ITS836 Residency Research Project & Presentation

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Assignment Type: Group Project

ITS 836 – Data Science & Big Data Analytics Research Project & Presentation
Project Description:

You are a team of Data Scientists working at a Large Corporation. I am the chief information

officer (CIO and President) of an organization that has contracted you to provide us with research

and presentation on the benefits that data science and big data analytics solution could have for

our organization. Our organization has provided you with access to our databases to aid in the

identification of potential benefits. In addition to providing a presentation on the general benefits

of data science, big data analytics, and proposing a solution (software tool), you will also need to

identify one major problem that your team has already identified as one that you propose that big

data analytics solution can solve. You should also provide at least five examples of the type of

information that your big data analytics solution can provide.

Part 1 – Research Paper

1. You can choose a real or fictitious organization as your case study organization, which will
represent where I am the CIO/President and to which you will be presenting as a Data

Scientist.

2. Choose at least one dataset as that which was provided to you by my organization.
3. You may use or create any data you like, but here are some resources that may be helpful to

you in locating a dataset. The dataset should be relevant to my organization (i.e., your case

study organization or vice-versa). Examples: (feel free to use any dataset of your choice)

https://www.census.gov/data.html

https://sqlbelle.com/2015/01/16/data-sets-for-bianalyticsvisualization-projects/

http://bi-notes.com/2011/09/sas-bi-sample-data-sources/

https://dreamtolearn.com/ryan/1001_datasets

4. You will also need to select a Big Data Analytics tool solution that your team proposes to
use to provide meaningful analysis of a large set of data. Many Big Data Analytics tools

are available in a trial version. Examples: (feel free to use any tool of your choice)

https://www.census.gov/data/data-tools.html

https://www.guru99.com/big-data-analytics-tools.html

https://www.softwaretestinghelp.com/big-data-tools/

5. Your paper/presentation should include the following components:

• A general explanation of what data science and big data analytics is

• The type(s) of data in your data set

• How the data is housed and any proposals for potentially consolidating it

• How the data was or will need to be prepared

• The big data analytics software solution your team is proposing to use including
features it offers (time series, decomposition, “What if” analysis, interactive reports, etc.)

• How your chosen big data analytics software differs from its competitors and why you
chose it.

• A model used in your data analysis of the case study organization data

• You will need to back up your claims with the source material, at least half of which should

be scholarly peer-reviewed articles.

https://www.census.gov/data.html

https://sqlbelle.com/2015/01/16/data-sets-for-bianalyticsvisualization-projects/

http://bi-notes.com/2011/09/sas-bi-sample-data-sources/

http://bi-notes.com/2011/09/sas-bi-sample-data-sources/

https://dreamtolearn.com/ryan/1001_datasets

https://dreamtolearn.com/ryan/1001_datasets

https://www.census.gov/data/data-tools.html

https://www.guru99.com/big-data-analytics-tools.html

https://www.softwaretestinghelp.com/big-data-tools/

ITS836 Residency Research Project & Presentation

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Deliverables:

Your group should prepare two deliverables:

(a) Microsoft Word for the paper submission about 25-30 pages (double spacing)
(b) PowerPoint for the presentation about 15-20 pages

Formatting and Mechanics:

Your paper should be formatted using APA guidelines and should contain the following sections:

• Title Page

• Table of Contents (Use the auto-generation features in Microsoft Word for the TOC)

• Abstract

• Introduction

• Problem Statement

• Literature Review

• Methodology

– Research Methods

– Research Question

• Data Analytics
– Types of data in the data set
– Preparing and Consolidating Data
– Data Analysis Model
– Time Series and Decomposition

• Findings
– Big Data Analytics software solution
– Compare and Contrast of other Big Data Analytics software

– Research Question Findings

– Discussion

• Limitations and Future Research

• Conclusion

• References

Submission:

Only one person (a group leader) in your group may submit the paper and presentation on behalf

of the group. The paper and the presentation should be submitted separately in their respective

areas in iLearn. You will have the option to submit your paper and your presentation to iLearn

twice.

The first time you submit, you will receive a SafeAssign score in the form of a percentage of the

likelihood that your submission was plagiarized. If the SafeAssign score is under 20%, then I

assume there is no plagiarism. If it is above 20%, then there may be some issues of plagiarism that

will need to be addressed to prevent your group from receiving a failing grade for the course. If

you do receive a SafeAssign score that is higher than 20%, please work on the paper to paraphrase

and reduce it. The second submission of the paper and presentation is what will be graded.

You may submit your paper as soon as you like, but we recommend that you submit it by 10 PM

on Saturday. This will enable you to work on any revisions you need to make as soon as t h e

presentations are over on Sunday. All submissions are due at 1:30 PM on Sunday.

ITS836 Residency Research Project & Presentation

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Part 2 – PowerPoint Presentation:

Upon developing your Company research paper, prepare a PowerPoint for a presentation that

your team will present to the company CIO/President to advise on how to overcome the

identified Big Data Analytics problem and recommendations on the essential software and tools

for competitiveness in a global marketplace.

Your PowerPoint presentation file can be organized any way you like; however, you are still

required to use APA guidelines, including in-text citations and references page.

• The length of the presentation should be between 15-20 slides.

• Maximum Number of Attempts allowed for submission is two

• Save the group file with group name before submission: Example:
Team1_ITS836_WK11_GP_PPT_date

Grading Criteria: will represents 60% of the course grade:

(a) Research Paper possible grade of 300 points:
– Meets Standard Criteria ((Introduction, Relevant Research, Methodology, Data Analysis,
Findings, Conclusion)

– APA Guidelines and Format
– Completeness/Content
– Explanation of Data Science & Big Data Analytics Issues
– Literature Review
– Type(s) of data in your data set
– Preparing and Consolidating Data
– Big Data Analytics software solution
– Compare and Contrast with other Big Data Analytics software
– Data Analysis Model Used
– Grammar and Document Organization

(b) PowerPoint Presentation possible grade of 150 points:
– Completeness of the Topic (Big Data Analytics Issues, Problem Identification, Big Data
Analytics Software Solution, Justification, Recommendation, Conclusion)

– Literature Review and Comparison of Big Data Analytics Tools
– Presentation Delivery

(c) Peer Evaluation Form grade of 10 points

Residency Grading Summary:

The residency assessments and projects attract a total of 60% of the course grade in iLearn.

– Group Research Project (paper) = 300 points
– Research Project Individual Presentation = 150 points
– 1st Assessment due Friday = 50 points
– 2nd Assessment due Saturday = 34 points
– 3rd Assessment due Sunday = 50 points
– Team Evaluation Form = 10 points

– Attendance Quiz (Day1-3) = 6 points

Total Residency Assessments and Projects = 600 points