Information Systems and Big Data Analysis - Desklib

This presentation discusses the history, challenges, techniques and characteristics of big data analysis. It highlights the features of big data such as velocity, volume, variety, validity, volatility, visualization and veracity. The presentation also covers the challenges faced by companies in choosing the right tools and professionals to operate big data tools. It also explains how big data supports businesses by observing customer behavior and providing insights to design products as per their choice. Techniques such as machine learning and social network analysis are also discussed. The presentation is relevant to PRO369 Information Systems and Big Data Analysis course.

History on big Data
Big data can be defined as combination of both structured
and unstructured data which is collected by the company
so that the best decisions can be taken for the purpose of
better optimization of large data. The report is going to
highlight the various features of big data such as velocity,
volume, variety, validity, volatility, visualization and
veracity (Hopkins and Hawking, 2018).
Information Systems and Big Data Analysis
Name of the Student
What is big Data
Big data is said to be the combination of data which is huge in
volume and it is further divided into structured and unstructured
data. Big data is also connected from various information that is
from websites, social network, questionnaires, product purchase
and many others. As the concept is new it consists of three key
actions such as integrate, manage and analyse.
Characteristics of Big data
Volume of data- As the name suggests, it is
enormous in size and the information is collected from
various sources such as machines, networks, human
interactions and social media platform.
Variety of data- The data can be collected from various
sources that can be in the form of structured,
unstructured and semi-structured such as Emails, audios,
photos, videos and many others.
Veracity of data- As the big data is reliable and there are
different ways to translate the data that makes it more
easier to handle the data efficiently.
Value- It is one of the main feature of the big data that
can be valuable, reliable and that can also be stored,
processed and analysed.
Velocity
big data assists with the speed at the data that flows
from different sources such as application logs,
processes, networks, mobile devices, sensors and many
others.
The challenges of big data
analytics
One of the main challenge is that company may find it
difficult to choose and select the best tool for the purpose
of analysing and storing the data.
Professionals such as data analysts and data scientist may
find it difficult to operate the tools of big data and also
there is shortage of such professionals because the tools
of the big data have evolved rapidly.
Another challenge can be the security of such data as the
company is busy in understanding and analysing the data.
References
Choi, T.M., Wallace, S.W. and Wang, Y., 2018. Big data
analytics in operations management. Production and
Operations Management, 27(10), pp.1868-1883.
Dey, N., Das, H., Naik, B. and Behera, H.S. eds., 2019. Big
data analytics for intelligent healthcare management.
Academic Press.
How Big Data technology could
support business & Examples
Big data allows to observe the behaviour of the customers with
the help of online preferences. As all the customers are unique as
they all have their own choices that keeps changing as per new
trends and preferences. Big data supports in keeping the data
safe as it has more professionals to guard the data by managing
the big data to reduce the level of risk and safeguard the sensitive
data. Big data allows to gather the large data of the customers
and get the digital footprints about the buying behaviour of the
customers in order to provide the scope to design the products as
per their choice. As the quality products are offered to the
customers then the customers will be keep coming back to the
same company.
Techniques that are currently available to analysis big data
Machine learning helps in improving the overall experience with the help of using the data and it allows to distinguish between
spam and non-spam email messages.
Social network analysis is one of the technique which is used to analyse the big data and it is used to evaluate the relationships
and communications. It also allows to identify the critical issues in the organisation