Big Data Analysis: Techniques, Challenges, and Business Support

This report covers the conception of big data including its features, challenges along with the technique of big data. In addition to this, it also states how big data technology supports the business organization.

History on big Data
Big data is defined as the process under which inspection of
large and complex data is done for the purpose of disclosing
the same data in a particular assigned manner. Market trends,
correlation preferences, and hidden patterns are the some
examples. In order to making any decision, every
organization is required to to extract the relevant data from
large data. So that they can take effective decisions on the
basis of data analysis which also result in the minimization
of future risk. In the economy, all the organizations are
related to the IT sector which provide wide range of solution.
Hence, it can be said that the Information system has a wide
concept in an economy. Internet plays an important role in
Information system which is correlated with the network of
devices. For the purpose of making sure about the
connectivity with the exchange of data. With the use of
technology, a network of communication has been developed
which ensures the connectivity. It has been found that the
Information system has a vital role in performing several
business operations such as managing the organization,
conducting business transaction, interaction with customers
and many more. This report covers the conception of big
data including its features, challenges along with the
technique of big data. In addition to this, it also state how
big data technology support the business organization.
Information Systems and Big Data Analysis
Name of the Student
What is big Data
A data which is fast, long and complex in nature is
consider as the big data. It is very difficult to process
manually or by the use of traditional methods. Analysis of
big data means performing of the several measures of
accessing and storing the huge amount of information for
analytics for a long duration of time period. Big data
analytics has been developed for the purpose of taking
effective decisions at work place on the basis of relevant
information derived from the big data (Pramanik and et.al,
2017). An improvement in the work performance of an
organization has been found at work place, only because
of Big data. The organizations work on their services
which they provide to their customers which result in the
increase in the overall revenue of the organization. The
size of big data is very large. Hence, it is really a difficult
task to process the data manually or by the use of
traditional methods. The data become easy after the big
data analytics and then, it can be used by the companies
for analyzing the several opportunities which makes the
management smart. In this way, analysis of big data is
related to the generation of higher profit as it bring
efficiency and effectiveness in the business operations. In
addition to this, effectiveness in working performance also
create the loyalty in customers towards the organization.
Data mining, data visualization, data storage, data analysis
etc. are some functions which are involved in the big data.
Characteristics of Big data
Volume: Big data is very large in size as it also deal with the various technological processes which
only deals with the large data. This huge amount of data is collected from several of sources which
include machines, social media, networks and many more.
Velocity: Speed of flow of data is defined as the velocity of data. The big data is being collected by
several of sources which helps the organizations in getting quick data. Hence, any organization can
get the data from social media sites, business processes, application logs, networks and many more
or the purpose of getting data instant.
Variety: There are several forms in which data can be found. Some of them are numerical data,
videos, audios, email, financial transactions and many more. The nature of extraction of data comes
under this characteristic. In ancient times, spreadsheets and databases were used as the formats of
data. But now data can be found in digital form.
Value: It can be defined as the advantages which are directed from the data. A relevant and valuable
data is required to perform the function of processing. Only after the successful analysis, the data is
said as valuable.
Veracity: Accuracy and relevancy of data can be determined by big data. This feature is related to
the reliability and trustworthiness of data.
The challenges of big data analytics
Big data analytics are the actions which are taken by the
organizations for the purpose of processing with the data to
abstract the relevant result. The biggest challenge of big data
analytics is to search the best way of managing the large
amount of data. Few major challenges of big data analytics
are given below:
Lack of knowledge professional: It is necessary for the
organizations to hire the employees who have knowledge of
applying the big data techniques in a professional manner.
They are required to search the employee with relevant
professional skills, knowledge and experience. The person
who works with the different tools related to the data are
known as data analyst, data scientist and data engineer.
Lack of proper understanding of Massive data: Big data is
the collection of huge data which is not in the proper form
for use. The organizations are required to effectively
understand the big data initiative. It has been found that
many of employees in the organization do not know about
the data, it's sources, processing, storage, importance etc.
data Growth Issues: Another challenge of big data analytics
is doing the storage of huge set of knowledge (Sun and et.al,
2020). The quantity of knowledge is stored in data centers
and databases of organization increases instantly.
Confusion while big data tool selection: The organization
have to select the tool for performing the function of big data
analytics. So the organization have to select the best tool of
analyzing their data as it directly effect the outcomes of
analytics. Along with this, there are several questions which
arise at the tome of selecting the tool for data analytics.
References
Pramanik and et.al, 2017. Big data analytics for security and criminal investigations. Wiley
interdisciplinary reviews: data mining and knowledge discovery. 7(4). p.e1208.
Sun and et.al, 2020. Big data analytics for venture capital application: towards innovation
performance improvement. International Journal of Information Management. 50. pp.557-565.
Wang and et.al, 2020. Big data analytics on enterprise credit risk evaluation of e-Business
platform. Information Systems and e-Business Management. 18(3). pp.311-350.
How Big Data technology could support business & Examples
A business organization get various opportunities with the help of technologies of big data as
they work on the internal view of organization so that they can interact with the users or
customers. It is also helpful as it provide a new perspective for companies to discover the
information which is being used in a proper manner. Below mentioned are the ways in which
the big data helps the business organization:
Understanding the customers: The technology of big data helps the business organization to
know about their customers in a better way (Wang and et.al, 2020). The marketers get to
know about their customers in a detailed manner i.e. what the customer want, what they use,
what is their spending power and many more. For instance, Disney has used the big data
technology in order to knowing the behavior of visitors at its theme park.
Delivering smarter services or products: It is also help the organization in knowing the
production of smart products so that they can influence the customer to buy their products.
For example, In order to providing the better services to the customers, Royal bank of
Scotland is using the Big data technology.
Generating an income: Big data helps the organizations in decision making processes along
with understanding the behavior of customers. It also leads to generation of higher revenue .
For example, American Express is handling more than 25 percent of credit card transactions
in the US. Amex is leveraging the data generated by these transactions for the purpose of
bringing the businesses and customers close together.
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Techniques that are currently available to
analysis big data
There are several techniques which are being available
for organizations for the purpose of managing the data.
The organization have to make the selection of effective
technique so that they can acquire more speed, depth and
scope. Few of techniques of analyzing the big data are
given below:
Machine learning: This technique make the data more
understandable by applying more trends and patterns. In
order to accelerating the processes, it work as the
advantage. It leads to the conversion of data in a
visualized form. Hence, it is necessary for the
organization to properly recognize the trends and
patterns.
A/B Testing: In order to recognizing the better
performers under a controlled environment, comparison
of two elements have been done. This technique work as
the function of comparison which result in the
completion of A/B testing technique with the outcome of
higher profit.
Statics: Big data analytics perform the functions of
collecting, organizing, inferring the data by using the
several methods of research like as base surveys and
experiments. Various techniques of statistics make easy
to analyze the big data and implies the effective result.