Big Data Analysis - Techniques, Characteristics, Challenges and Applications

This report provides an overview of big data technology, its characteristics, techniques used in big data analysis, challenges faced in big data analytics, and how big data technology supports businesses. It also discusses the importance of data security, privacy, and complexity in big data management.

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Big Data Analysis
Introduction
Big data technology is considered as large set of data
belonging to different customers in a business. It is
essential and compulsory for a business to maintain big
data technology in order to grow at marketplace (Choi,
2018). A company has to develop good software for
handling major operations related to big data
technology. In this report there is a precise explanation
of big data technology along with its characteristics.
This report contains explanation of various challenges
that are effective in analysing big data and various
techniques available to analyse big data. This project
also contains the way in which big data technology can
support a business.
In today's competitive world big data technology is emerging with a
boom that is creating a huge impact on IT industry. The example of
Big Data technology is Hadoop, Spark, NO-SQL, Hive and Cloud.
These technological software helps in storing and managing big data
related to a business. The big data technology also includes
assessment of various factors that like data management and data
storage that are essential for growth of a business and develops
synchronisation of big data. There are majorly two types of big data
technologies which are operational and analytical big data
technology (Du, 2021). It is main work of IT department in a
company to analyse and store big data in a precise way to support
company operations. Big data technology is also helpful in
increasing the level of safe operations which are essential for a
business to develop big data related operations. The big data
technology is considered as major step which is essential for
protecting crucial data related to customers. In the success of a
company at the marketplace big data technology play a crucial role
by giving priority to large data management in a precise manner.
A brief overview of big data
Techniques to analyse big data:
Techniques used in big data analysis:
It is essential for a company to identify various factors that are
related to big data technology in order to accomplish success at the
marketplace. The major characteristics of big data technology are
mentioned below:
• Volume of data- In general case related scenario, it is
essential for a company to develop precise approach in handling
large amount of data. Big data's volume is large and number of
consumers is always high in case of multinational and national
companies. In order to handle large volume of data which is
essential for a company it is major responsibility of a business to
hire skilled and trained employees.
• Variety of data- The variety of data is immense in case
of big data technology which is essential to be maintained in an
effective manner it includes categories of data (Liu, 2018). In order
to make sure that the variety of data is transferred in a precise
manner, a company has to do various tasks like financial
management and business strategy preparation.
• Velocity of data- It is considered as the speed of data
through which it is transferred from one source to another. In the
recent times velocity of data is managed by advanced software like
HADOP HPCC in the business. It is very much essential for a
company to manage velocity of data consistently for long term
success of business.
Characteristics of big data

Big data technology and its application in a business is
irreplaceable in nature, most of the companies in recent
times use big data technology. It is important for a
business to focus on big data for long term customer
satisfaction (Singh, 2019). In the recent times challenges
related to big data are increasing day by day so there is a
strong need for data analysis in order to manage
customer data. In order to tackle challenges related to
big data analytics the management should create an in
depth analysis of capabilities by taking advice of IT
experts. The main challenges in big data analytics are
mentioned below:
Data integration- In the management of big data
technology data integration is considered as a major
challenge. The data integration plays a crucial role in
managing data from large number of sources. A
researcher collects data from many sources and it
becomes major responsibility of a researcher to facilitate
data integration.
• Data complexity- In order to handle data
complexity, it is essential for a researcher to overcome
several issues and practices (Singh, 2019). The data is
complex and rigid in many cases which makes hard for
researcher to handle data. Data complexity is a major
challenge and it is ethical duty of IT experts in a
business to handle data complexity.
Data security- The main issue and challenge in data handling and
maintenance is data security. It is major role and responsibility of
management to handle data security with major patience in order to
manage security of data. In the world of technology there are many
attacks like malware and spyware can impact whole data. It is
important for researcher to analyse and develop big data while
keeping mind various security issues. Value: It refers to advantages
that a company derives from the data. It doesn't matter how rapidly
data is producing, but it should be useful and reliable.
The techniques available to analyse big data are mentioned below:
•Data mining- The data mining is a common tool used by a business
to handle big data analytics. The data mining extracts patterns from
large data set combining methods from statistics and machine
learning within the database management.
•Machine learning- This message is related to artificial intelligence,
machine learning is mainly related with the dimension’s computer
science and algorithms. The machine learning also provides various
analysis that are based on various perspectives.
•Statistics- The technologies that process, manage, and analyse this
data are of an entirely different and expansive field, that similarly
evolves and develops over time. Techniques and technologies aside,
any form or size of data is valuable. Managed accurately and
effectively, it can reveal a host of business, product, and market
insights
Challenges of big data analysis: Big data technology could support business
In current competitive environment the big data
technology helps a business to grow at a faster pace by facilitating
a company in handling precise data of customers (Siyuan, 2018).
Many business organisations can develop competitive advantage
with the help of big data technology. The big data technology is
helpful in supporting a business with the help of following factors:
• Management of data- Big data technology helps in
management of data which is useful for the business in a
systematic manner. In big data technology use of advanced
software and systems makes it easy for business to manage large
amount of data. The data which is managed by big data
technology, is available for a business for a long time which helps
in customer handling. For example, Morris Garages is a
multinational UK based car company which precisely manages
large amount of data in different parts of globe with the help of big
data technology. How big data technology supports business:
• Privacy of data- The privacy of data is also important for
both company and customers in a major sense. Use and application
of big data technology play a major role in business development
by maintaining privacy of data of customers. This increases faith
of customers by maintaining privacy of large amount of data. For
example, Astra Zeneca which is a British multinational
pharmaceutical company maintains privacy of data with the help of
big data technology.
Big Data Analysis
Challenges of big data analytics