Analyzing Information Systems: Big Data Challenges and Support

This report provides an overview of big data, its characteristics, and the challenges associated with its analysis. It examines various techniques available for analyzing big data, including A/B testing, data mining, and machine learning. Furthermore, it explores how big data supports business organizations by enabling better decision-making, enhancing customer understanding, facilitating automation, and promoting cost-saving measures. The report concludes that big data plays a crucial role in helping organizations anticipate customer needs and make informed strategies based on market trends. Desklib offers a platform for students to access this and other solved assignments for their studies.

Information system
and big data analysis

Table of Contents
INTRODUCTION .............................................................................................................................3
Explain big data and characteristic of big data.........................................................................3
Critically examine challenges of the big data analytics, and other techniques that are presently
available to analysis big data. ..................................................................................................4
How big data support the business organisation?.....................................................................6
CONCLUSION .................................................................................................................................8
REFERENCES...................................................................................................................................9

INTRODUCTION
The Big data refers to that data which is being generated across the world wide at the
unprecedented rate. It is a accumulation of all tools and processes related to managing and utilize
large data sets. Concept of big data wad developed out of need to understand preferences, patterns
and trend in vast database generated when individuals interact with the each other and different
system. It is used in order to describe exponential availability and growth of data which can either
be in structured and unstructured formate. For large organisations, big data is become essential as
other technology such as internet and other etc (AlNuaimi, Khan and Ajmal, 2021). Big data can
be considered as structured and unstructured. This report will include the concept of big data and
its characteristic, challenges of the big data analytics and other techniques which are presently
available to examine the big data and explain how big data technology help the organisation.
Explain big data and characteristic of big data
Big data is refer to aggregation of the data that is vast in volume, yet growing
exponentially
with the time. Big data are large in size and complex that none of traditional data management tool
can store it and process it expeditiously. The big data can be delineated by some characteristics
which are mentioned below:
 Volume- It refers to a vat amount of the data generated every seconds. Size of the big data
is very enormous. It is a vast volume of the data generated from various sources daily such
as machines, networks, social media platforms, human interaction, business process and
many more. Its size play a crucial role to determine value out of the data. New w big data
tools use the distributed system so that individual become able to store and analyse the
data across database which are dotted around everywhere in world (Bell and et. al., 2021).
 Variety- It refer to different kinds of the big data. It is essential to manage the variety of
organisational data properly. Set of big data can contain several types of the data in same
unstructured database as traditional data management system mainly uses the structured
relational database which contain a specific data kinds with a set relationships to the other
data kinds. Big data approach frequently lead to more complete picture that how all factors
are related.

 Velocity- It refers to speed of the data's generation. It play essential role in comparison to
others. It create speed by which data is created in the real time. Big data velocity mainly
deals with speed at which the data flow from source s like application logs, business
process, social media sites, mobile device, sensors and many more. Flow of the data is
continuous and massive. Mostly big data platforms record and interpret the data in a real
time (Boissay and et. al., 2021).
 Value- It refers to benefits that a business derives from data. Does it will match the
organisational objectives? Does it help the business to enhance itself. It is a significant
characteristic of the bog data. It is reliable and valuable data that an organisation store
process and analyse. Big data's value ordinarily comes form pattern recognition and
insights discovery that lead to stronger customer relationship, effective operation and other
quantifiable or clear business benefits.
Critically examine challenges of the big data analytics, and other techniques that are presently
available to analysis big data.
The data is a valuable asset for every organisation. Big data and analytics are still in initial
stage of its growth, its importance can not be undervalued. With great opportunities and potential,
it come with great hurdles and challenges. That means organisation must be enable to resolve all
these concerned hurdles in order to unlock full potential of the big data analytics. When challenges
of big data analytics are address properly then success rate of implementing the big data solution
increases. There are various challenges of the big data analytics which are mentioned below:
 Big data talent gap- The big data is considered as a flourishing field and several experts
are acquirable in this field it is because the big data is very complex field and individual
who understand this complexity and the intricate nature of that filed are far few and
between. Its another big challenges in this field is talents gap which exists in the industry.
 Uncertainty of the data management landscape- As the bis data expanding
continuously, there are many new technologies and firms that are developing every day.
Big challenges for the business is to determine that which technology can work better for
them without any new problem and risk (De Santis and D’Onza, 2021).

 Long system response time- It is time consuming as it take a long time to examine data
even though input data is already available, and report needed now. Such type of delay can
cost pretty penny.
 Expensive maintenance- Big data system require an ongoing investment in its
infrastructure and maintenance. Every organisation wish to minimize such investment.
Therefore , even if an origination is happy with cost of the maintenance and infrastructure,
then it is a good idea for taking fresh look at their system and also ensure that they are not
overpaying.
 Complicated to use- It is very complicated to use big data analytics as it bring all efforts
invested in creating efficient solution to naught. When using the data analytics become
complicated, organisation may find it very difficult to extract the value to their data (Naqvi
and et. al., 2021).
Techniques which are presently available to analysis big data.
Data analytics is a process to examine the data sets and drawing a conclusion about an
information that they contain, commonly through a specific system methods and software.
technologies of data analytics are used on industrial scale and in all mercantile business industries.
There are different technique of data analytics which are currently available for analysing the big
data. These techniques are mentioned below:
 A/B testing- It is basic randomized control experiment. This technique of the data analysis
involve comparing a control group with variety of the test group to recognize what changes
or treatment will amend any given clinical variable. This optimisation technique frequently
used in order to understand that how altered variable impact audience and user
engagement. It is useful to understand satisfaction of the online features like new product
or feature.
 Data mining- It describe the process, which is undertaken by the organisation to study an
information for gaining insights in the customer's behaviour. It is a communal tool which
is used within the big data analytics, it combine methods fro the statistics and machine
learning, in data base management to extracts patterns from a large data sets. The data
scientist collect a large amount of the data and then study it, looking for discrepancies and
patterns to solve the problems ( Rawat and Samriya, 2021).

 Machine learning- As well known within field of the artificial intelligence, the machine
learning techniques is used for the data analysis. It work with the computer algorithms for
producing assumptions on the basis of data. It also provide predications which is not
possible for the human analysts. The machine learning algorithms are very useful to
collect, analyse and integrate data for a large organisations. It can be implemented in all
the component of big data operation such as segmentation and data labelling and scenario
simulation.
 Data fusion and data integration- In this, by combining set of the proficiency that
analyse and integrate available data from the multiple source and solution, insights are
very expeditious and more accurate than developed through sing source of the data (Riley,
Vrbka and Rowland, 2021).
How big data support the business organisation?
All the business organisation need a valuable data and insights. It help them to understand
customer's preferences and target audience. Using of the big data is become crucial for leading
business organisation to outperform any competition in the market. In many industries, the new
entrants and other established rivals uses the data driven strategies in order to capture, compete
and innovate. Big data support the business organisation in several way which are discussed
below:
 Making better business decision- The big data gives organisation the tool that they need
for making smarter business decision which are based on the data. For this, everyone in the
organisation must have access to data that they need for improving the decision making.
With speed of the data analytical technology system, paired with ability to analyse the
new sources of data, organisations are become able to examine an information
immediately and make astute decisions (Saura, Ribeiro-Soriano and Palacios-Marqués,
2021).
 Understanding customers- A business is very dependent on customers as not single
business can accomplish success without a good customer base. Big data play an
important role in understanding the valuable insights about company's target demographic
and preferences of customers. It allow the business organisation to understand the buying
decision of customers.

 Automation- The big data has potentiality to amend an internal operation and efficiencies
through the robotic process automation . A large amount of the real time data can be
instantly analysed and also built into a business processes for the automation process of
decision making. With the scaleable information technology infrastructure and declining
cloud computing costs, the automating data collection and their storage is within reach
(Sundarakani, Ajaykumar and Gunasekaran, 2021).
 Promote cost saving measures- Big data toll like Spark, Apache Hadoop etc. bring a cost
saving advantage for business when the store a large amount of the data. Though an initial
cost of deploying the big data analytics are every high, return and the gainful insights more
than pay for themselves. It also enable, better risk management, constant monitoring and
IT infrastructure personnel can be freed up (Tiwari and Rana, 2021).

CONCLUSION
From the preceding report it is find out that, big data has a crucial role as it aid the
organisation anticipated customer's needs. Right data are required to be properly analysed and
effectively presented. It is very large due to which it create many problems and challenges for the
organisation. The big data analytic is time consuming and its maintenance is very expensive.
There are different techniques such as A/B testing, machine learning, data mining and many more
which are available to analysis the big data. The big data is very helpful and useful for the
business organisation as it help them, to understand their customer and make enable them to take
better decision. Organisation uses big data to innovate new things and in their automation
process. Hence, it is essential for companies to use big data in order to understand the market
efficiently and make strategies on the basis of new market trend.

REFERENCES
Books and Journals
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Bell, D. and et. al., 2021. Exploring future challenges for big data in the humanitarian domain.
Journal of Business Research, 131, pp.453-468.
Boissay, F. and et. al., 2021. Big techs in finance: on the new nexus between data privacy and
competition. In The Palgrave Handbook of Technological Finance (pp. 855-875).
Palgrave Macmillan, Cham.
De Santis, F. and D’Onza, G., 2021. Big data and data analytics in auditing: in search of
legitimacy. Meditari Accountancy Research.
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data techniques and technologies. In The International Conference on Artificial
Intelligence and Computer Vision (pp. 838-853). Springer, Cham.
Rawat, B. and Samriya, J.K., 2021. A study on challenges of big data and their approaches in
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social IoT: Theorizing the challenges and directions in big data research. Big Data
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Sundarakani, B., Ajaykumar, A. and Gunasekaran, A., 2021. Big data driven supply chain design
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Tiwari, S.R. and Rana, K.K., 2021. Feature selection in big data: Trends and challenges. In Data
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