Information Systems: Big Data Analysis, Challenges and Techniques

This report provides a detailed overview of information systems and big data analysis, highlighting the characteristics of big data such as variety, velocity, value, volume, veracity, and variability. It addresses the challenges organizations face when implementing big data analytics, including expensive maintenance, complicated data structures, inaccurate analytics, and long system response times. The report also explores available techniques for big data analysis, such as association rule learning, machine learning, and social network analysis. Furthermore, it examines how big data technology supports business by increasing market intelligence, improving customer insight, enabling agile supply chain management, providing smarter recommendations and audience targeting, and driving data-driven innovation, ultimately concluding that information systems and big data analysis are critical for the smooth operation and strategic direction of an organization.

Information Systems
and Big Data Analysis

Table of Contents
INTRODUCTION...........................................................................................................................1
TASK...............................................................................................................................................1
What big data is and the characteristics of big data? .............................................................1
The challenges of big data analytics; and the techniques that are currently available to
analysis big data..........................................................................................................................2
How Big Data technology could support business, please use examples wherever necessary.
.....................................................................................................................................................3
CONCLUSION................................................................................................................................4
REFERENCES................................................................................................................................5

INTRODUCTION
Information systems is the bundle of integrated components that works in collecting
information, storing the data and processing the information and data in respect to generate
relevant information and providing knowledge. Whereas big data is the terms that describes as
the large volume data which comprises structured data, unstructured data and semi-structured
that includes in day to data activities in the business. Big data analysis is the thriving method
which is used in range of data sets(Choi, Wallace and Wang, 2018) . The aim of this report is to
highlight the basic characteristics of the big data with the challenges that occur while using or
implementing big data analysis. It also covers the methods that are available in order to
evaluating big data and how its supports business.
TASK
What big data is and the characteristics of big data?
Big data is describes as the data sets that comprises wide range of data in sets and are available
in different forms. Big data extract the information and implement that information for the
benefit of the organisation. This can be used by wide range of companies in respect to process
the data and mine the information and data. Big data has the different characteristic which helps
in provide detail knowledge about the big data(Dartmann, Song and Schmeink, 2019) . Some of
the characteristic of the big data ar mention below:
 Variability- This characterise of the big data checks how fast an frequent the data
changes and how does shaping of the information helps the organisation. This includes
managing and detail analysation of data.
 Veracity- It checks the authenticity of the data as it shows the quality as well as the origin
of the data. The information which is generated is relevant or not and how to deal with
the information comprises in veracity.
 Value- This is defines as want value which is generated from the data and how big data
generate better results from the data which is stored.
 Volume- It is the common feature of the big data that maintain the link between size and
the processing capacity. This aspect frequently changes as data collection increases
constantly.
1

 Velocity- It is describes as the measurement of the current value of data because big data
constantly changes. In order to take advantage of data and information it is necessary to
process structured and unstructured data quickly as possible.
 Variety- It refers to the wide range of the data that is being stored in the big data which
can be further processed and analysed. New data can be generated from different
platforms and then it stored in a structured form.
The challenges of big data analytics; and the techniques that are currently available to
analysis big data
There are multiple challenges that an organisation faces in the process of implementing big
data analytics which are mention below:
 Expensive maintenance- In the current scenario it is important to implement the updated
technology in the organisation in order to stand in the market and earn appropriate
profit(Ghasemaghaei, 2020) . Using outdated technology not generate effective output
and implementing innovative techniques generate more expense to the company.
 Complicated structure of data analytics- Another challenge in using big data analytics its
complicated structure. As many company are not capable of using it properly and finds it
difficult to mine data from sets of data. This issue occur because of unclear data
visualization and due to over engineered systems.
 Inaccurate analytics- If an organisation is using big data in each and every aspect of it
then they are relying on the big data completely in respect to manage the information. It
may results error in the information and defects in the knowledge systems (Hopkins and
Hawking, 2018). Inaccurate data also results in mismanagement in the information which
can be seen in the profitability structure of the organisation.
 Long system response time- In some situation it is being analysed that it takes too much
time than needed which is proven critical for batch processing. Taking longer than
expected time results in delay in working structure.
There are multiple techniques that are available in the big data analyses, some of the techniques
are mention below:
 Association rule learning- It is the procedures that determines the relation between
various variables and huge data sets. It provides help greatly in placing goods in better
2

proximity, helps in extracting data about the site visitors in the websites and checks the
systems and identify malicious activity.
 Machine learning- This comprises software that learn from the data sets. It generates the
ability learns from the systems(Novak, Bennett and Kliestik, 2021) . It is an essential
process because learning what user is expecting and make recommendations based on
that information proves to be very useful in organisation. It also attract more and more
customers in the organisation.
 Social network analysis- It is the method which can be implement in telecommunication
industry, it is also apply by sociologist in respect to study interpersonal relationships.
This network analysis used in generating different social social structure for building
customer base and for evaluating ties to link with individuals.
How Big Data technology could support business, please use examples wherever
necessary.
Big data is the set of data that allows the various business organisation to manage its
customers. It provides the ways through which organisation can make conversation or engage
with the customers in the real time. It handles types of data and make in-depth analysis in order
to generate information which is very important for the organisation. In provides benefits to the
businesses in multiple ways, some of the advantages are mention below:
 Increased market intelligence- Through the analysis on the big data it is analysed that big
data evaluates the complex behaviour of the customers in detail and also generate
understanding ODF the marketplace with its changing dynamics (Papadopoulos and
Balta, 2022). By the evaluation of the different aspects provides helps to the companies
in the development and innovation in products and assist modern market intelligence.
 Better customer insight- Big data helps in understanding its customers and their
requirements and provides them huge range to choose from. It generates information by
the internal and external surveys, external sources of the organisation and by the social
media activity.
 Agile supply chain management- Big data provides major help in integrating data in
accordance to the customer needs and trends through various e-commerce sites, through
supplier’s data and by retail application. It helps in evaluating the real time processing of
the products and the services which influences the supply chain efficiently and
3

effectively. For instance- Big data monitors and give information and knowledge about
the supply chain of the organisations, which provides the help in making tasks effective
and faster.
 Smarter recommendations and audience targeting- Big data collects information and
knowledge from different sources and implement it in the organisation strategies. It
greatly helps in targeting potential buyers. For example- If a buyer wants to purchase
some dress and they are searching it online, then big data automatically evaluate that
information and apply it in making change in company.
 Data driven innovation- There are multiple tools and the technology of the big data that
is available in the market in respect to make enhancement in the products and services. It
generates the data that provide information about the changes with that it gives the
understanding about how to make innovation in different products.
CONCLUSION
From the above report it is concluded that information system and big data analysis are the
aspects in the business which gives direction to the working structure of the organisation. It helps
majorly in running organisation smoothly. This report covers many aspects about the big data
analytics. This report evaluates and defines the characteristic of the big data which comprises
4

variety, velocity, value, volume, veracity and variability. Volume includes the size and amount
of data that is manages by the big data in order to make analysation. Whereas variety includes
types of data that can be help in generating information. Adding to that it provides the challenges
that an organisation can face in order to implement the big data in the organisation. Further it
provides the how big data supports the organisation or makes the company's work effective. The
benefits comprise Agile supply chain management, Better customer insight, Increased market
intelligence, Smarter recommendations and audience targeting and Data driven innovation.
5

REFERENCES
Books and Journals
Choi, T.M., Wallace, S.W. and Wang, Y., 2018. Big data analytics in operations
management. Production and Operations Management, 27(10), pp.1868-1883.
Dartmann, G., Song, H. and Schmeink, A. eds., 2019. Big data analytics for cyber-physical
systems: machine learning for the internet of things. Elsevier.
Ghasemaghaei, M., 2020. The role of positive and negative valence factors on the impact of
bigness of data on big data analytics usage. International Journal of Information
Management, 50, pp.395-404.
Hopkins, J. and Hawking, P., 2018. Big Data Analytics and IoT in logistics: a case study. The
International Journal of Logistics Management.
Novak, A., Bennett, D. and Kliestik, T., 2021. Product Decision-Making Information Systems,
Real-Time Sensor Networks, and Artificial Intelligencedriven Big Data Analytics in Sustainable
Industry 4.0. Economics, Management & Financial Markets, 16(2).
Papadopoulos, T. and Balta, M.E., 2022. Climate Change and big data analytics: Challenges and
opportunities. International Journal of Information Management, 63, p.102448.
6