Analyzing Big Data: Information Systems, Business Support & Challenges

This report provides a comprehensive overview of big data, including its definition, characteristics (volume, variety, velocity, veracity, and value), and the challenges associated with its analysis, such as the talent gap and the need for data synchronization. It also discusses techniques like machine learning and Apache Hadoop used for big data analysis. Furthermore, the report highlights how big data technology supports businesses by enabling dialogue with consumers, facilitating product redevelopment, and enhancing data safety. Examples, such as Mark and Spencer's use of big data for customer engagement and Tesco's application for optimizing production processes and safeguarding sensitive information, are provided to illustrate the practical applications of big data in enhancing business operations and decision-making. The report concludes by emphasizing the importance of embracing big data and continuously improving its uses to reach its full potential.

Information Systems
and Big Data Analysis

Table of Contents
INTRODUCTION...........................................................................................................................1
What big data is & characteristics of the big data? ....................................................................1
Challenges of big data analytics & techniques that are currently available to analysis the big
data .............................................................................................................................................2
How Big Data technology could support business, please use examples wherever necessary...3
CONCLUSION................................................................................................................................5
References:.......................................................................................................................................6

INTRODUCTION
Almost everything people do produce data. Smart watch and smart phones constantly
track the individual's daily activities. Even cars are also tracking the way how people drive it,
where driving to, what they listen during driving and in few cars can determine causes of any
accidents (Bhardwaj and Agarwal, 2022). As per the Edward Snowden of Prism Document,
individuals are being exposed to same amount of the information on daily basis as 15th century
ancestors were exposed to in their entire lifetime. It is has been analysed that big data lead to a
substantial breakthrough, nevertheless, individuals need to proceed with the caution as this ocean
of the data contain a very terrifying complete story of humans such as where they travel, what
they purchase and where they live. Therefore, this report is going to cover concept of the big
data, different characteristics of big data, challenges related to the big data analytics and
significance of the big data technology in the success of a business.
What big data is & characteristics of the big data?
Big data is defined as a process of delivering the decision making insights. Process uses
individuals & technology to quickly examine huge amount of the data of various kind (traditional
table- unstructured data & structured data, such as video, email, social media, picture and
transaction data) from a variety of the source for producing a stream of an actionable knowledge.
Characteristics of the big data
 volume- It is first dimension of the big data that deal with quantity of the data &
frequently thought of as a definition of the big data. Volume of the data to be examined is
genuinely massive. This size is frequently measured in zettabytes & petabytes. It has
been identified that approximately 2.5quintillion bytes of the data are created on regular
basis. This large amount of the data that is generated all the time used to be created by the
employees, but nowadays it’s created by the humans (employees & users), networks
(internet networks), machines (computers) and systems
 Variety- This term is used to describe the increasingly diversified kinds of the data. These
different sources related to data need to be examined & managed (Hassna, 2022). The
Data used to be stored in spreadsheets and databases (structured data), but now humans
obtain more data via audio, photos, video, emails and other etc. These multiple and
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complex data forms require an integration. In present time, around 90% of the real-time
data created consists of the unstructured data.
 Velocity- It is defined as consumption and rate at which the data flows from various kind
of the data sources like network, social media, business process and machines. ICU
within flagship hospital is an example of the big data velocity. Big data analytics are
constantly streaming the data in order to predict the infections inpatients with the
collapsed lungs. It provides an admonitory that will be seen by the nurses or physicians &
they can instantly take the action based on changing conditions of infection & can save
their patients’ lives
 Veracity- It refers to data trustworthiness. It considers accuracy and quality of significant
data, the source or provenance of data & intended usage thereof. Because of volume
increase of the data generated in a diverse form, uncertainty connected with the data need
to be managed efficiently (Patel and Shah, 2022).
 Value- It is another dimension of the big data that is not always acknowledge by the
technologist, but gaining the insight needs that can be converted into the business value is
very significant in current time. Value is prime driver that deal with the real world
utilisation of the big data. Organisations investing in the big data are enjoying clear
benefit over those who ignore it & can aid them in understanding the things like
customer's behaviour.
Challenges of big data analytics & techniques that are currently available to analysis the big data
Challenges
 Big data talent gap- As filed of the big data growing very rapidly and there are only few
experts available within this field this is because, the big data is considered as a complex
field & individuals who understand its complexity & intricate nature are far few &
between. Thus, talent gap is a major challenge that exist within the industry.
 Need for the synchronization across the data sources- As it has been analysed that
data set is becoming more diverse, therefore, it requires to incorporate them in to the
analytical platform. In case, if it is ignored, then it can create a gap that lead to the wrong
insights & messages (Ray, Alani and Ahmad, 2022).
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 Getting the data into big data platform- As data is increasing on regular basis which
means that organisations have to tackle the limitless amount of the data every single day.
Variety and scale of the data which is available in recent time can overwhelm any data
practitioner & that is why it is significant to make the data accessibility convenient and
simple for the brand managers & owners.
Techniques
 Machine learning- It has been analysed that in the file of artificial intelligence, the
machine learning is very helpful in data analysing. As emerging from the computer
science, machine learning work with the computer algorithms with the motive to produce
data based on the assumption.
 Apache Hadoop- It is free Java based software framework that can be used to store a
big amount of the data in cluster. This technique enables the users to process the data
across various nodes. It also contains a storage system that is HDFS. It allows the bog
data to be disunited and distributed to several nodes inside the cluster.
 Search & knowledge discovery- It support an extraction of the information from the
structured & unstructured repositories of the data from different sources including
database, applications and file system (Singh, 2022).
How Big Data technology could support business, please use examples wherever necessary
It has been analysed that every business, big, small and medium need a valuable data &
insights. When it comes to understand customer's preferences and target audience, then big data
play a vital role as it helps the organisation in anticipating their needs. Big data technology
supports a business in various ways, mentioned below:
 Dialogue with the consumers- It allow the companies to profile the customers in a far
reaching manner. For instance, in Mark and Spencer, big data enable the company to
engage in the real time and one on one conversation with its customer that help the
respective company to understand their customer's requirements (Teimourzadeh,
Kakavand and Kakavand, 2022).
 Re- develop the product- It has been analysed that big data is most effective way to
gather and use the feedback. As it helps the companies in understanding that how the
customer perceives company's products & services. Thus, organisation is able to make
the significant changes and also re develop their products. Additionally, big data allow
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the organisation to test several variations of the high- end computer- aided design in few
seconds. For example, by Tesco can gather information related to lead time, performance,
material affect cost and more. This enable the respective company to raise productivity &
efficiency of different production processes.
 Data safety- The big data allow organisation to map entire data landscape across the
organisation. It allows them to analyse all types of the internal threats. Therefore, with
this information, company like Tesco can keep the sensitive information safe. This is
protected in most appropriate manner & stored based on the regulatory requirements.
Because of this, mostly industries are paying attention on the big data in order to ensure
the data safety & protection. It is more significant within workplace that deal with the
credit & debit card information, financial information and other such kind of practices
(Xie, and et. al., 2022).
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CONCLUSION
From the above report, it become clear that the big data is changing was individuals
perform complex and common tasks & this changes will take the organisation and individuals
they cannot begin to imagine. This report has examined that there are various challenges that
arise in scope of the big data, by to win over these challenges, major techniques breakthrough
can be reached. Hence, instead of seeing the big data as a challenge, companies need to accept
them and keep improving its uses to reach full potential thereof. Therefore, it is advised to the
enterprise that they follow the most suitable technique so that they can overcome for the risk or
challenges of big data analyses and become more productive and efficient.
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References:
Books and Journals
Bhardwaj, M. and Agarwal, S., 2022. Decision-making Optimisation in Insurance Market Using
Big Data Analytics Survey. In Big Data Analytics in the Insurance Market (pp. 57-80).
Emerald Publishing Limited.
Hassna, G., 2022. Big Data and Analytics to transform higher education: a value chain
perspective. Perspectives: Policy and Practice in Higher Education, pp.1-9.
Patel, S. and Shah, M., 2022. A Comprehensive Study on Implementing Big Data in the Auditing
Industry. Annals of Data Science, pp.1-21.
Ray, S.K., Alani, M.M. and Ahmad, A., 2022. Big data for educational service management. In
Big Data and Blockchain for Service Operations Management (pp. 139-161). Springer,
Cham.
Singh, N., 2022. Developing business risk resilience through risk management infrastructure:
The moderating role of big data analytics. Information Systems Management, 39(1),
pp.34-52.
Teimourzadeh, A., Kakavand, S. and Kakavand, B., 2022. Application of python in marketing
education: A big data analytics perspective. Marketing Education Review, pp.1-16.
Xie, Y. and et. al., 2022. Ower Big Data Analysis Technology and Application Based on Cloud
Computing. In Innovative Computing (pp. 1559-1564). Springer, Singapore.
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