Application of Data Visualization Technology Under the Background

of Big Data

FENG LI, LINGLING WANG

School of Management Science and Engineering

Anhui University of Finance and Economics

Bengbu 233030, CHINA

Abstract: - In the development trend of big data era, visualization technology gradually integrates with big data

technology to form data visualization technology. This paper mainly introduces the concept of data

visualization, analyzes and summarizes the advantages of data visualization technology, and analyzes its

application scenarios, such as financial, E-commerce, medical, education, agriculture, weather forecast,

transportation and epidemic prevention fields. Finally, through the above application scenarios, we can better

understand the importance of data visualization technology in the big data environment.

Key-Words: - Data Visualization Technology; Big Data; Financial.

Received: August 23, 2021. Revised: May 14, 2022. Accepted: June 13, 2022. Published: July 3, 2022.

1 Introduction

In the era of big data, not only are all kinds of

data flooding our lives, but also we need to process

and use all kinds of data [1-3]. We can not do

without data, can not do without all kinds of

information, in receiving information at the same

time we are also the sender of information. The

massive and complicated data usually makes people

dazzled. How to get the data we need quickly and

accurately has become a big problem that modern

big data technology is committed to solving.

Nowadays, data capture technology based on web

crawler technology has been applied in many

aspects, which greatly improves the efficiency of

data acquisition. However, not everyone is skilled in

working with data, and for data that is difficult for

non-professionals to understand and difficult for

professionals to understand, it needs to be presented

in another way. Data visualization technology

allows data to be presented in the form of pictures,

charts and so on, intuitively and effectively

conveying the information expressed by data to

people [4]. In general, data visualization technology

helps us to better manage and understand data and

get more useful information from it. And with the

continuous maturity of data visualization

technology, it is applied in more and more fields and

scenes, bringing more and more services, playing a

more and more important role.

With the development of big data, the value of

data is released to the maximum extent. Small data

may carry important information under certain

circumstances, so even small data may have an

unimaginable important role. When it comes to big

data, the first thing that comes to mind should be its

"many". Indeed, big data is characterized by large

amount of data, various types of data, fast

transmission speed, high time-efficiency, low value

density and online data [5]. In addition, compared

with traditional data, the "data online" feature of big

data allows people to search and call data for

unlimited time and realize real-time data sharing.

Data visualization is an indispensable tool for big

data analysis. Data visualization technology is a

kind of technology that uses programming and

coding to transform all kinds of numbers and letters

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representing data into graphics and other visual

objects for people to view intuitively. In fact, data

visualization is more like a way of communication,

receives the information from the data source, and

its visualization, to want to get the data of a more

intuitive, clear get want to get the information, and

that for the message, let the information fast, and

easy to understand is to receive is desired.

Data visualization requires the construction of

data space, the use of a variety of data sets to form a

multidimensional space, but also need to calculate

and analyze the data, multidimensional data also

need to analyze the data from multiple angles, every

step should be accurate and accurate. Data

visualization is not a single technical method, it

includes many technical methods, because the

principle of visualization is more than one, with the

development of technology, data visualization has

been put forward a variety of methods [6].

From the concept of data visualization, we can

know that data visualization is a more advanced and

simple technology compared with traditional

visualization. Clarity and intuition are the most

essential characteristics of data visualization. Using

data visualization to sort out and analyze data will

greatly improve work efficiency. Traditional data

visualization, such as various statistical graphs and

tables such as histograms, scatter graphs and broken

line graphs, are often used for data analysis in real

life [7]. However, compared with advanced data

visualization developed in the era of big data,

traditional data visualization is less efficient and

more complicated. In the era of big data, data

visualization should not be limited to static charts

and graphs, but more used data visualization should

be interactive and interactive. Compared with static

expression, dynamic expression can deepen people's

impression, and people can receive the information

conveyed by complex data more easily, which is

clearer and more intuitive. Therefore, dynamic data

visualization is more interactive and more efficient

than traditional data visualization.

Therefore, in the era of big data, data

visualization is evolving all the time. People's

definition and concept of it are constantly changing

with the development of big data technology and the

evolution of The Times, and its boundaries are

constantly expanding.

2 Overview of Big Data and data

visualization technology

Big data refers to the collection of data that

cannot be captured, managed and processed by

conventional software tools within a certain period

of time [8]. It is a massive, high-growth and

diversified information asset that requires a new

processing mode to have stronger decision-making

ability, insight and discovery ability, and process

optimization ability. Big data covers a wide range

of industries, including politics, education, media,

medicine, commerce, industry, agriculture, Internet

and other aspects in addition to finance.

According to the report of McKinsey, an

internationally renowned consulting company,

information technology, financial insurance,

government and wholesale trade have the highest

potential in terms of the comprehensive value

potential of big data application [9]. In terms of the

data volume of each company in the industry, the

data volume of information, finance and insurance,

computer and electronic equipment, and public

utilities is the largest. It can be seen that both the

information industry and the financial industry are

key industries for big data application in terms of

investment scale and application potential. If we

look into its development history, data visualization

has previously gone through two stages: scientific

visualization and information visualization.

Different from the previous two stages, the

definition of data visualization at this stage is

broader, which comes from the increase of its

technical methods. Not only computer technology,

image processing, mathematical modeling and so on

are applied to data visualization, and the

combination of various technologies gives rise to its

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broader concept. This becomes a major prerequisite

for the flexible application of data visualization

technology in various fields.

With the development of data visualization,

there are more and more data visualization

technologies in front-end interface, such as

Highcharts, Echarts, Charts, D3, etc. Most of them

can be flexibly used in PC and mobile devices, and

have high compatibility, allowing them to be used in

many browsers. Some of them are open source, but

not entirely free, and require licensing and paying

fees to get better services [10]. Some are open

source and free with rich features; Some

visualizations take on a variety of forms; Some can

be used flexibly and quickly without any plug-in. In

general, they are highly compatible and easy to

operate and use. In addition, in the process of

continuous development, these technologies will be

more perfect, with more new features, new

functions, while the user experience will be

constantly improved, the user will be more and

more.

In addition to front-end technology, data

visualization technology also has a relatively

representative graphics technology -- Processing,

which is an open source programming language

based on Java development. Compared to front-end

technology, Processing is also a development

environment. As a development environment, it not

only supports Linux, Windows, and Mac OSX

platforms, but also supports exporting images to

various formats. Therefore, Processing has higher

compatibility and flexibility.

The data visualization market has grown since

the concept of data visualization was first

recognized [11]. There are endless visualization

products in the data visualization market at home

and abroad, and there are many mature products.

The representative ones known to people are DateV,

RayData, Tableau, Sugar, etc.

In the era of big data, visualization technology

has occupied a place and developed into an

irreplaceable part. No matter how visualization

technology develops and how numerous

visualization products are, in terms of development

concept, it has been continuously developing to

provide convenience and better service to people's

life.

3 Application of data visualization

technology

With the continuous development of data

visualization technology and tools, more and more

technologies and tools have been developed and

applied, which also makes data visualization applied

in more and more industries. In the process of the

continuous development and application of artificial

intelligence technology, the two technologies are

gradually combined and applied, so that more and

more fields are gradually becoming intelligent. Here

are the main applications of data visualization:

3.1 Financial and E-commerce fields

In the era of big data, information is advanced,

digital economy is developing rapidly, a large

amount of data is generated in the financial field,

and data visualization has been widely applied in the

financial field [12]. By using data capture

technology, financial information can be captured

quickly on the Internet, such as valuable information

related to customers in various transactions, and the

obtained data can be analyzed and mined. Using

visualization technology intuitive multi-angle

analysis of customer behavior effectively, so as to

get the real needs of customers, understand

customer profitability of financial products,

security, and so on various aspects of demand,

further through the technology of data for the design

of financial products to build, in the form of visual,

eventually make reasonable design scheme, Design

financial products that meet customer expectations.

In addition, based on the technology of data,

managers can obtain the whole financial market

transaction data, and carries on the full data from

multiple perspectives analysis and calculation,

intuitive use data visualization technology to show

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the stages of financial market development trend,

then can design better and more reasonable for the

next step of financial products to provide direction

and train of thought. Big data technology brings not

only the improvement of financial analysis tools to

the financial industry, but also stimulates new

changes in financial technology in the process of

continuous development. The integration of big data

technology and financial technology enables the

massive and miscellaneous data generated by the

financial industry to be filtered and purified, which

further improves financial efficiency and enables

financial technology to be innovated. For financial

services, data visualization has completely changed

the traditional financial services, enabling them to

realize the innovation of financial services based on

big data. With the help of data visualization

technology, user data can be intuitively analyzed

and modeled from multiple angles. The data can be

classified and sorted according to the needs of

managers, and user needs can be reasonably

divided, so as to provide targeted financial services

to users. Based on the "data online" feature of big

data, even if the decision is wrong, it can find out

the mistake and correct it in time. In general, the

application of data visualization in the financial

field will promote the improvement and innovation

of all aspects of the financial industry, not only

enhance the activity of the financial market, but also

increase the competitiveness of the industry and

enable it to get more development.

With the rapid development of the Internet, the

e-commerce industry has risen rapidly and

developed in full swing [13]. Therefore, when

people make use of various e-commerce platforms

for online shopping, massive e-commerce data will

be generated, and the demand for data management

will increase. The use of big data technology to

manage data, hot-selling commodity analysis,

service data analysis, customer feedback analysis,

logistics information management, to make more

scientific and reasonable strategies, in order to

achieve precision marketing, personalized

recommendation, personalized service and other

applications, improve competitiveness, optimize the

quality of the industry.

3.2 Medical and education fields

Compared to the early medical industry to

record and store data in written form, data

visualization brings electronic data storage, which

greatly reduces the risk of data loss [14]. At present,

the medical industry can predict influenza, conduct

genome analysis, patient data analysis and other

medical data analysis through big data visualization

technology. Remote monitoring of equipment and

evidence-based medicine are also the applications of

data visualization in the medical industry. These

applications can help patients achieve intelligent

management of disease. Through real-time data

sharing, medical information sharing can be realized

by constructing data network between medical staff

and patients, and management information system

between medical devices. The application of data

visualization plays a key role in the realization of

smart medical treatment and the construction of a

new green medical ecology.

The application of data visualization in the

field of education means that data visualization

enters the classroom and the concept of smart

classroom will be deepened [15-17]. In the era of

big data, creating smart classrooms in the field of

education has become a development trend.

Knowledge is no longer limited to books, videos,

etc. More and more dynamic forms make

knowledge more intuitive and dynamic display,

which can not only deepen the reconstruction of

knowledge, but also promote the training of learning

thinking. In intelligent teaching, massive learning

data will be optimized to make it multi-dimensional

and multi-structured. The application of learning

process analysis, knowledge heavy and difficult

analysis, teacher-student information sharing, and

future performance prediction can realize the

sharing of information between teachers and

students and between students, and realize the goal

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of knowledge visualization, thinking visualization,

learning data visualization, so as to create a more

interactive classroom experience.

3.3 Agriculture and weather forecast fields

In agriculture, data visualization also has many

application scenarios [18]. By analyzing the data of

crop growth environment, growth preference,

growth cycle and so on, using data visualization

technology to simulate the growth and development

of crops in specific light, water, temperature,

humidity and other conditions, to achieve the

determination of the best growth conditions of

crops. And using big data technology, the

simulation experiment can be carried out quickly

only by importing relevant data. Compared with

experiments under natural conditions, big data

simulation experiments are more efficient, and the

results obtained under natural conditions are just as

accurate and real. The agricultural simulation

experiment completed by data visualization can not

only greatly save the experiment time, reduce the

input of manpower, material resources and financial

resources, but also ensure the purpose of agricultural

teaching experiment. In addition, the traditional

agricultural field teaching is based on field practice,

the use of data visualization can be agricultural

teaching visualization, through the computer

network and other remote visual teaching,

interactive experience as if immersive.

In the field of weather forecast, daily weather

forecast work also produces a large number of data

[19]. With the help of big data technology, various

meteorological observation data and geographical

observation data can be managed, and the data

visualization method can be used to present the

analysis results more intuitively and effectively, so

as to obtain scientific and reasonable decisions,

which is conducive to better developing various

meteorological services. For example, Tableau is an

intelligent software with simple operation and

flexible use. As a visualization tool, it can quickly

switch and generate views by following the path of

thinking. Some studies have used it for statistical

analysis of meteorological data, and conducted in-

depth group analysis through dynamic screening of

data visualization, and obtained the results of

research without the aid of visual tools in previous

years very quickly [20].

3.4 Transportation and epidemic prevention

fields

With the improvement of economic level,

people's living standard has also been improved

[21]. In order to meet the demand of going out,

more and more families have private cars, and

traffic congestion has become a concern. The

application of data visualization in the field of

traffic provides a new way to solve the problem of

traffic congestion. With the support of

transportation Internet of Things and CIS and other

technologies, it collects all kinds of transportation

infrastructure information, constructs the

transportation system more intuitively and

effectively, and actively seeks solutions. The

construction of three-dimensional space

transportation network, convenient staff to find

information, repair loopholes, greatly improve work

efficiency. Using data visualization technology to

solve the problem of traffic congestion is scientific

and effective, and Shenzhen is a successful case.

Looking to the future, data visualization will be

applied in a wider range in the field of traffic.

Data visualization also plays an important role

in epidemic prevention [22-24]. Not only the

epidemic situation in different regions and the

whole country, but also the situation of the global

epidemic. Through data visualization, the map of

the global epidemic situation can be built to analyze

the flow of people and exit and entry conditions, so

as to make more scientific and reasonable decisions

on epidemic prevention and control. A series of

applications such as real-time observation, real-time

reporting, real-time monitoring and real-time

protection have made important contributions to

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improving the epidemic situation and implementing

epidemic prevention and control [25].

Nowadays, we are increasingly inseparable

from big data, and while recognizing the importance

of big data technology, how to avoid the possible

risks of big data technology is also worth thinking

about [26]. Although the development potential of

big data technology is huge, it does not mean that it

will not have negative effects that disturb people. In

fact, in the era of big data, our personal privacy has

been seriously disclosed. Whether we can use big

data technology to solve the problems caused by big

data needs to be explored. While enjoying the

benefits brought by the development of science and

technology, we also need to be alert to danger in

times of peace and have an optimistic attitude.

4 Conclusion

In the era of big data, data visualization

technology plays an important role in many fields,

such as financial, E-commerce, medical, education,

agriculture, weather forecast, transportation and

epidemic prevention fields. Finally, through the

above application scenarios, we can better

understand the importance of data visualization

technology in the big data environment.

Acknowledgment

We thank the anonymous reviewers and editors

for their very constructive comments. This work

was supported in part by the Natural Science

Foundation of the Higher Education Institutions of

Anhui Province under Grant No. KJ2020A0011,

Innovation Support Program for Returned Overseas

Students in Anhui Province under Grant No.

2021LCX032. the Science Research Project of

Anhui University of Finance and Economics under

Grant No. ACKYC20085, Undergraduate teaching

quality and teaching reform project of Anhui

University of Finance and Economics under Grant

No. acszjyyb2021035.

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