Information Systems and Big Data Analysis: Techniques and Business Use

This report provides an overview of big data and information systems, defining big data and its key characteristics such as volume, variety, velocity, and variability. It highlights the challenges of big data analytics, including a lack of understanding, data growth, and tool selection. Various techniques for analyzing big data are discussed, such as A/B testing, data fusion, data mining, and machine learning. The report further explains how big data technology can support businesses through healthcare applications, consumer dialogue, and product redevelopment, providing real-world examples. It concludes that big data and information systems enable organizations to test variations, gather information, and enhance performance, while addressing the challenges associated with processing large volumes of data systematically.

Information Systems and Big Data
Analysis
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Contents
INTRODUCTION...........................................................................................................................3
MAIN BODY...................................................................................................................................3
What big data is and the characteristics of big data...............................................................3
The challenges of big data analytics.......................................................................................4
The techniques that are currently available to analyse big data.............................................5
How Big Data technology could support business, an explanation with examples...............6
CONCLUSION................................................................................................................................6
REFERENCES................................................................................................................................8
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INTRODUCTION
The term information system is explained as an integrated set of components which is
used for collect, process and stores the data to provide information or knowledge to the
organisation. Big data refers to that information that contains a large variety, increase in volume
of information and more velocity. In the present scenario, most of the business depends upon
entirely big data and information system. Moreover, this report highlights on big data and also on
characteristic of big data (Al-Mekhlal and Khwaja, 2019). Along with this challenges related
with big data analytics and techniques related with analysis of big data will also include in this
report. In the last, role of big data technology to support business is also cover in this report.
MAIN BODY
What big data is and the characteristics of big data
From the perspective of Gartner, Big-data is a high-volume, variety and velocity related
information asset and this is related with cost-effective, innovative forms of information
processing related that enhance insight and decision-making. In simple terms, big data is
explained as the collection of data which are large in volume and also they are increasing with
time. Furthermore, big data is too large in size and due to this it is complex to store and process
with traditional tools. Example- Stock exchange market is an example of big data as they
generate one terabyte of new trade information per day.
Characteristic of Big Data
 Volume- The name big data refers to size that is enormous or huge. Size of big data
performs an essential role for determining the value of data. Moreover, whether data is
considered in category of big data or not, is depends on upon volume of data. So volume
is one characteristic that is used to deal with big data solutions.
 Variety- The term variety consider heterogeneous sources and nature of data, it include
both structured and unstructured data (Kobusińska, Pawluczuk and Brzeziński, 2018). In
the present scenario, database, spread sheet, email, photos, videos, etc. are considered as
sources which relates with variety of data.
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 Velocity- It include or undertake speed of generating the data and also how fast data is
processed and generated to match with demand. This support to determine the real
potential of information and data.
 Variability- Data is stored at a large level and due to this sometimes inconsistency is
identified by the data in different times. Thus, this explains as a process to handle all
data in an effective manner.
The challenges of big data analytics
This is complex for organisation to perform their functions without engagement of big
data. Huge of data is generated in each second from the product or service sales figure,
stakeholders, etc. and this information work as a fuel that drives companies to retain in market
for longer period (Lin and Yang, 2019). But, as big data is used by all organisations so this is
also identified as competitive task. Some challenges related with big data are mention as follow:
 Lack of proper understanding of big data- Organisation fail to understand big data
because of their insufficient knowledge. Workforce face challenges to analyse and
evaluate data, its storage, processing and importance. This results that business
authorities do not store sensitive data due to which database are not utilised properly for
storage of data.
 Growth of data- One of the most difficult challenges related with big data is that this is
complex to store huge set of data in a proper manner. On the other side, amount of
essential data which is important to store is increasing with rapid speed. Due to this
growth of data is another challenge and this is complex to handle because most of them
comes from videos, document, text-files, etc. which is unstructured and complex to store
and identify in database.
 Selection of big data tool- Several times organisation gets confused to select the
appropriate tool for big data storage and analysis. HBase, Cassandra and many more are
the tools related with data storage. Furthermore, Hadoop Mapreduce, etc. are the
methods or options related with data-analytics (Ming and et. al., 2018). So this end up in
poor decision-making and selection of inappropriate technology and it results in waste
of time, work-hours and efforts.
The best way for overcome from above mention challenge is to seek professional help and
support. For this business authorities recruit experienced professional who understand and know
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about the systems are used for process big data consulting. These results to formulates effective
strategy and to select best tools to engage big data in organisation.
The techniques that are currently available to analyse big data
Revenue from the global market of big data is increasing with rapid speed because the
overall world is based on data. On the other side, data analytics is a process of examine data sets
in the form of audio, text, video, etc. and after this to draw conclusion from the information
which contain more common factors related with specific system, methods and software. Some
big data analysis techniques are mention as follow:
A/B testing- This information investigation strategy includes contrasting a benchmark group and
an assortment of test gatherings, to recognize what medicines or changes will work on a given
objective variable (Qi, 2020). McKinsey gives the case of investigating what duplicate, text,
pictures, or format will further develop change rates on an internet business site. Big information
squeezes into this model as it can test gigantic number that may demonstrate some numbers it
must be accomplished if the gatherings are of a large enough size to acquire significant contrasts.
Data Fusion and data integration- By joining a bunch of strategies that examine and
coordinate information from different sources and arrangements, the experiences are more
effective and conceivably more exact than if created through a self-contained wellspring of
information.
Data and Information mining- A typical instrument utilized inside huge information
investigation, information mining separates designs from enormous informational collections by
consolidating techniques from insights and AI, inside data set administration. A model would be
when client information is mined to figure out which portions are probably going to respond to a
deal.
Machine Learning- Notable inside the field of man-made brainpower, AI is additionally utilized
for information investigation. Arising out of software engineering, it works with PC calculations
to deliver suspicions dependent on data (Qiu and et. al., 2020). It gives expectations that would
be outlandish for human investigators.
How Big Data technology could support business, an explanation with examples
Big data is explained as the combination of all processes and tools which is useful for
utilising and managing set of large data and information. Concept of big data was introduce for
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understand the preferences, trends, patterns and systems related with huge database that are
understand when people interact with each other. Furthermore, big data support in completion of
business function is mention as below:
Use of big data in healthcare- Information and data pioneers analyse all those outcomes that
relate with pharmaceuticals (Sarker and et. al., 2020). Like, in the traditional period health relate
companies focus on more benefits and after the use of big data risk related section are also
identify because this helps to better analysis of trials and outcomes. These results to create new
design and services related with future products by using knowledge that relates with
organisation.
Dialogue with consumers- The existing customers is smart and also they understand all of its
priorities. This determines before making purchase decisions buyer look for all sections and
options that fulfil similar need. Also, individual talk with business through use of different social
media channel. Example of dialogue with customer relate with bank as when a customer or
individual entered in the bank, clerk check their profile to learn about the individual preferences
and desire.
Re-develop of products- Big data is identified as one of the best way for collect and utilise
feedback and this support an organisation for understand how customers perceive its services and
products. It results that management is able to make essential changes as well as to re-develop
products. Example- with the analyses of unstructured social-media text an organisation uncover
general feedback related of customers (Wu and et. al., 2020). Moreover, big data analyse also
helps to disintegrate feedback according to the geographical locations and demographic groups.
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CONCLUSION
From the basis of above report, this is concluded that big data and information allow an
organisation for test numerous variations that relate with current trends. The main focus of big
data is to gather information about the computer-aided design and then to use them enhance
organisational performance. Velocity, variety, etc. are different characteristics of big data and
they are beneficial for store and process huge number of data. Furthermore, challenge related
with big data generates problems for organisation to process information in a systematic manner.
In the last, report also concludes about big data role and their support among organisation to
enhance company performance.
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REFERENCES
Books and Journals
Al-Mekhlal, M. and Khwaja, A.A., 2019, August. A Synthesis of Big Data Definition and
Characteristics. In 2019 IEEE International Conference on Computational Science and
Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous
Computing (EUC) (pp. 314-322). IEEE.
Kobusińska, A., Pawluczuk, K. and Brzeziński, J., 2018. Big Data fingerprinting information
analytics for sustainability. Future Generation Computer Systems, 86, pp.1321-1337.
Lin, H.Y. and Yang, S.Y., 2019. A cloud-based energy data mining information agent system
based on big data analysis technology. Microelectronics Reliability, 97, pp.66-78.
Ming, J and et. al., 2018, April. Analysis models of technical and economic data of mining
enterprises based on big data analysis. In 2018 IEEE 3rd International Conference on
Cloud Computing and Big Data Analysis (ICCCBDA) (pp. 224-227). IEEE.
Qi, C.C., 2020. Big data management in the mining industry. International Journal of Minerals,
Metallurgy and Materials, 27(2), pp.131-139.
Qiu, H.J and et. al., 2020. Using the big data ofinternet to understand coronavirus disease 2019's
symptom characteristics: a big data study. Zhonghua er bi yan hou tou jing wai ke za
zhi= Chinese journal of otorhinolaryngology head and neck surgery, 55, p.E004.
Sarker, M.N.I and et. al., 2020. Disaster resilience through big data: Way to environmental
sustainability. International Journal of Disaster Risk Reduction, p.101769.
Wu, Y and et. al., 2020. Characteristics and optimization of core local network: Big data analysis
of football matches. Chaos, Solitons & Fractals, 138, p.110136.
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