Big Data Analysis and its Features: Challenges, Techniques, and Benefits for Organizations

Information System
and Big Data Analysis

INTRODUCTION
Big data analysis is a large volume which to not easy to handle. It is combination which
structured and unstructured that flocks the company on daily basis. Bid data is used to interpret
the vision that is working for the accomplishment of good decisions in the further actions of the
company. It is also difficult in nature, in the coming time the basic idea of big data has been
reached out to a point in order to approach and stock large mass of information for the analytics.
In the following task, an explanation on big data with its features is being discussed. There are so
many challenges that are include in the the big data analytics that are also essential to be
understood. Furthermore, the main methods which are there to interpret and analyse big data is
also determined. Lastly it covers the point the points which explains how big data technology
could assist organisations(Sreedevi And et. al., 2022).
TASK
Big Data and features.
Big data is defined as an aggregate of data acquired by businesses in order to fine-tune it
for useful information and use in predictive sculpture, machine acquisition forecasts, and other
modern analytics applications. Data might be structured, semi-structured, or unstructured. It has
a lot of mass and has been performing well for a long time. Because of the volume and
complexity, none of the traditional data management technologies can handle it or store it in a
timely manner. It entails a large volume of data, social media analytics, data extraction
capabilities, and real-time data. The action of studying a large volume of data is known as big
data analytics. There is a large amount of mixed digital data. It's all about data size and enormous
data sets,' which sounded like a computer memory unit and a terabyte. This design is all about
Huge Data, and when big data is evaluated, the data is proclaimed as Big Data analytics. Big data
examples include the New York Stock Exchange (NYSE), smartphone apps, and social media
sites like Facebook(Srivastava and Maurya, 2022).
Characteristics of Big Data
 Volume: As the name implies, the volume of big data is continually increasing. When
determining the value of data, the magnitude of the data is critical. Furthermore, whether
the data is independent or not is determined by the amount of data. One of the hallmarks
of large data is its volume(Abanumay and Mezghani, 2022)

 Variety: It simply refers to the structure, semi-structuredness, or unstructuredness of
data. Data is now available via email, Google Sheets, and other platforms, resulting in a
greater diversity than in previous years. Unstructured data comes in a wide range of
formats, each with its own set of challenges, such as analysing it, storing it, and so on.
 Velocity: Simply said, velocity refers to the rate at which data is generated in an
organisation. An significant aspect with regard to data is how quickly information is
processed in order to meet the demands of consumers, as this demonstrates the data's
potential.
 Variability: This simply refers to the data's inconsistency, which can wreak havoc on
the process of successfully and efficiently managing the data(Başak, Kılınç and Ünal,
2022).
Challenges of Big data analytics
There are some of the challenges of big data analysis that have all the appropriate ways of
dealing with the large volume data and it involves the function of holding the data, examining
the big volume of information on some kind of data. In context to the big data, there are some of
the challenges that are important to be considered and they are as follows:
 Lack of knowledge professionals: In the big and international companies there are so
many of the data in the company that is being used in the company working and to
maintain the data, the company need to have some of the data analysing experts who are
just best in the management and interpretation of the data. And some of the experts
include data scientists, engineers who will be the people who will use some of their skills
and manager that big data of the organisation.
 Lack of proper knowledge of massive data: When the company is having so much o
the data about the transactions and dealings of the company and this is because of the
inefficiency of the employees of the company, they are not able to identify the proper
processing of the data, where the data is stored and major importance of the sources of
the company. When the workers of the organisation don't know the importance of
knowledge storage then they will not be capable to maintain the confidential data(Shah,
2022).
 Integrating data from a spread of sources: There are the information of the data which
is collected from various sources like social media, applications, financial reports, e-