Big Data Analytics in Aviation Emirates Airlines

This report examines the characteristics and importance of big data analytics globally and how it affects Aviation Emirates Airlines. It explores the opportunities and challenges faced by the airline industry due to big data analytics. The report also relates the value chain and/or virtual value chain to evaluate how value is created and delivered in the business by big data analytics.

Information Systems

Table of Contents
INTRODUCTION ..........................................................................................................................3
TASK 1 ...........................................................................................................................................3
Examine and calculate the characteristics and importance of big data globally........................3
TASK 2............................................................................................................................................5
Examining the industrial opportunities and problems caused to Aviation Emirates Airlines by
big data analytics.........................................................................................................................5
TASK 3............................................................................................................................................8
Relate the value chain and/or virtual value chain to evaluate that how value is created and
being delivered in your business by big data analytics...............................................................8
CONCLUSION .............................................................................................................................10
REFERENCES..............................................................................................................................11

INTRODUCTION
Big data analytics is the application of the latest and progressive analytic methodologies
in an opposition to very huge, distinctive data sets or groups that comprises of organized, semi
organized and unorganized data, from divergent sources, and in non-identical sizes varying from
terabytes to zettabytes (Du, Liu, and Lu, 2021). Aviation Emirates Airlines is the largest
airline in the Middle East which was founded in the year March, 1985. It is the world's fourth
and second largest airline in terms of organised revenue passenger kilometers flown and freight
tonne kilometers flown respectively. In the following report, identification and evaluation of
features and importance of big data analytics in the global market has been included.
Opportunities and challenges faced by the Aviation emirates Airlines by the usage of big data
analytics has also been considered. This consists of the technique of value chain and virtual value
chain.
TASK 1
Examine and calculate the characteristics and importance of big data globally.
Characteristics of Big data Globally
 Volume: The name Big data is itself related to a size which means huge or enormous.
Size of data plays a very crucial role in determining the value of data. Also, a specific
data can also be considered as a Big data or not, is totally dependent upon the volume of
the data. Therefore, Volume is that one characteristic which needs to be in mind while
dealing with big data solutions. Big data is basically related with the information
provided from the various sources like machines, social media platforms, networks and
interaction with the humans. The volume of the data is measured in the yottabytes (YB),
zettabytes (ZB) and gigabytes (GB). In accordance with trends in the industries globally,
the volume of the data will significantly take a high jump in terms of growth in the
coming years (Jiang, Huo, and Song, 2018).
 Variety: Variety refers to the heterogenous sources and the quality of data,both
structured or unstructured are included. During earlier days, databases and spreadsheets
were the only sources of data considered by most of the applications. Nowadays, photos,
videos, emails and audio are also considered in the analysis of the applications. It is one

of the major issues which is faced by the industries globally as it can directly impact the
performance of the businesses.
 Velocity: The term refers to the generation of speed of the data how fast a data can be
generated or processed to meet the demands and determines the potential of the data.
Velocity stands to the speed of the processing of the data. For the better performance of
the process of the big data high velocity is the key element for getting better results. It
basically consists of the activity bursts, rate of change and linking of the income sets of
the data (Kobusińska, and et.al., 2018).
 Variability: This refers to the inconsistency which can be shown by the data in some
cases,therefore hampering the process of being able to handle and management of data
efficiently. It refers to few different things in context with the big data. One of the major
reasons in data is the number of the inconsistencies. It can be found by various
inconsistent and exceptional methods in order for the fulfilment of the meaningful
analytics.
 Veracity: It stands to present that how much data is accurate and dependable. There are
many ways to get a clean, clear and interpretation of the data. It is a process of handling
the data and management of the data effectively and efficiently. Big data is also
necessary to provide the information for the development of the businesses in the global
market.
Significance of Big Data
 Cost Savings: Many tools like spark, Apache hadoop are some kinds of cost saving
benefits to the businesses when they have to accumulate a large amount of data. These
type of tools help the businesses in relating more efficient ways of doing the business.
 Time Saving: It helps the companies to collect the data from various sources around the
globe. It helps them to examine the data as fast as possible which after all helps in
making the decisions very quickly on the basis of learnings (Liu, Yang, and Sun, 2020) .
 Understanding the conditions of the market: It helps a business to get the better
understanding of the situations in the market. For the expansion of the growth of the
business it is very much necessary to have a clear evaluation of the conditions in the
market.

 Social Media Listening: Businesses can perform very much better on the basis of the
views and sentiment analysis using the big data tools. These help to authorized them to
get the suggestions of the companies that what people think about the business and their
opinion on the plan of expanding the business (Mazanec, 2020).
 Solve the problems of the advertisers and offering them the insights of the market:
Big data helps to analyse the business properly and the operations in the business. It
allows the companies to manage the needs of the customer and the expectations of the
customer.
 Driver of the innovations and development of the product: It makes the businesses
capable to initiate with the ongoing ideas in the market and makes them to innovate for
the development of the new product and redeveloping their existing products. It generally
refers to all the stages which are included in the upbringing of a product by the idea of
releasing in the market.
TASK 2
Examining the industrial opportunities and problems caused to Aviation Emirates Airlines by big
data analytics
Opportunities arise in Aviation Emirates Airlines due to using big data analytics
The ideal advantage of big data analytics comprises of well-timed feedback to the market
demands prevailing in the current period and future period, upgrades planning and lining up
decisions in a well organized manner along with transparent understanding and observing and
examining of all principal performance factors related to the airline industry. When adequately
used the good and positive results of the above mentioned advantages embrace the lower cost of
operation, upgradation in consumer service, competitive market and growth in profit margin and
stockholder value (Nie, and et.al., 2020).
 Boost in airlines revenue: it aid the aviation industry in understanding choices and
preferences of its customers or clients and also helps in maintenance of other problems.
For example, examination of ticket booking assist the industry in targeting the customers
having specific demands while taking care of the revenue of the organisation. The factor
of revenue management should be considered seriously as it is based on the idea that

different customers have different approaches towards the product. Therefore their
paying capacity depends on the time of purchase and the group to which they belongs.
Furthermore, revenue management mainly focuses on making proper ad adequate
utilisation of artificial intelligence in order to determine the destinations and specific
prices fo that destination, to search and reach efficient and effective distribution channels
and management of seats in order to prevent the competitiveness of the airlines and make
it according to the needs of the consumer (Pramanik, and et.al., 2020) .
 Reduction in cost: Due to the entrance of the big data analytics in aviation sector, there is
a reduction of cost in terms of loss of baggage. Initially, the damages caused due to the
loss of the baggage were borne by the organisation but after the introduction of big data
technology there is a reduction in the loss, damage and delaying of bags. Moreover, in
case of consumption of fuel, the data is obtained and examined n such a way that the
collected data will results in achieving a upgraded level of fuel utilisation efficiency.
Artificial Intelligence applications assist airlines in learning built-in machine theorems to
gather and examine data of the flight related to the distance of the route and heights, type
and mass of the aircraft, climate, etc. Based on these informations, the system evaluates
the required amount of fuel needed for a flight.
 Satisfaction of customers: The aviation industry keeps the updated record of its clients,
while promoting specific offers which are based on the preferences, choices, needs ,
habits and specific experiences. By gathering and consuming data of their clients, airlines
industry interprets tastes, preferences and choices of their passengers in order to provide
them better transportation facilities and options on which they are ready to spend their
earnings (Rezaee, and Wang, 2018).
 Digital modification: With an intention to provide better and upgraded services to its
clients, the big data analytics assist in providing a better and appropriate policy for the
customized mechanised supplier to display their trade good and services to airlines and
airports in order to provide the passengers a more attached travelling experience.
 Risk management: It has been experienced from the past years that this organisation has
ben majorly effected. Due to this reason it has become very important for the industry to
develop a number models of risk management and strategies for risk management in
order to secure themselves from obstructive effects of these events. In such a situation big

data analytics acts as a saviour for the industry. Some of the issues has been resolved like
the danger due to continues change in time zones, longer time of duty days, etc. The main
focus is to make available the data to the schedulers which is reliable and helps in
reducing risk (Samara, Magnisalis, and Peristeras, 2020).
 Control and authentication: This industry needs a huge number of control and verification
methods that are able to manage costs which arises from a variety of operation activities.
In a relation to alter this, airlines have an urgent requirement for a complete and integrated
repository of flight information data which is collected from its distinct units of business. This
will help in calculation of efficiency of various analytics like comparison of actual fuel utilised
and planed fuel usage per flight and crew usage. This problem can also be addressed by
combining and examining related flight data. Hence, the establishment of the 360 degree view of
the aircraft will help the airlines in sufficiently upgrading and altering their systems of control
and verification.
Challenges faced by Aviation sector by using big data analytics
 Operating the flow of Data Volume: From many years, the aviation sector is flooded with
data by the usage of big data techniques. It was estimated that on the busiest day, i.e., on
July 25,2019 a huge and diverse quantity of worthy data has been produced by each flight
and there were 230,000 flights in total. It can observed from the past estimation that in
the future generation of aircrafts each flight will produce minimum five and maximum
eight terabytes of data. This estimation of the future is already 80 times larger than the
aircrafts moving in the air in the present time (Wang, and Alexander, 2020). This is the
reason behind the aviation industry analysts expectations that the annual data production
will reach upto 98 million terabytes by the year 2026.
 Regulating varied Data types, formats and frameworks: Only the availability of data
varieties, types, forms and structures does not relates to the safe environment of a flight.
The availability of the generated data depends on the climatic conditions, air traffic,
speed of the aircraft, consumption of the fuel by the aircraft, performance of the engine,
real-time sensors, radars for navigation and weather forecast and many more. All the
varieties of available data types, forms and structures and considered with a view of
safety, success and profitability of operations of flight. Operators of flights and its pilots
are required to approach to the available data as early as possible due to many reasons.

The initial step that should be taking is the decision making in the industry. But if the
decision making procedures takes a longer period of time in acquiring and utilisation of
the significant data, then the working must be done with the availability of correct t and
appropriate information (Wang, and et.al., 2019).
 Examination and utilisation of data instantly: It is the major problem or challenge faced
by the operators of the flights and its pilots, they are required to utilise data but are not
able to do so because the processing of data stuck. Ignoring initialisation and
transformation of data is difficult because they impacts completeness of delivery on time
and correctness which inturn results in the loss of the data. Processing data in advance
and converting it also produce ancillary data groups and sets which combines the
problems of managing greater data quantity. In order to study and utilise data in the given
time, the organisation requires technologies that mechanically combine and assist a large
number of essential types of data, formats of data and data structures in the given time. It
is also important for aviation sector to have technologies that are particularly developed
for this sector.
TASK 3
Relate the value chain and/or virtual value chain to evaluate that how value is created and being
delivered in your business by big data analytics.
In the field, business management, value chain is used as a tool which helps in decision
for making the model of the chain of the activities held in the business to provide or to deliver a
valuable product or services in the market. The value chain have a certain categories of the
generic value activities in a business to give them the permission to optimised and understood.
1. Data Acquisition:It is a process of filtering,gathering and and cleaning of the data before
putting it into the data warehouse or any other storage place on which the process of the
analysis of the data can be executed. It is one of the most important challenges in the
terms of requirements of the infrastructure (Xie, Qian, and Wang, 2021). The required
infrastructure helps in the supporting of the acquisition of the big data and it must be
delivered on low scale. Latency should be very much foreseen in capturing the data in
execution of the queries. Artificial intelligence is a utilisation to assist airlines in

understanding to built-in machine methods to gather and analyse data of the flight linked
to the distance of the route and heights, type and mass of the aircraft, climate, etc. Based
on these such kind of information, the system calculates the required amount of fuel
needed for a flight.
2. Data Analysis: It is concerned with the execution of the data which is raw and to obtain
flexible decision making ability as well as domain specific usage. It involves
transforming, exploring and handling of the data with the target to highlight the data
which is relevant,combined and extraction of the hidden information with the high
growth potential on the point of doing the business (Xu, and et.al., 2019). Aspects which
are related to it are mining of the data, business intelligence and learning of the machines.
The aim of data analytics in aviation is to analyse the wide amount of data which is
obtained daily and to provide meaningful information to airlines, airports and
stakeholders so that it can improve the operation and to execute any related products and
services.
3. Data curation:It is the management of the data actively for the life-cycle to make sure
that the required quality of the data for the better and its efficient usage. It is a process
which can be categorised into different types of operations such as creation of the
content,validation, classification, transformation, validation and selection. It is performed
by the group of experts who are responsible for improving the quality and availability of
the data. The Data curators has the responsivity to make sure that the data should be
accurate, accessible and trustworthy and should fulfil the requirements of the experts. The
key role of the curation of the big data uses a community and sourcing of the crowd
which approaches. Emirates can use the data for better analysis of the conditions in the
market to improve the travelling experience of the passengers in terms of luxury,
technology and budget (Zhang, and et.al., 2020).
4. Data storage:It is the preservance and data management in particular scalable way that
fulfils the requirements of the applications which require the fast access of the data.
Relational database management (RDBMS) has always been the main and the most
distinctive which is providing the solution to the paradigm from past 40 years. Moreover,
the ACID(atomicity, consistency,isolation and durability) are the some properties that a
database grantees so that there should be no lack of flexibility in the transactions and the

production of fault tolerance when the volumes of data increases and the complexity to
grow which make them inappropriate for the situations in the big data. Emirates airlines
can designed with the expansion of the goal in mind and to represent a broader aspects of
the solutions which is based on different models of the data so that it can expand the
business more efficiently and effectively.
5. Data Usage: It protect the data which is driven with the business activities and the need
of the access the data, and evaluate the tools which are needed for the merging of the data
analysis within the activities in the business. Data usage of the emirates can help in the
decision making of the business which can increase the chances of expansion by reducing
the costs, increase in the value added or any of the other aspect that can be use to analysis
against the performance of the the business (Zhang, and et.al., 2021).
6. Digital Modification: With an intention to provide a better and upgrading services to its
clients, big data analysts assist in providing a better and appropriate policy for the
customised and mechanised supplier to show their goods and services to airlines and
airports in order to provide the passengers a more enhanced and comfortable way of
travelling.
CONCLUSION
In the above prepared report of Aviation Emirates Airlines, the features and importance
of big data analytics in the global market have been recognized and evaluated. The report also
conclude the opportunities or benefits arise like increase in revenue of the industry, control and
verification process, management of risk factors, digital transformation and satisfaction of clients
and challenges such as operating the flow of data, examining and utilising data as a speed of now
and regulation of different types of data, data forms and structures. Value chain technique in
order to analyse the value creation has also concluded.

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