Information Systems & Big Data: Analysis of Applications & Challenges

This report provides a comprehensive overview of big data within the context of information systems. It begins by defining big data and outlining its key characteristics, including volume, value, variety, velocity, and veracity. The report then examines the challenges associated with big data analytics, such as difficulties in providing timely business solutions, inaccurate analytics, data complexity, system limitations, and high maintenance costs. Various techniques used in analyzing big data, including A/B testing, data fusion and integration, data mining, and machine learning, are also discussed. Furthermore, the report highlights the advantages of applying big data in business entities, such as focusing on targeted customers, cost-cutting, risk management, innovation, and improved efficiency. The conclusion emphasizes the importance of accurate insights and relevant sources for effective business development and customer relationship management.

Information system
And Big Data

Table of Contents
INTRODUCTION ..........................................................................................................................3
MAIN BODY...................................................................................................................................3
1.Explain what is big data and mention its characteristics..........................................................3
2. What are challenges faced in big data analytics and which techniques are used in analysing
big data. ......................................................................................................................................4
3. Advantage of application of big data in business entity. .......................................................5
CONCLUSION ...............................................................................................................................6
REFERENCES................................................................................................................................8

INTRODUCTION
Information system is technical organisational system implemented in an organisation to
organise operation and enhance capability. Big data is accumulation of wide variety range of
data, which is available in different forms. This data is too complex to be understood by normal
human intelligence (de Camargo Fiorini, and et al., 2018). In this report big data is examined
about its characteristics, challenges faced in application. Techniques used for applying in data in
the organisation, and how this data is advantageous for business operation is discussed.
MAIN BODY
1.Explain what is big data and mention its characteristics.
Big data as the name suggests is a huge collection data which includes wide variety range
of information. The extraction of this information is done through different sources, these are
available in different forms. This data set is too large and very complicated therefore different
techniques are used for data processing application. Current use of bid data is in forecasting,
trend analysis and understanding consumer behaviour. The data available is unorganised,
organised, different sizes, photos, videos, graphics and files.
Big data is being used since 1990s, it gathers semi structured, structured, unstructured however
main focus is unstructured data. Big data is massive need set of techniques and technologies
with new form of statistical tool and techniques (Jiang and et al., 2019).
Characteristics of big data
Big data accumulated from many sources available therefore there is mostly complex and
unstructured. There are five characteristics of this type data:
 Volume: The size of the data is huge and company uses this voluminous data for
analysing.
 Value: The most essential characteristic of the big data, it is this that determines the
efficiency of the insights gained from the data. The relatability and validity of the data is
play a important role. This ensures that efficient results are produced and strong
relationship is maintained.

 Variety: The heterogeneity and range of different data types, including unstructured data,
semi-structured data and raw data (Lv and et al., 2021).
 Velocity: The speed at which companies gets the amount of data , how it manges store
and manages the data. The data can be received in a particular period of time.
 Veracity: The accuracy and validity of the data determines the efficiency of the insights.
2. What are challenges faced in big data analytics and which techniques are used in analysing big
data.
Big data is very much used in today's business environment and provide innovative business
solutions. It is used for everyday challenges and bringing innovations and creativity in the
organisation. However it has its own setbacks that experienced when big data is applied. Below
are some of them mentioned:
 It is not successful in providing timely business solution- The information available is
though important and very useful but searching for the correct information consumes a
lot of time. In order to get the required insights data integration is performed,. Storage of
the data is also one of the major challenges that the organisation faces (Rao, and et al.,
2019).
 Inaccurate analytics- This one of the major setback the organisation, wrong analytics is
the worst a organisation can face. If the system is not proper and is unable to read the
data hence, it delivers inaccurate results. Since data is collected enormously quality of the
data decreases. The system sometimes omits important information due to human error.
 Complicated data is difficult to use- The level of complexity is more in the data therefore
it is difficult get information out the data. Some times system is over engineered therefore
the main focus often losses relevance. This also makes the results unclear and
unsatisfactory.
 Takes very complicated system, long response system- This system contains large files
which are in different forms. Therefore it requires technical analysis and complicated
study to read the data. Software is unable to no longer work with sufficient efficiency as
the limit is already reached.
 Maintenance of the system is expensive- day by day new technologies are coming up
therefore matching with current advanced technology is quiet expensive. Outdated
technology do not deliver required result hence updating the version is necessary and

costly. The resources are also not fully utilized if the technology is not up to date, even if
the system is not selected wisely it might also be harmful.
There are 6 techniques for using big data analytics
 A/B testing- It is a users experimental methodology, it is random testing method. In this
two variable are estimated and functions are performed. In this values are similar except
for one deviation which helps in understanding the behaviour. Two or more variables can
be used but it increases the complexity.
 Data fusion and data integration- In this method permutation and combination is used
for getting new insights. Various combination and relationships are discovered then an
estimation or prediction is made on the data. It is related to statistical functionating and
applications used in statistics.
 Data mining- This is most basic tool to build a strong relationship with customer. It helps
in finding out customer preferences and potential customer accordingly suggest methods
for customization and improvising the offering. Data mining uses machine learning for
different goals , it focus on finding out hidden prospectives.
 Machine learning- It is totally technical field , it takes data for improvising the
functioning. Machine learning uses algorithms and models to predict or forecast
something it is closely related to computational statistics which focuses on making
estimation based on computer applications.
Big data level and managed by services offered by IT vendors combines many of the techniques
and tools. Some of the reputed companies that offers platform for big data services are Amazon
EMR, Cloud era Data Platform, Google, HPE Ezmeral Data Fabric and Microsoft Azure
Hdinsight.
3. Advantage of application of big data in business entity.
Benefits of concept of big data is huge, this has become an essential requirement for
organisation who are looking for increasing efficiency. There is ample of opportunity available
with company when they use Big data. Data analytics provides success to the organisation
improves its customer relation and also other many benefits to the organisation. A business
whether big or small can benefit from the usage of this technique on good level if used properly.
This is because of the following reasons:

 It takes the focus of the business on targeted customer and potential audience- Big data
helps the business entity to produce customized product that the customer demands.
Business use big data to modify the data by serve consumer patterns. This goes long way
to ensure customer satisfaction, loyalty , trust which results in boost in sales.
 Focused attention helps in cost cutting and better communication- Big data give good
amount of information about the customer to organisation. This actually helps in
estimation who are the targeted audience and what they desire from the company. This
helps in making efforts for the promotion on that particular group of person. This reduces
overall sales cost and increases reach of the organisation (Wang and Wang, 2020).
 Risk management- Business function in high risk business environment, so they require a
system which detects risk beforehand. The tools in the system is capable of making
complex decisions and identify loss making events. Thus it is very advantageous system
when risk in the environment is high. Safeguarding the company form risk, looses,
potential threats and unexpected events.
 Provides scope for innovation- The insights achieved by analysing the big data helps to
find out new opportunities. This plays key role in bringing innovation and creativity in
the operations. Helps in formation of business strategises and provides first mover
advantage.
 Helps in application of complex data in the organisation- one of the most common and
basic advantage of big data tool is that provide crucial cost advantage for storing,
processing and analysing large volume data.
 Improve efficiency of the organisation- Data analytics can improve operational efficiency
by working on valuable feedbacks given by the customer. The tools can automate routine
process and tasks.
CONCLUSION
From the above report it can be concluded that big data that contains huge amount of
information. The information available is in structured and unstructured format, it can be
pictures, data, videos or document. It has its own disadvantages due to its complexity, variability
and format. It is important that insights gained is accurately acquired and from relevant sources.
This play a very important role in business development in improving overall efficiency. Big
data is also enables the company to provide customized product to the consumer according to

their preference. This all amount to build strong relationship with customer. Gain loyalty and
trust of the audience.

REFERENCES
Books and Journals
de Camargo Fiorini, P. and et al., 2018. Management theory and big data literature: From a
review to a research agenda. International Journal of Information Management, 43.
pp.112-129.
Jiang, D. and et al., 2019. Big data analysis based network behavior insight of cellular networks
for industry 4.0 applications. IEEE Transactions on Industrial Informatics, 16(2).
pp.1310-1320.
Lv, Z. and et al., 2021. Analysis of using blockchain to protect the privacy of drone big
data. IEEE network, 35(1). pp.44-49.
Rao, T.R. And et al., 2019. The big data system, components, tools, and technologies: a
survey. Knowledge and Information Systems, 60(3). pp.1165-1245.
Wang, S. and Wang, H., 2020. Big data for small and medium-sized enterprises (SME): A
knowledge management model. Journal of Knowledge Management, 24(4). pp.881-
897.