Information System and Big Data Analysis: A Comprehensive Overview

This report provides a comprehensive overview of big data, beginning with its definition and the distinction between structured and unstructured data. It delves into the key characteristics of big data: volume, variety, velocity, and variability, explaining their significance. The report then addresses the challenges of big data analytics, including data synchronization issues, a shortage of skilled professionals, data storage and quality concerns, and data security and privacy. It explores various techniques used in big data analytics, such as A/B testing, data fusion and integration, and data statistics. Furthermore, the report illustrates how big data technologies, like cloud-based analytics and Hadoop, support businesses by improving customer service, enabling cost advantages, and informing decision-making. Examples from various sectors, including government agencies, are provided to demonstrate the broad applicability and evolving nature of big data analytics in the current marketplace. The report concludes by emphasizing the potential of big data to drive social and economic advantages, highlighting the adoption of rapid technologies such as agile methods, machine learning, AI, Hadoop, and predictive analytics.

Information system and big data analysis
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Contents
INTRODUCTION...........................................................................................................................3
TASK...............................................................................................................................................3
Big data and its characteristics....................................................................................................3
Challenges of big data analytics and technique available in marketplace...................................4
How big data technology support business with example...........................................................7
CONCLUSION................................................................................................................................8
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TASK
Big data and its characteristics
Big data is based on the concept in which describe the large amount of data in the form of
both unstructured and structured manner. Big data can be analysed the insight view of
information and lead to make better decision in regards of strategic business plan. Nowadays,
there are many companies used the big data in their system to improve the overall performance
of business operations, provide the excellence customer services. Ultimately, it would be
increased the revenue of business profits. Companies that uses big data effectively in order to
hold the potential competitive advantage.
For Example- Big data provides valuable insight to the potential consumers who will attract
towards enterprise. In this way, it will help to increase customer engagement as well as
conversion rates (Ageed and et.al., 2021). On the other hand, big data is also used in the term of
medical researcher in which help to recognise the signs of diseases, risk factors and also help
doctors in term of illness or medical condition examination.
In 2005, Roger Mougalas from O’Reilly media which coined from big data technology. It
refers to the large amount of data sets, which is almost impossible to manage and process using
traditional business intelligence tool or platform. in 2005, it was created Hadoop as big data
technology by Yahoo!
Characteristics of Big data
Here are explained the different characteristics of big data technology as following:-
Volume- it is one of the characteristic of big data in order to represent the actual size. It is also
playing important role in identifying the value out of data or information in proper manner. In
case, if particular data can eventually be used in big data which means that depends on the huge
amount of information (Choi, Lee and Yoo, 2021). Hence, volume is the most commonly used
characteristics which needs to be consider when dealing with large amount of information. This
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is also another reason where different companies used the big data in order to manage and
control or record data in the organised manner.
Variety- it refers to the heterogeneous sources and nature of data or information. This can
be organised in the form of structured. At earlier days, companies are mainly used traditional
method such as spreadsheet, database. In order to store or collect the data in proper manner.
nowadays, organisations are used the big data concept in which store any kind of data such as
videos, emails, photos, audio, Pdf and monitoring devices. That’s why, it is to be considered one
of the characteristics of big data in which collect variety of information in different formats. This
is the best way to analyse the information and eliminate any kind of issue or problem at the time
of storage.
Velocity- it is another characteristic of big data in which maintain a velocity of data
generation. How fast the data or information is generated and processed. In order to meet all
essential need or requirement for clients, determine real potential in the form of data (Jin, Xing
and Wang, 2020). generally, A big data velocity deals with the actual speed at the time of data
flows in the form of various sources such as networks, social media, application logs and mobile
devices. Therefore, it become easier for organisation to maintain or control massive flow of data
in proper manner.
Variability- this kind of characteristic is basically referred to the inconsistency which can
be represented by data or information at single time. Thus, it is happening and able to manage or
handle information effectively.
Challenges of big data analytics and technique available in marketplace
In context of big data analytics, there are large amount of data or information producing in
every minute. Therefore, it is challenging to store, manage, analyse and utilise relevant
information in proper manner. In this way, many companies are struggling to find right path and
use data in business development. There are different challenges identified in big data analytics:-
Need for synchronization across disparate data sources- As data sets are basically
collecting large amount of data or information. There is a big challenge to incorporate them in
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the form of analytical platform. At that time, it may arise a problem while creating a gap and lead
a wrong message or insight. If in case, large amount of data are collected from multiple sources
so that it would be increased the possibility to damage the system of business. A lot of malicious
data stored in the form of message. Sometimes, it is very dangerous of business reputation and
image.
Shortage of professional’s and lack of knowledge related big data analytics- the analysis of
large amount of data is important to organise in the structured forms. But if a person does not
have a proper knowledge of analytical tool (Wu, Ao and Li, 2020). It is become consider as
challenging situation which is directly affecting on the entire business performance. Nowadays,
big data analytical has been created but having a lack of professionals who can handle it.
Another challenge faced in big data is shortage of people.
Getting voluminous data in big data platform- it is surprising that data is growing with
every days. It is simply indicate the business needs to handle large amount of data on regular
basis. Nowadays, there are variety of data and overwhelm any engineer. But it may be increased
the situation of overloaded which means that accessible data at single time.
Data Storage and Quality- It has been rapidly growing organisation and increases the large
amount of data produced. The storage of massive information is challenging aspect in context of
big data analytics. This kind of problem arise when using data lakes or warehouse to combine
unstructured or inconsistent data from multiple sources (Yang, Zheng and Chen, 2020).
Therefore, it encountered missing information, logic conflicts, inconsistent data and duplication
in data quality. These kind of challenges are mainly identified in the big data analytics.
Security & privacy of data- by using big data analytics, it can be discovered the
information or data, which bring them a variety of possibilities or opportunities. The potential
challenge identified in regards of privacy or security. The big data analytical tool for purpose of
storage and analysis, eventually it leads to high level of risk at the time of data exposure. It
making as vulnerable and increase voluminous amount of data in term of security and privacy.
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Big data techniques available in marketplace
Big data techniques and technologies are identified in the different areas such as
computer science, statistics and mathematics conceptual termed.
A/B testing – it is kind of data analysis technique which is mainly applicable in the big data tool
or platform. This will help to compare a group of data with performing variety of tests, in order
to change and improve quality of information. This is because every data should be stored into
different formats such as text, image, and video. Big data once again fits into the particular
model and achieve meaningful result or outcome.
Data Fusion and integration- it is also consider commonly used technique in big data
analytics which means that analyse large amount of data or information from different sources.
Afterwards, it will be identify the better solutions, insights are efficient and accurate way to
arrange the information (Yan, Wensi and Jiasong, 2020). Data fusion or integration is the
important aspect in which combined a data to hold relevant information. This type of technique
is basically used in the big data analytics tool or platform.
Data statistics- in big data analytics, it is collecting large amount of data or information,
organise and interpret in properly. This can possible due to conduct a proper survey or
experiments. On the other hand, big data analytical technique include predictive modelling,
network analysis and association. These are helping to manage, analyse and process information
in step by step manner. Different techniques or technology aside in the different forms and
arrange into predictable size.
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How big data technology support business with example
With the help of big data, the primary aim of organisation offers a better consumer service,
which help increase rate of profitability. In order to enhance the customer experience which
become consider as primary goal of every business. Nowadays, big data technologies are helping
enterprise to storage large amount of data or information. It enabling a significant cost advantage
or benefit.
Example of big data technology such as Cloud based analytics and Hadoop. These kind of
technologies are mainly used by retailer such as M&S. this will help to analyse the information
and improve decision making. Moreover, data breaches can tend to find the better security
options and resolve complex situation or condition in proper manner. In recently, big data has
performed the potential aspect in which bring social as well as economic advantage in term of
organisation development (Yang, Zheng and Chen, 2020). For example- government agencies
have already used big data analytics tool; in order to manage or control large amount of
information in proper manner. Afterwards, it has made up a policies and procedures. In this way,
it has been identified the importance of big data in different organisations.
Over years, big data analytics has evolved with adoption of rapid technology such as agile
method. This will help to increase the performance of organisation in context of data
management. Among with machine learning, AI, Hadoop and predictive analytics. These are
developing a latest trend in current marketplace.
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REFERENCES
Book and Journals
Ageed, Z.S. and et.al., 2021. Comprehensive survey of big data mining approaches in cloud
systems. Qubahan Academic Journal. 1(2). pp.29-38.
Choi, D., Lee, H. and Yoo, J., 2021. Design and implementation of an academic expert system
through big data analysis. The Journal of Supercomputing. pp.1-25.
Jin, L., Xing, M. and Wang, R., 2020, April. Operation Framework of the Command Information
System Based on Big Data Analysis. In 2020 IEEE 5th International Conference on
Cloud Computing and Big Data Analytics (ICCCBDA) (pp. 459-462). IEEE.
Wu, W., Ao, X. and Li, F., 2020, May. On curriculum relevance of the information management
and information system major in the age of big data. In Journal of Physics: Conference
Series (Vol. 1550, No. 3, p. 032147). IOP Publishing.
Yan, Z., Wensi, G. and Jiasong, S., 2020, December. Research on the Big Data Intelligent
Application. In Journal of Physics: Conference Series (Vol. 1693, No. 1, p. 012096). IOP
Publishing.
Yang, J., Zheng, B. and Chen, Z., 2020. Optimization of Tourism Information Analysis System
Based on Big Data Algorithm. Complexity. 2020.
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