Information Systems & Big Data: Business Support and Challenges

This case study provides an overview of big data, its characteristics (volume, velocity, value, variety), and its application in various industries. It discusses the challenges associated with big data analytics, including data consolidation, statistical analysis, A/B testing, machine learning, and data mining. The study highlights how big data technologies support businesses by enhancing product quality, ensuring data security, and improving decision-making processes. Examples of companies leveraging big data are provided, along with references to relevant research and publications. Desklib offers this and many other solved assignments for students.

History on big Data
Big data is a form of technology which is used in storing,
analyzing and managing the massive data. The case study
describe about the combination of a structured and
unstructured or semi-structured part of detail collected
by the firm which is mainly used in many kind of
projections it includes acquisition of machine operations,
forecast modeling etc. They also assists the organization
to manage a big amount of information
Information Systems and Big Data Analysis
Name of the Student
What is big Data
The company big data involves big detail, bunch of tough data,
significantly gathered from innovative or new origins. These
kind of information have a combination of some variety of data;
It also have a high volume and velocity. This case study includes
four V's that shows velocity, volume, value and variety. It gives
power to the firms to create profit based decisions.
Characteristics of Big data
There are some illustrative examples of companies that utilize
big information technologies and it involves agriculture,
pharmaceuticals,etc. The important features of big information
are explained under:
• Velocity: It express the value of speed at which data is
gathered, elaborated the flashy information.
• Value: This is the important part of big information. It
confirm that the gathering of information is equalizing with
the firm's necessities or not.
• Volume: The information of big data is always come in
large amount and it gathered in from of raw data. It cannot
be used instantly.
• Variety: It express the information which is mainly recorded
by the machine or person in semi-structured or unstructured
way for some particular reason.
The challenges of big data
analytics
There are various challenges of big data which can be
explained as given below:
Union and consolidation of data: This process is the
collection of many methods it mainly examine the
information from collective origins and matters.
Statistics: It is a very similar technique which is used in
analytics of big data that involves aggregation,
interpretation, firm and summarize the information.
A/B testing: In this technique it includes comparison
between the power of association, in order to determine
what changes will raise the available objectives.
Learning through machine: This is the current part to
examine the information.
Data mining: It mainly remove the design of big
information bunch by connecting methods from statistics
and technological learning, within the system of database
Alavi, A. and Buttlar, W.G. eds., 2018. Data Analytics for
Smart Cities. CRC Press.
Cooklev, T and et.al., 2018. Enabling RF data analytics
services and applications via cloudification. IEEE
Aerospace and Electronic Systems Magazine. 33(5-6).
pp.44-55.
Fugini, M., Finocchi, J. and Locatelli, P., 2021. A big data
analytics architecture for smart cities and smart
companies. Big Data Research. 24. p.100192.
Gökalp, M.O and et.al., 2019, November. Open-source big
data analytics architecture for businesses. In 2019 1st
International Informatics and Software Engineering
How Big Data technology could
support business & Examples
• Enhance the product quality: Big data help in
analyzing the demand of the consumers which help to
improve the quality of existing product. It also
suggests the company to launch new product to meet
consumer wants. Big data provide support in that
areas where company is lacking.
• Data safety and security: Big data ensure that the data
is stored at a place where it is secured and protected
from the various risks, frauds and hacking.
Techniques that are currently
available to analysis big data
•Raise the quality of good: It mainly assist in examining the
customers demand which assist to better the quality of
available good. They also recommend the firm to introduce
new goods to achieve the customer desires. It provide helps
in that fields in which firm is deficit.
•Security and safety of information: It is confirmed that the
information is protected at a place where it is kept and
secured from many risks, hacking and frauds. Information is
protected below more technologies which assist the company
run without any mistake(Oneto and et.al., 2020).
•Good decision making: Data methods assist in bettering the
company decision making procedure in respect to increase