NEED APA formatFinal Research Paper:
This final research paper is a team project. Students are randomly grouped in iLearn. Please
check the Group area to check your assigned group. The contributions of all team members to
the assignment must be posted in the team’s study group conference. The study group discussion
forum is the place for the instructor to ascertain each team member’s contribution and
participation. If students use other methods for collaboration, they should first get permission
from their instructor, and then clarify in the study group discussion area each member’s
contribution by posting copies of all electronic communication and collaboration in case of a
future dispute.
At the end, students will submit peer assessment form rating self and team members. Those team
members contributing less than their fair share of effort will see their individual grades reduced
accordingly.
Each teams is required to complete this two-part final research project as follows:
A. Research Paper Proposal:
Prior to writing your Final Research Paper, each team is required to develop a research proposal.
The research paper proposal should state what research question will be answered (or what
research problem will be addressed) by the analysis your paper proposes to perform. In
other words, your proposal should define the focus of the paper by stating a research
question or describing a research problem to be analyzed in relevant to key topics covered in
this course. It should also explain what types of resources and references will be used to
perform the analysis to answer your selected research question or address the stated research
problem.
To begin your preliminary literature search, the proposal will include a preliminary list of at
least three (3) relevant references from credible peer reviewed sources. Papers you select must be
current, published since 2014. The UC Library provides myriad of online resources to assist
students with proper research. It is anticipated that reputable Internet sources will also be
helpful and appropriate. The proposal should not exceed two (2) pages.
Instructor will review and provide feedback to each group on their research proposals. The
purpose of instructor’s feedback is to provide comments on the appropriateness of your proposed
topic, topic’s coverage (both breadth and depth), as well as research approach, sufficiently early
in the course to allow for topic revision if necessary.
Please submit it via your assignment folder as a Microsoft .doc attachment by the end of week 3
Session.
B. Final Research Paper
The length of final research paper must be at least 1800 words. The paper must follow the
American Psychological Association (APA) style of writing. Use double spaced APA style.
Ensure to include at least six (6) APA-compliant references and corresponding in-text citations.
Most references must be current/recent, published since 2014.
Papers must include a Cover Page, Table of Contents, APA compliant in-text citations and list of
References, and page numbers. The word count begins with the Introduction and ends with the
Conclusions and Recommendations.
The emphasis of paper must be analytical, i.e. the paper should pose a research question or
problem, and attempt to answer the question or problem with an analysis of available sources and
reference material, as well as team members’ own perspective(s).
Research paper must NOT seek merely to summarize the relevant details of a topic, even if that
topic is new to the writer. The value in this assignment is in reaching a sufficient understanding
of a set of material to allow you to provide an informed opinion on some application of the
material to a specific issue.
The Final Research Paper will be graded against the following criteria:
 Clear research question or research problem statement to be analyzed and
its relevance: 15%
 Content (depth and accuracy of information and analysis): 40%
 Recommendations and conclusions supported by research and analysis: 15%
 Clarity, Organization, grammar and spelling: 15%
 APA Style: 15%
Each group will submit their research proposal and final research paper as a group. Please be
sure to spell check and carefully proof read your paper prior to submitting it.
Check for plagiarism BEFORE submitting!! Submit your paper to Safe Assign. Safe Assign will
be used to analyze each paper for any plagiarism. For guidance to avoid plagiarism, please check
Content>Week 1: Getting Started folder.
final_research_paper.pdf
big_data__research_paper.docx
Unformatted Attachment Preview
Final Research Paper:
This final research paper is a team project. Students are randomly grouped in iLearn. Please
check the Group area to check your assigned group. The contributions of all team members to
the assignment must be posted in the team’s study group conference. The study group discussion
forum is the place for the instructor to ascertain each team member’s contribution and
participation. If students use other methods for collaboration, they should first get permission
from their instructor, and then clarify in the study group discussion area each member’s
contribution by posting copies of all electronic communication and collaboration in case of a
future dispute.
At the end, students will submit peer assessment form rating self and team members. Those team
members contributing less than their fair share of effort will see their individual grades reduced
accordingly.
Each teams is required to complete this two-part final research project as follows:
A. Research Paper Proposal:
Prior to writing your Final Research Paper, each team is required to develop a research proposal.
The research paper proposal should state what research question will be answered (or what
research problem will be addressed) by the analysis your paper proposes to perform. In
other words, your proposal should define the focus of the paper by stating a research
question or describing a research problem to be analyzed in relevant to key topics covered in
this course. It should also explain what types of resources and references will be used to
perform the analysis to answer your selected research question or address the stated research
problem.
To begin your preliminary literature search, the proposal will include a preliminary list of at
least three (3) relevant references from credible peer reviewed sources. Papers you select must be
current, published since 2014. The UC Library provides myriad of online resources to assist
students with proper research. It is anticipated that reputable Internet sources will also be
helpful and appropriate. The proposal should not exceed two (2) pages.
Instructor will review and provide feedback to each group on their research proposals. The
purpose of instructor’s feedback is to provide comments on the appropriateness of your proposed
topic, topic’s coverage (both breadth and depth), as well as research approach, sufficiently early
in the course to allow for topic revision if necessary.
Please submit it via your assignment folder as a Microsoft .doc attachment by the end of week 3
Session.
B.
Final Research Paper
The length of final research paper must be at least 1800 words. The paper must follow the
American Psychological Association (APA) style of writing. Use double spaced APA style.
Ensure to include at least six (6) APA-compliant references and corresponding in-text citations.
Most references must be current/recent, published since 2014.
Papers must include a Cover Page, Table of Contents, APA compliant in-text citations and list of
References, and page numbers. The word count begins with the Introduction and ends with the
Conclusions and Recommendations.
The emphasis of paper must be analytical, i.e. the paper should pose a research question or
problem, and attempt to answer the question or problem with an analysis of available sources and
reference material, as well as team members’ own perspective(s).
Research paper must NOT seek merely to summarize the relevant details of a topic, even if that
topic is new to the writer. The value in this assignment is in reaching a sufficient understanding
of a set of material to allow you to provide an informed opinion on some application of the
material to a specific issue.
The Final Research Paper will be graded against the following criteria:





Clear research question or research problem statement to be analyzed and
its relevance: 15%
Content (depth and accuracy of information and analysis): 40%
Recommendations and conclusions supported by research and analysis: 15%
Clarity, Organization, grammar and spelling: 15%
APA Style: 15%
Each group will submit their research proposal and final research paper as a group. Please be
sure to spell check and carefully proof read your paper prior to submitting it.
Check for plagiarism BEFORE submitting!! Submit your paper to Safe Assign. Safe Assign will
be used to analyze each paper for any plagiarism. For guidance to avoid plagiarism, please check
Content>Week 1: Getting Started folder.
The Effectiveness of the Big Data Technologies
In the Modern World
Presented By:
Samyuktha Varaganti (Student ID: 002832342)
Venumadhavi Suri (Student ID: 002860384)
Vijitha Gaddampalli (Student ID: 002833228)
Raju Shivanadula (Student ID:00283
Rajesh Singirla (Student ID: 003015226)
Course: ITS-832-14
Date: 12-08-2019
Present To & Guided By:
Professor: Dr. Amjad Ali
Table of Contents
Definition of Bigdata ………………………………………………………………………………………………………………….. 1
The Effectiveness of Big Data Technologies in the Modern World ……………………………………………….. 2
Big Data and 5 Vs…………………………………………………………………………………………………………………… 3
Big Data Management ……………………………………………………………………………………………………………….. 4
Big Data Analytics……………………………………………………………………………………………………………………… 5
Policy making with Big Data ………………………………………………………………………………………………………. 6
Ownership on the data……………………………………………………………………………………………………………. 7
Data-Driven Policy making …………………………………………………………………………………………………….. 7
Centralized plan of System……………………………………………………………………………………………………… 7
Decision Making Framework: ……………………………………………………………………………………………………. 8
Big data Decision Making Process …………………………………………………………………………………………… 8
Big data governance of Policy making ………………………………………………………………………………………… 8
Game Theory of Big Data in AI Applications ……………………………………………………………………………… 9
Effectiveness of Big-Data Computing in ecommerce, science, and society: ………………………………….. 10
Limitations in Decision making with Big Data …………………………………………………………………………… 12
Technology and Application Challenges ……………………………………………………………………………………. 13
High-speed networking …………………………………………………………………………………………………………. 13
Cluster computer programming: ………………………………………………………………………………………….. 13
Security and privacy: ……………………………………………………………………………………………………………. 13
Conclusion ………………………………………………………………………………………………………………………………. 14
References ……………………………………………………………………………………………………………………………….. 15
1
Abstract
Big Data is extremely large or complex set of data which is difficult to process it using
traditional database and software techniques. 2.5 quintillion bytes of data is being generated
every day from different sources like social media, music, sports, online shopping and many
other smart phone applications in this modern world. Data needs attention because companies are
capturing the growing data that streams into their businesses. Various analytics are being used
for significant value from it with better speed and efficiency. There are a lot of Big Data tools, all
of them help the user in some or another way in saving time, money and uncovering business
insights. Many business organizations want to find new business opportunities such as fraud
detection, customer sensitivity analysis, and new product offerings while some other business
organizations are still pondering the long-term value of big data investments. Business leaders
and managers want to be sure that big data projects can deliver true value and provide long term
benefits. This paper provides an account of how recent big data project initiatives have been
successful in delivering business value and highlights what technology solutions are primarily
used by those big data projects.
Keywords: Analytics, Big data, Computational social science, Data analytics, Interdisciplinary
research, Managerial decision-making, Paradigm shift
Definition of Bigdata
Big Data has received an awful lot interest from the academia and the IT industry. In the virtual
and computing global, statistics is generated and gathered at a price that unexpectedly exceeds
the boundary range. As statistics is transferred and shared at light pace on optic fiber and Wi-Fi
2
networks, the volume of records and the speed of market increase growth. However, the fast
increase fee of such large facts generates several challenges, including the speedy boom of
records, transfer speed, diverse facts, and safety. Nonetheless, Big Data continues to be in its
infancy degree, and the domain has no longer been reviewed in well known. Hence, this have a
look at comprehensively surveys and classifies the various attributes of Big Data, including its
nature, definitions, rapid growth rate, extent, control, analysis, and security. This take a look at
additionally proposes a information life cycle that makes use of the technologies and
terminologies of Big Data. Future studies guidelines on this subject are determined based totally
on possibilities and several open problems in Big Data domination. These research guidelines
facilitate the exploration of the domain and the development of foremost strategies to address
Big Data.
The Effectiveness of Big Data Technologies in the Modern World
“Each methodology has its strengths and weaknesses. Each approach to data has its strengths
and weaknesses. Each theoretical apparatus has its place in scholarship. And one of the biggest
challenges in doing interdisciplinary work is being able to account for these differences, to know
what approach works best for what question, to know what theories speak to what data and can
be used in which ways.”
Introduction
Due to the enhancement of technology, a huge amount of data is being generated every minute.
This data is not in a format that our relational database can handle, on the other hand, even the
volume of data has also increased exponentially. In the early technology, the data was stored in a
traditional way which was very difficult to maintain. Nowadays, the data is getting generated
3
from various sources like social media, learning, retails, entertainment, government,
health/medical, social, finance, transportation etc., and is rapidly growing every minute.
Maintaining this humongous amount of data using different technologies plays a key role in this
paper.
Big Data has been defined in terms of the five V’s (Russom, 2017, Chen 2012, Abdullah 2015),
i.e., Volume, Velocity, Variety, Veracity and Value
Big Data and 5 Vs
Volume: The quantity of generated and stored data. Zettabytes or Brontobytes
Variety: The variety of data such as blogs, social media, updates, pictures, videos, audio files,
etc.,
Velocity: Speed at which the data is generated, collected and analyzed at any given time
Value: The worth of the data being extracted
Veracity: The messiness or trustworthiness of the data that is being collected.
Technological progress has resulted in the fast development of computers and the computing
power has increased considerably. The infrastructure for analysis of big data is developing
rapidly and accessing the data has become ease from different sources. We really need advanced
technologies and infrastructures to analyze the data. Examining a large amount of data to
uncover the hidden parent’s correlation and other insights from the data itself.
Cost Reduction: Technology like Hadoop and Cloud based analytics brings significant cost
advantage storing large data.
4
Faster Better Decision Making: With speed of new analytical technology over big data, business
can analyze information immediately
New Product and Services: Big Data Analytics identifies customer’s needs and business can
create new products to meet those needs.
Big Data Management
The architecture of Big Data ought to be synchronized with the help infrastructure of the
organization. To date, all of the facts utilized by organizations are stagnant. Data is more and
more sourced from numerous fields which might be disorganized and messy, which includes
information from machines or sensors and large assets of public and private records. Previously,
maximum businesses had been unable to either capture or store these records, and available gear
couldn’t manage the information in an inexpensive quantity of time. However, the brand new Big
Data era improves overall performance, helps innovation in the goods and services of business
models, and gives decision-making assist. Big Data technology aims to reduce hardware and
processing fees and to verify the value of Big Data earlier than committing good sized agency
resources. Properly controlled Big Data are available, dependable, secure, and viable. Hence, Big
Data programs can be applied in various complicated medical disciplines (either unmarried or
interdisciplinary), together with atmospheric technology, astronomy, remedy, biology, genomics,
and biogeochemistry. In the subsequent phase, we in brief discuss facts management gear and
advocate a brand-new information life cycle that uses the technology and terminologies of Big
Data.
With the evolution of computing generation, massive volumes can be controlled without
requiring supercomputers and high price. Many equipment and techniques are to be had for
5
records management, consisting of Google BigTable, Simple DB, Not Only SQL (NoSQL), Data
Stream Management System (DSMS), MemcacheDB, and Voldemort. However, agencies should
expand unique equipment and technologies which can shop, access, and analyze huge quantities
of records in near-actual time because Big Data differs from the conventional records and can’t
be stored in a unmarried machine. Furthermore, Big Data lacks the shape of conventional
records. For Big Data, several the maximum typically used tools and techniques are Hadoop,
MapReduce, and Big Table. These improvements have redefined records management due to the
fact they effectively method huge amounts of information efficiently, value-effectively, and in a
timely manner. The following segment describes Hadoop and MapReduce in addition detail, in
addition to the various tasks/frameworks which might be related to and suitable for the control
and evaluation of Big Data.
Big Data Analytics
Big Data analytics helps us to predict and monitor the development of epidemics and disease
outbreaks in Healthcare industry. Because of computing power of big analytics, we can decode
the DNA in short period of time which can help find the new cure and predict disease pattern.
Some hospitals are using data collected from a cell phone app of millions of patients to their
patients rather than traditional lab tests. Big data technologies allow putting all data together and
then running the proper analytics and making use of massively parallel computing architecture.
Technological change plays a role
IT has improved the efficiency and effectiveness of organizations since the original
implementations of decision support systems (DSS) in the mid-1960s. Since then, new
technologies have been developed, and new categories of information systems (IS) have
6
emerged, including data warehouses, enterprise resourcing planning (ERP), and customer
relationship management (CRM) systems. The technologies have evolved and become
commoditized and less expensive and have delivered continuous increases in storage and
computing power. Moreover, the Internet revolution has had a drastic impact on business and
society, including the rise of social communication through e-mail, instant messaging, voice over
Internet protocol (VoIP) services, video conferencing, and other means.
To augment the growth of big data analytics development Intel® has joined Hadoop community
in offering enterprises the support of a big technology player in terms of its Hadoop distribution
software [24] along with a new generation of processors to provide performance in big data
processing and analyzing.
Intel’s proof of concept customer NextBio® confirmed software and hardware performance
improvements on its computing resources using the Intel Hadoop distribution. In big data,
predictive models are heavily used, and more new tools are emerging to open them up to new
users to apply to a varieties of use cases. In IBM, researchers are applying predictive analytics to
design diagnostics and evaluate treatments of patients at risk of heart failure as much as two
years ahead of time.
Policy making with Big Data
In education, security, and health care projects policy making is mandatory for this kind of
implementations Bigdata is very helpful in collecting raw data, storage and analysis. There are
couple of aspects which uses in policy implementation of bigdata.
Stakeholder’s Point of view: In the policy implementation public or citizens will play key role as
stake holders as they give credit card and sensitive information, while gathering this kind of
7
information public should be aware what kind of data government is pulling and they should
accept terms and conditions.
Ownership on the data
Public usually worried about the data responsibility for government gathered information. The
administration needs to give significant bits of proof with respect to the protection approach and
security of the information accumulated from the general public. (Ian Lustick, Sep 7 2015)
Individuals need to be guaranteed about who is controlling their data and how it is being utilized
Data-Driven Policy making
In Policy making, the significant focal point of the administration ought to be towards the
advantages for the general public. Nonetheless, their arrangements will be advantageous just
when they have right data accessible.
In this way, the objective ought not simply be moving towards huge information. The
administration needs to strategize powerful approaches to total right and top-notch information.
Centralized plan of System
For the big policy systems which are implemented through ABM methodology will help on
doing centralized system so that any kind of traffic flow communication will flow from
centralized systems to multiple systems all those are interlinked, and which provides a good
behavior in policy making.
8
Decision Making Framework:
1.What kind of opportunities big data may provide for analysts to get information and to get
better data to leaders? (Ian Lustick, Sep 7 2015)
2.What kind of opportunities may enormous big data give chiefs to more likely assimilate data
from information investigators? (Ian Lustick, Sep 7 2015)
3. What openings may enormous information give informat …
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