MAN421 MIS Homework: Exploring Big Data Reliability and Definitions

This homework assignment for Prof. Eshra's MIS—MAN421 course defines essential terms like application software, operating system, binary system, CPU, dual processor, and database concepts such as field, file, table, and primary key. It also includes a case study analysis on the reliability of big data, discussing its benefits in areas like business, education, science, law enforcement, sports, and healthcare. The analysis covers the successes and failures of big data applications, highlighting the importance of data quality, context, and proper planning. It also addresses limitations such as the focus on correlations rather than causation, outdated modeling techniques, and privacy concerns, emphasizing the need for a balanced understanding and secure implementation of big data technologies. Desklib provides access to more solved assignments and study resources for students.

Prof. Eshra MIS—MAN421
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Name:______________________________ Ch. 5 & 6—Homework
Part I: Define the following terms
Application software : These are the groups of programs which are designed for end users. Ex:
Hadoop.
Operating system (OS): It is a system software which acts an interface between user and the
system. Example: Microsoft Windows XP, Linux, etc.
Binary system: This is the number system using two individual values for representation of data
and codes.
CPU: The mode of processing in a computer is initiated by a specific unit, called the Central
Processing Unit (CPU), which controls data flow and instructions inside a computer system, and
heavily relies on the chipset.
Dual processor: The operation of two processors under the techniques of multiprocessing to
work in tandem is known as Dual processor. It helps in faster performance of a machine than a
single usage of a processor.
Horizontal-market application: It is an application software which increases the productivity of
an organization in a respectable market with the scopes, which are just opposite of the vertical
market’s.
Vertical-market application: This is the application software which maintains the productivity of
an organization with respect to the usefulness scope’s limitation to a small amount of industries.
Virus: Viruses in a computer are malicious and harmful software which replicates itself through
modification of programs and insertion in its own code.
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Prof. Eshra MIS—MAN421
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Database: The collection of different information is structurally organized for ease of access,
management and updates in a specific storage space are called the database.
Field: Relational database’s data has multiple parts, which are known as record, which are again
divided into further sub-records, known as Fields. Each record has several fields.
File: A file is a collection of records.
Table: In databases, tables are the sets of data elements which uses the structure of horizontal
rows and vertical columns. Numbers of columns are specified, whereas number of rows are
numerous.
Primary key: It is a unique record in a database. It is also known as the unique identifier.
Example: Roll number, license number, etc.
Part II: Case Study Analysis:
Read case study “How Reliable Is Big Data?” at the end of Chapter 6 and answer the questions
that follow.
6-13.
Big data is one of the emerging technologies in the modern world, which has significant benefits
to the organizations who utilize the technology. The benefits to the multiple organizations are
solely related to the organization’s performance and decision making processes. One of the
evident examples to the decision making feature of the respective technology is Spotify’s
generation of products according to the previously recorded user’s preference. This boost
business performance, also. Additionally, the software system’s predictive behavior is evidently
beneficial in the political stages. The winning of Barack Obama during the time period of 2008-
2012 was hugely influenced by the usage of the respective software. Apart from businesses, big
data provides profitable outcomes in the fields of:
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Prof. Eshra MIS—MAN421
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Education: Admission rate, Student-Teacher analysis and other academic predictions.
Science: Research analysis, calculative monitoring (Clifford 28), weather predictions and others.
Law enforcement: Crime rate analysis, crime hotspots and other identifiable informations.
Sports: Athlete recruitment decisions contractual sport’s concussions and enhancement of fan’s
experiences (Robert & Memmert 1410).
Healthcare: Determination and analysis of common diseases and personalized health
recommendation to patients.
6-14.
Big data is used to analyze huge chunks of information. Thus, the use of the technology is
essentially mentionable in the political field. The use of the technology during the victories of
Barack Obama, during the time period of 2008-2012, had played a large role in prediction of the
consumer behavior and the party had taken future procedures, accordingly. However, the same
had opposite impacts during Hillary Clinton’s election time, as there were absence of specific
context to the predictive models. The success rate of the Big data is directly depended on the
quality and quantity of input data, that needs to be processed (Chen, Chiang & Storey 36).
Mentionable benefits are observed in the Crime investigation departments of New York, where
CompStat crime-mapping program analyzes the citywide databases to record and determine the
crime rates. Nowadays, healthcare services are also inheriting big data for effective and
economical treatment’s determination and further recommendations.
Also, Meridian Energy Ltd.’s case of primitive modeling produced failures to accurate
recommendations (equipment failure). Relatable issues are found to occur in the multinational
organization of Google, where calculation of ‘influenza flu’ patient rate in US was recorded to be
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Prof. Eshra MIS—MAN421
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twice the actual numbers. The algorithm missed the search result’s context, as only the numbers
were considered, during the calculative procedure.
6-15.
The technological field of Big data is useful to the modern world due to the rich predictive
nature of the program. However, it also poses few limitations to the organizations and other
users, which are essentially addressed as:
 Studies suggest that many companies have already tried to utilize big data to initiate
huge data projects, without establishing the motive of the project, in the first instance.
Thus, without proper planning of the goal, the predictive nature of the big data cannot be
achieved successfully. To be clear, analysis of data is not directly relatable to the
achievement of goal, moreover, both are differently addressed in an organization.
 Big data analysis detects co-relations, than causation between the involved components.
The calculation from the relational aspects are maintained, however, the meaningfulness
of the relation is not stated. This requires knowledge of the business operation, which are
being solved with the big data analysis.
 Also, future predictions are affected in some cases, where the system may use outdated
techniques of modelling.
 Issues to privacy and information security also poses challenges, which further becomes
a reason for limitation to the Big data’s usage.
6-16.
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Prof. Eshra MIS—MAN421
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The analysis of the case study is targeted to influence the minds of people towards the
knowledge of Big data and its usage. Moreover, the technology is sufficiently recommendable to
be used in all of the organizations, as it has outcomes that enhance the decision making and
productivity of the business. The predictive nature already influences fields to sports, science,
law enforcement and others. Thus, the system has been seen to produce better results already.
However, the system also poses certain challenges that needs to be addressed. The
challenges are related to the privacy and information security. The manipulation of
organizational and consumer’s data can become an issue. The intermixed data of an
individual/organization to data from dissimilar sources produces exceptional information (user
may be unaware of the information) which can disturb the privacy of the involved personnel. The
vulnerability to such issues makes big data’s usage, a debatable one. However, the security
boundaries and maintenance in an organization are bound to resolve the privacy issues to Big
data’s implementation and usage (Zikopoulous et al. 176). Also, expectations of the
organizations should be relative to the quality and quantity of input, and involved individuals
should know that the big data initiates analysis which are co-relation oriented, rather than
causation’s. Therefore, corrective and appropriate understanding of the system will produce
benefits to any organization.
Page 5 of 6

Prof. Eshra MIS—MAN421
Type your answers in the space provided and upload as attachment by due date
No e-mail submissions/hard copies will be accepted
References
Zikopoulos, Paul C., et al. Understanding big data: Analytics for enterprise class hadoop and
streaming data. New York: Mcgraw-hill, 176 (2016).
Chen, Hsinchun, Roger HL Chiang, and Veda C. Storey. "Business intelligence and analytics:
From big data to big impact." MIS quarterly 36.4 (2015).
Lynch, Clifford. "Big data: How do your data grow?." Nature455.7209 (2018): 28.
Rein, Robert, and Daniel Memmert. "Big data and tactical analysis in elite soccer: future
challenges and opportunities for sports science." SpringerPlus 5.1 (2016): 1410.
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