Big Data: Exploring Characteristics, Techniques, and Challenges

This report provides an introduction to big data, highlighting its characteristics (variety, velocity, volume, veracity) and its significance in modern industries. It discusses the challenges associated with big data analysis, including data growth, lack of professional knowledge, tool selection, and data security. The report outlines several techniques used in big data analysis, such as A/B testing, data mining, and data integration, explaining how these methods support businesses in customer involvement, data management, and data privacy. The report also references how technology helps companies to evaluate quickly by managing the old data of clients.

Big Data
Introduction
Information system is a process or set of co – ordinate components
which works together to store, process and collect. It refers to the
software which assists in organizing and analyzing data with system
having a motive to convert unprocessed data into useful data which can
help industries in decision making. There are several elements of it
such as, software, hardware, procedures, feedback and people. There
are many advantages of it such as creating new job roles, globalization
and reducing cultural gap. The following report will cover
characteristics of big data , challenges faced while doing big data
analysis, techniques which are currently available for analyzing big
data and how big data could support businesses.
Big data and its Characteristics
Big data refers to large and complex data components which are analyses to decode important data that
can be very essential for the growth of the organization. It is an assets that is innovative and cost effective
and also helpful in giving insight and decision making. In today's time it is used by almost every big
industry and giving successful results to the businesses across the world. It is used in many differen
sectors such as, IT, retail, banking, healthcare, manufacturing etc. There are 3V's of big data described
briefly below:
 Variety- It contains semi structured, structure and unstructured data which is gathered from
different multiple sources which is earlier used to collected from database and spreadsheets
but now a days it comes in form of blogs, videos, pictures, mails etc. It is one of the essential
feature of big data (Hou, et. Al,2020).
 Velocity- It refers to the pace of rate at which data is traveling or it means pace in which data
is being made in the present time. In a brief concept it comes with different difficulties for
data centers which is trying to manage with the variety. It is basically considered that how
quickly the data is gather and saved.
 Volume- Very large quantity of data is being sourced on a consistent basis from many
different portals like machines, networks, social media, business processes etc. Now data
volume has been converted from TB to normal PC memory with unrecoverable shift to zeta
bytes and data processed cannot be saved or stored at traditional systems.
 Veracity- It follows the state of the stats and on how much companies are dependable on the
results to take any further decisions. The raw data is collected from the different sources that
are crucial for the companies perspective in order to over see the quality of the products and it
also assists in arranging the figures to restrict the errors which can come and later that data is
analyses (Bates, et. Al,2018).

There are several techniques which are available to analyses the data are:
A/B Testing- It is a method which is used in take control of data and
examining the variables in the different test centers to analyses the better
controlling atmosphere. It also gather the data which is used in evaluating
and giving the improved outcomes by creating the possibility and taking
control on the variables.
Data Mining- It helps in finding and evaluating the quality of the data to
find a suitable way of solving it. It is helpful in business analytic to
proceeds the proper utilization and charge of the AI (Artificial Intelligence)
that is very crucial in choosing and understanding the data. Its main goal is
to give the require data from the database to system and to the software in
the PC's of the firms (Pan, 2019).
Data Integration- It helps in managing the large data which is in size of
gigabytes and terabytes which is next to impossible to evaluate by the
humans. It is essential for the firms to evaluate the trend of the market so
that it can be useful for the organizations in the decision making and for
the well being of the consumers. The data gathered is in the formation with
the present data of the firm with using software like SPSS, python, Tableau
etc.
Techniques in using Big dataChallenges in using Big data
It refers to the procedure of organizing, assembling and analyzing the large quality of data
to disclose the furtive, relative and essential insights. Big data analysis refers to the
appropriate division in the firm. Its prospect is fixed, that many of the firms in the current
time uses this techniques. The organization requires to focus on the big data to accomplish
consumer satisfaction for a longer period of time. Currently, there are many kind of
problems which is associated to big data that are increasing in regular basis. As this need is
efficacious for data analysis to keep the customer data. In a manner to ,resolve a issue
which is connected to big data analytic s, where organization should evaluate in depth
analysis of capabilities by asking ideas of IT professionals (Dey, Bhatt, and Ashour, 2018).
the business should develop an in-depth analysis of abilities by taking the suggestions of IT
experts. The basic challenges in big data analytic are as follows -
 Problems in growth of data- It is the one of the major issues of saving data sets
because of lack of understanding and due to this data is rising very quickly which is
making difficulties in storing the data properly and safely at the authentic place.
This difficulty has obligated the firm to save the data in an unstructured way.
 Lack of professional knowledge- Latest applications and techs are required to
analyses the data for which specific content is required. The skills that are needed
to involve the professionals are IT specialist, researchers, data scientists and data
engineers, so that they analyses and understand the data which can be beneficial for
the organization. It is difficult to find people with such skills and qualifications.
 Selection of proper data tool- It is bit difficult for the companies to choose proper
tools which can easily fits data and are conveniently operable for making many
software.
 Security of Data- It is important to save the data at authentic and safe place from
where the data can be recover it by chance misplaced but only authorized person
can access to the data. It is very daunting challenge to securely save such a
important data. Many organization are busy in knowing the depth of the data but are
not mainly focusing on security of it.
 Understanding big data- If the person is in the place of knowing the data then it will
be convenient to interpret it but understanding the data is the main challenge as
usually the type of device available in the data could be contrasting. IT only
happens b cause of not having proper understanding that firms are a not able to
provide their IT analysts (Hamad, Fakhuri, and Abdel Jabbar, 2020).

How big data support business
The way of technology which is helpful in the industry of data and gives a whole new view
to look at the data in the firm to utilize in the proper way. Now a days in the current
situation, this technique helps the company to evaluate quickly by giving the business in
managing old data of clients. Several business management can make the competitive
benefits with the help of big data technique/ This technique assist in managing the
organization concerned factors which are as follows below:
 Customer Involvement- It is expedited by big data techniques. As it will facilitates
in syncing the data and it is also a key term of duty of information practice section
in the management to keep the data as per to the quantity of consumers. It helps in
gaining the importance of the manage ment by increasing consumer satisfaction
because it will make trust in management (Wright and et. Al,2019).
 Management of data- Big data technology assist in managing the data which support
the company in a organized manner. This technique uses in vast terms of software
and divisions which will be convenient for the firm to keeping big terms of data.
The data which is maintained by this technique is easily approachable for
management for a longer term which also helps in managing the clients efficiently
and effectively.
 Privacy of data- It is very important for consumers and organization in any industry.
By utilizing the instruction of methods in big data technologies, it plays an
important role in growth of management by keeping the data of the clients privates
which will increase the value of customers by keeping their large amount of data
private (Liu, 2018) .
References
Liu, Y., 2018, January. Big data technology and its analysis of application in
urban intelligent transportation system. In 2018 International Conference on
Intelligent Transportation, Big Data & Smart City (ICITBS) (pp. 17-19).
IEEE.
Pan, L., 2019. A Big Data-Based Data Mining Tool for Physical Education
and Technical and Tactical Analysis. International Journal of Emerging
Technologies in Learning, 14(22).
Dey, N., Bhatt, C. and Ashour, A.S., 2018. Big data for remote sensing:
Visualization, analysis and interpretation. Cham: Springer, p.104.
Hou, et. Al,2020. Unstructured big data analysis algorithm and simulation of
Internet of Things based on machine learning. Neural Computing and
Applications, 32(10), pp.5399-5407.
Bates, et. Al,2018. Why policymakers should care about “big data” in
healthcare. Health Policy and Technology, 7(2), pp.211-216.
Hamad, F., Fakhuri, H. and Abdel Jabbar, S., 2020. Big data opportunities
and challenges for analytics strategies in Jordanian Academic
Libraries. New Review of Academic Librarianship, pp.1-24.
Wright and et. Al,2019. Adoption of Big Data technology for innovation in
B2B marketing. Journal of Business-to-Business Marketing,26(3-4), pp.281-
293.