketing, Com, HQ)
• (in % of decision makers, multi-responses)
Customer Experience Personalisation
Optimize the Marketing Product
Track Predictive Information (pre-targeting vs. retargeting )
Track Real-Time Analysis
Manage Risks (Churn, retention)
Have detailed analytic tools to managing the data
Source: Markess, 2015

11. 11 Source: IDC FutureScape: Worldwide IT Industry 2016 Predictions — Leading Digital Transformation to Scale
Study #259850 | Nov 2015 | by Frank Gens, IDC Worldwide IT Industry 2016 Predictions
Worldwide ICT Industry FutureScape
The size of the bubble indicates
complexity/cost to address.
Top 10 predictions in terms of their likely impact across the enterprise and the time it will take for the
predictions to reach mainstream, meaning the broad middle of the bell curve of adoption (i.e., the 40–60% of
enterprises that are neither the first movers and early adopters nor the last to act)
"Data Pipelines" in/out :
by 2018, Enterprises with
DX Strategies will expand
external data sources by at
least 3- to 5-fold and
delivery of Data to the
market by 100-fold or more

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• By end of 2017, more than 75% of ICT providers have identified applying
big data to business processes as one of their top two business
challenges.
• During this timeframe, ICT providers plan to allocate 16% of their total ICT
spend toward data management to address some of the challenges
associated with using big data across the business.
Source: OVUM, 2016 ICT Enterprise Insights in the Telecoms Industry. Key findings from the 2015/2016 survey results
Applying Big data to business process is key

13. 13
Software
Infrastructure
Services
Big Data Market will double over 2014-2018 period
Source: IDC, 2015
France

14. 14
Perspective and future developments (1/2)
Analysts (Idate-France, OVUM) have identified the following perspective and future
developments:
• Technical improvements will first help big data development, especially to
process data in real-time:
• The increase of the mean bandwidth will make data gathering easier and
faster, especially on mobile networks (LTE), which will allow a larger
volume of data to be exchanged between machines (images, videos, real-
time data…);
• The increase of storage and calculation capacity for servers and
computers will ease the potential analysis that can be done with big data
techniques;
• The evolution of mathematic algorithms at the research scale may
improve big data analysis process and techniques;
• Moreover, turnkey solutions will also be developed progressively, especially for
the processing and analysis of real-time generated data;
• The potential of Big Data will be able to provide various opportunities to gather
data from different devices belonging to a user (mobile phone, tablet, laptop,
connected TV).

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Perspective and future developments (2/2)
• Analytics and CRM should be more and more placed into the public cloud
which offers many benefits over private cloud environments:
- reduces the cost of storing large hardware
- cloud will significantly reduce total cost of ownership, as costs will be split
between multiple organizations.
- lower security risks for data generated for analytics use are also much lower
than they are for other systems
• Centralization of data should be before investing in analytics
- need to centralize data repositories before investing in analytics solutions
- to get the best ROI from analytics investments, it is important to catch the
complete customer story (including data from the networks, CRM, billing
systems, social media)
- then analytics solutions will be more effective and will provide more detailed
insight – offering better applications of the data across the business.

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How Big Data will impact Tourism Industry?
• Can deliver better and richer business insights
• Will help for innovation for tourism organisations thanks to new products
and services
• Will bring better customer relationships as a result of a good learning
about consumer preferences
• Can enable the use of information and insights to build connections with
individual travellers
• Will enable to offer travellers the right and expected services at the right
time
• Will help addressing increasing and various needs in order to still be
relevant for travellers
• Will allow tourism organisations to react instantly
• Can continuously improve the customer experience
• Will enable better decision support
• Will allow cheaper and faster data processing

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Thank you