Big Data Analysis: Characteristics, Challenges, and Techniques

This article discusses the characteristics, challenges, and techniques of big data analysis. It explains what big data is and how it can be managed effectively. It also explores the challenges of big data analytics and the techniques currently available to analyze big data. Additionally, it provides examples of how big data technology can support businesses in managing data, maintaining data privacy, and engaging with customers. The article is relevant to subjects such as Information Systems and courses related to data analysis and management.

Information Systems and
Big Data Analysis

Table of Contents
INTRODUCTION ..........................................................................................................................3
TASK...............................................................................................................................................3
What big data is and the characteristics of big data...............................................................3
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...............5
Poster......................................................................................................................................7
CONCLUSION ...............................................................................................................................8
REFERENCES................................................................................................................................9

INTRODUCTION
Big data technology is termed as a wide term of data that refers to diverse consumers in an
organisation. This is important and mandatory for the management to manage their big data
analytical concerning development in the marketplace (Anatolyevich, and Mikhailovich, 2021).
The business has to create an effective operative software for controlling functions and functions
that are linked to big data technological data. The following project, there are brief explanation
of big data technology as with their prospects. It also involves an explanation of several
challenges that are efficient in measuring big data analytics. At lastly, it covers the manner
through that big data techniques will help the company.
TASK
What big data is and the characteristics of big data
Big Data
In the present competitory worldwide, big data technology is evolving to develop an effective
effect on the IT sector. Some instance of Big Data technology is Hadoop, Spark, Hive and Cloud.
It involves technological software will support the outlet and maintain big data that are related to
an organisation. The big data technology also involves the categorization of various components
that manage data organisation and data storehouse which is effectively for the development of
the company and create synchronism of big data technology. It involves two section of the big
data techniques that are operational and analytical big data techniques (Chen, and He, 2021). It
will rely on the work of the Information Technology division in the management to evaluate and
store big data in a fine way to help the managerial functions. It is also supported in maximising
the section of secure activities that are important for the management to create big data. The big
data technique is termed as a fundamental section that is important for securing critical
information that is related to consumers. The management can gain effectiveness in the field of
the marketplace by big data technique that plays an effective role by presenting large data section
in a precise way.
Characteristics of big data
As the business needs to determine several factors that are linked with big data techniques that
are as follows -

 The volume of data - In a broad section, the business needs to create a precise method in
maintaining a large section of data. Big data volume is large and has an enormous amount
of consumers who are high in a section of international and national business. Concerning
managing the large volume of data that are also important for a business to maintain the
responsibilities of the management to recruit expert and proficient workers. Variety of data - It is vast in the case of big data techniques that is important to be
managed in an efficient way (Pop, 2021). It involves a sort of concept of the information.
In respect to ensuring that the variety of data will get transferred effectively. The business
has to perform several tasks such as financial outputs and creating managerial tactics.
 The velocity of data – It will relate to the rate of information by which it will transfer
from one section to another section. In the current period, it will get maintained by
designing advanced software program such as HADOP HPCC in the company. It is an
important term for a business to maintain the velocity of data that will systematically for
a higher term of success of the company.
The challenges of big data analytics
Big data analysis relates to the suitable section in the company. It has a fixed aspect, most
of the businesses in the present time utilise big data techniques. The management needs to
concentrate on big data to capture consumer for a higher time. In the present time, there are
several sorts of challenges that relate to big data that will maximise a constant basis (Singh,
2021). As it is an effective requirement for data analysis in respect to maintaining the consumer
data. In respect to handling the issues that are linked to big data analytics, the business should
develop an in-depth analysis of abilities by taking the suggestions of IT experts. The basic
challenges in big data analytics are as follows - Data security - In the business of their techniques, data safety is termed a fundamental
challenge. It plays an effective role in maintaining and following it from a wider number
of sources. The investigator gathers the information from various points and it will be the
fundamental duty of the investigator to provide data security to their consumers. In the
present section of worldwide technology, there are various operations like malware and
spyware that will directly affect the overall data. Data complexity - Concerning managing the data complexity it is important for the
investigator to overcome the barriers and problems. The data is analysable and inflexible

in a varied section that makes it hard for the investigator to maintain the data. It will
directly relate to the major challenge because of its ethical course of work by IT experts
in the management to control the data complexity.
 Maintaining quality Data – By having an effective term of the data, it will be difficult
for the management to be get managed. It involves clean up for duplicates, errors,
absences, issues, and uniformity (Wahab, and et.al., 2021). As on the other side,
management is outlay a high section of the time than on eliminating such issues.
The techniques that are currently available to analyse big data
 Data mining - It is a frequent method that is utilised by the management to manage big
data analytical. The data mining pulls out various sections from a larger set of data. It
accumulates the approaches from applied terms and machine learning in the division of
the business.
 Machine learning – It will relate to the message that is directly linked with AI, machine
learning that is generally linked with the concept of computer science and algorithmic
program. It also offers several analyses that follows several orientations.
 Statistics - The technique involves the procedure, maintaining and evaluating this data
that is a globally diverse and expandable field of structure that grows and develops with
definite time (Wang, and et.al., 2021). Techniques that follows the structure and size are
valuable. It supports in maintaining accurately and efficiently and can present the
management, products and market presentation.
How Big Data technology could support business, an explanation with examples
In the present dynamic situation, such sort of technique supports the management to
develop rapidly by offering the management in maintaining past informations of consumers.
Various organisation can create competitive advantages with the help of big data techniques. The
big data techniques will help in managing the management concerning the factors that are as
follows - Management of data – It will supports managing the data that support the management
in an organised way. The big data technique utilises broad status of software program and
sections that might be easy for the management to maintain higher manner of the
information. The data that is managed by the big data technology, is accessible for
business for effective period of the time. It supports managing the consumers as

effectively. For instance, Tesla is an international UK based car management that
maintained a large section of data in diverse parts with the support of big data techniques. Privacy of data – It is essential for the businesses and consumers within field of area. By
using the course of activities in the technologies, it plays an essential role in managerial
growth by managing the privacy of data of consumers (Wong, and Wong, 2021). It will
increase the sections of consumers by managing the secrecy wider term of the data. For
instance, Sainsbury, which is multinational retail organisation that manages its personal
section of data with the aid of big data techniques.
 Customer engagement – Consumer engagement supports by big data techniques. As it
will support in synchronism of the data. It is a basic manner of functions of Informatics
practising division in the management to maintain data as per to the number of
consumers. Consumer involvement is a fundamental precedence of every management,
hence big data techniques will also support in maximising the worth of management by
maximising consumer satisfaction as it will create consumer belief in the management
(Zhen, 2021). For example, ASDA is an international retail management, management
that is effectively attained customer involvement and contentment with the support of big
data technologies.

Poster

CONCLUSION
From the above-mentioned report, it has been concluded that big data is a wider section of the
information of their clients that are useful for the investigator and the management. The big data
techniques also support the investigator in maintaining a higher number of data that are utilising
suitable approaches. The investigator also covers effective sections to defeat several challenges
and issues that are linked with the big data technology to deal with various issues. It also covers
the significance of big data techniques and their application in the management for speedy
functioning.

REFERENCES
Books and Journals
Anatolyevich, A.A. and Mikhailovich, P.A., 2021, February. Application of big data in
engineering industry. In AIP Conference Proceedings (Vol. 2318, No. 1, p. 070001).
AIP Publishing LLC.
Chen, K. and He, J., 2021, February. Big-Data-Based Research on the Architecture Design of
University Hydropower Intelligent Decision Service Platform. In 2021 9th International
Conference on Communications and Broadband Networking (pp. 1-5).
Pop, F., 2021 Big Data Platforms and Applications (Doctoral dissertation, School of Electronic
and Information Engineering, Soochow University, Suzhou).
Singh, H., 2021. Big data, industry 4.0 and cyber-physical systems integration: A smart industry
context. Materials Today: Proceedings, 46, pp.157-162.
Wahab, S.N., and et.al., 2021. Big data analytics adoption: an empirical study in the warehousing
sector. International Journal of Logistics Systems and Management, 40(1), pp.121-144.
Wang, J., and et.al., 2021 Application of Big data scientific research analysis platform in clinical
medical research. Journal of Intelligent & Fuzzy Systems, (Preprint), pp.1-12.
Wong, K.Y. and Wong, R.K., 2021. Big data quality prediction informed by banking
regulation. International Journal of Data Science and Analytics, pp.1-18.
Zhen, C., 2021. Using Big Data Fuzzy K-Means Clustering and Information Fusion Algorithm in
English Teaching Ability Evaluation. Complexity, 2021.