Big Data: Characteristics, Challenges, and Business Support

This report discusses the characteristics of big data, including volume, variety, velocity, and variability. It also covers the challenges faced by big data, such as lack of understanding, data growth, and security issues. Additionally, the report highlights how big data supports businesses, with examples from Coca-Cola and Netflix.

BIG DATA
INTRODUCTION
 Big data is an advance analytical technique that is use to collect large and diverse data that consist of semi structure, structure and
unstructured data from various source as well as of different size likewise terabytes to zettabytes.
 The present report will discuss on characteristic of big data and new techniques that is available currently with this software.
 Lastly, the study will throw light on how it data technology support organization and the challenges faced by it.
CHARCHTERSTICS OF BIG DATA
 Volume: The big data is generally known by it is size and it play
important role in determining its value.
 Variety It refers to the nature of the data such as structure,
unstructured or semi- structure as well as the source form where that
data has been taken such as heterogeneous (Saggi and Jain, 2018).
 Velocity: The term velocity means speed of the data such as how
rapidly the data will have processed in order to meet the demands and
determine the real potential of the data.
 Variability It refers to the inconsistency that is shown by the data
while processing the facts.
Describing how big data support business
 The big data helps the organization for collecting
the information form heterogeneous website.
 That helps company in identifying the needs and
demands of the customer and new market trends.
 Example Coco Cola and Netflix
Challenges faced by big data
 Lack of understanding Big data: Most of the organization do
understand the big data as in many company’s employees that
handle data processing.
 Data growth issues One of the most intense issues that company
generally face is storing the huge data.
 As the amount of storing the data is increasing day by day and
with high growth with time it is very hard to handle all the
information.
 Securing the data: This one of the most common and daunting
challenge that company has to face while collecting the data.
 Because the business is busy in collecting, analyzing and storing
the data it pushes data security at last stage.
 For solving the security challenge organization can make use of
advance technology such as data encryption, real time security
monitoring and use IBM guardian for big database.
CONCLUSION
 From the above report it has been concluded that
big data is consisted of large number of facts.
 It is mainly used to gather and processing huge
information.
 The report has concluded on the types of big data
such as structure, semi-structure and unstructured.
 As well as the new techniques that are used by the
company in order to solve the challenges.
REFERENCES
 Choi, T. M. and et.al., 2018. Big data analytics in operations management. Production and Operations Management. 27(10).
pp.1868-1883.
 Dai, H. N. and et.al., 2020. Big data analytics for manufacturing internet of things: opportunities, challenges and enabling
technologies. Enterprise Information Systems.14(9-10). pp.1279-1303.

NOTES
 Presenting big data and its characteristics
 Data can be defining as quantities and symbol that is used by the computer in order to perform
the operation.
 Moreover, the data is store and can be transmitted in the way of electrical signal and usually
recorded on mechanical recording likewise such as electric signals.
 Whereas big data is also a type of data with large size and it generally a collection of facts that are
in large volume (What is BIG DATA? 2021). It can be store by using the traditional data
management tool because of its large size and complexity.
 Furthermore, the sources of data are complex in nature compare to traditional data because it is
driven by artificial intelligence, social media, mobile phone and internet.
 For instance, New York stock exchange is a best example of big data because it generates one
terabyte while trading in one day (Hariri, Fredericks and Bowers, 2019).
 The another good example is jet engine as it generates 10+ terabytes in 30 minutes of flight time
as well as with many thousand flights it reaches up to Petabytes. Generally, there are three types
of big data that are explained in details below:
 Structure data: It can be describing as any data that can be store and processed in the form of
fixed structure. along with this, it defines the length and format for big data. The data store in
the relationship database management is a good example of structure data. Such as employee
table that is consist of date, group and numbers that contributes company in knowing the
appropriate amount of facts related to the employee’s performance.
 Unstructured data: The data that is in the form of unknown structure is known as unstructured
data. It is very hard for processing data and driving value out of it as it is not in proper form (Zhu
and et.al., 2018). The best example of this type is heterogeneous data source that is combination
of image, text and video etc.
 Semi- Structure: This type is combination of both the data such as it is a form of structure data
that do not follow the tabular format associate with the relational data. XML file is a good
example of semi- structure data.
 There are four characteristics of big data that is discussed in details below:
 Volume It is one of the crucial aspect that need to be taken into consideration is while dealing
with hue data. Because weather the data is to be consider big or not usually depends on it ‘size.
 Variety). Generally, the variety of unstructured data face problems in storing, mining and
analysing the data.
 Velocity: The big data requires high speed for processing and storing the data as the flow of
data is large and continuous. Example is business processes, mobile phone and social media.
◦ Challenges faced by big data
 Nowadays every company and organization needs advance technology for maintaining the
smooth flow of functioning within the departments of the company.

 As the business function there is large amount of data that generates such as customer relation,
sales figures etc.
 Thus, all this data compile together and become big data (choi and et.al., 2018). Furthermore, for
getting appropriate figures and information all the data needs to be analysed in order to make
proper decision.
 But there are some challenges that firm has to in-counter while dealing with big data. There are
various challenges that are mentioned in details below:
 Lack of understanding Big data
 There is a chance that subordinates may not know the nature of data, it's storage, processing,
importance and the sources from where the data is coming.
 Moreover, every organization needs a data expert as it has knowledge regarding the data
analytical for solving the problems related to it.
 Along, with this, firm can solve this issues by conducting the seminars, workshop and training
programmes.
 So that employees will be able to arrange the data handling properly that will contribute in
protecting the sensitive and important data.
 Data growth issues:
 Moreover, most of the data are in the form of unstructured type that include videos, image and
audio etc. (Singh and El-Kassar, 2019).
 For solving this problem, the company is making use of advance technology such as compressing
that helps firm in reducing the size of the database.
 Along with this, another tool that firm use is duplication that helps in removing the unwanted data
from the set. Whereas, data tire tool allows the firm in storing the data in different tire.
 Securing the data:
 And due to that companies face problems related to hacking that leads in damaging the firm
name in competitive market.
 Furthermore, company can have lost millions of stolen record or data breach (Dai and et.al.,
2020).
 For solving the security challenge organization can make use of advance technology such as data
encryption, real time security monitoring and use IBM guardian for big database.
 Describing how big data support business
 Thus, it allows the organization to make the product according to the demands of their targeted
audience that has contributed in building the brand loyalty locally as well as in international
market.

 The classic example of using the big data tool is Coco Cola such as in 2015 the firm has started
using the digital marketing strategy likewise social media and official website. The big data
analytical has helped the firm in high customer retention at global level.
 The another advantage that business has while using the big data that it helps the company in
knowing the market insights and solve advertiser problems. Furthermore, it has helped the firm in
changing the business operation that consist of changing product line, meeting the needs of the
customer as well as ensuring the appropriate marketing strategy (Examples of companies using
Big data analytical., 2021).
 ). The big data involves observing online activities, dynamic change in customer preference such
as gaining insights of market trends used by competitors as well as analysing the customer
data's.
 Netflix is the good example of using the big data as it uses for target advertisement. The
organization has a million of subscriber and because of that company is able to collect huge data.
 The company collects the search result of the customer and on the basis of that it suggests their
audience film and web series regarding their taste.
 That allow the firm in making the strong relation with their consumer and increased their loyalty
that leads in raising profitability of organization.
 CONCLUSION
 Along with this, the study has depicted about the characteristic of the big data likewise velocity
and variety.
 Lastly, the report has also thrown light on the challenges faced by this technology such as data
growth and security issues.
 As well as the new techniques that are used by the company in order to solve the challenges.
Furthermore, the study has also concluded on the benefits business have while using big data.
 REFERENCES
 Dai, H. N. and et.al., 2020. Big data analytics for manufacturing internet of things: opportunities,
challenges and enabling technologies. Enterprise Information Systems.14(9-10). pp.1279-1303.
 Hariri, R. H., Fredericks, E. M. and Bowers, K. M., 2019. Uncertainty in big data analytics:
survey, opportunities, and challenges. Journal of Big Data. 6(1). pp.1-16.
 Saggy, M. K. and Jain, S., 2018. A survey towards an integration of big data analytics to big
insights for value-creation. Information Processing & Management. 54(5). pp.758-790.
 Singh, S. K. and El-Kassar, A. N., 2019. Role of big data analytics in developing sustainable
capabilities. Journal of cleaner production .213. pp.1264-1273.
 Zhu, L. and et.al., 2018. Big data analytics in intelligent transportation systems: A survey. IEEE
Transactions on Intelligent Transportation Systems. 20(1). pp.383-398.
 Online

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