SEN 4210 Business Intelligence and Big Data
Order ID 53563633773 Type Essay Writer Level Masters Style APA Sources/References 4 Perfect Number of Pages to Order 5-10 Pages Description/Paper Instructions
SEN 4210 Business Intelligence and Big Data
Stage
Unit Code SEN 4210 Unit Title Semester
Business Intelligence and Big Data Spring 2020
Assessment Details and Submission Guidelines Assessment Type Individual assignment Assessment Title Business Intelligence, data mining and Big Data Purpose of the assessment (with CLO Mapping) This assignment is designed to assess students’ knowledge and skills related to the following learning outcomes:
LO-1: Describe the business intelligence (BI) methodology and concepts.
LO-2: Understand the objectives and benefits of business analytics and data mining.
LO-3: Understand the motivation for and business drivers of Big Data analytics
Weight 15% of the total assessments Total Marks 100 Word limit NA Submission Guidelines All work must be submitted on Moodle by the due date along with a cover page. The assignment must be in MS Word format, 1.5 spacing, 11-pt Calibri (Body) font and 2.54 cm margins on all four sides of your page with appropriate section headings.
Reference sources must be cited in the text of the report and listed appropriately at the end in a reference list using IEEE referencing style.
Due Date Week 14, 22th May 2020 – submit your report on Moodle Late submission late project submissions will result in a penalty. A one-week late submission results in a 10% deduction on the project marking; while a project submitted between 1 and 2 weeks late will be subject to a 20% deduction on the project marking. Submissions after two weeks will be considered a fail on the project.
Academic Misconduct and Plagiarism Plagiarism is defined as the presentation of another person’s work as your own. This includes copying from books without referencing the material or copying from another student’s work. Instructor Name Dr Mostafa Kamil Moderator Name Dr Don
Spring 2020
Assignment Description
Problem-1: LO-2
Discuss the main data mining techniques. What are the fundamental differences among them?
Problem-2: LO-2 and LO-3
Examine how new data capture devices such as RFID tags help organizations accurately identify and segment their customers for activities such as targeted marketing and prediction. Many of these applications involve data mining techniques.
Scan the literature and the Web and then propose five potential new data mining applications that can use the data created with RFID technology.
What issues could arise if a country’s laws required such devices to be embedded in everyone’s body for a national identification system?
Problem-3: LO-1 and LO-3
Go to https://www.cloudera.com/. Find at least two customer case studies on Hadoop implementation, and write a report in which you discuss the commonalities and differences of these case studies.
Note: attached the original case studies to your answer sheet.
Problem-4: LO-1 and LO-3
Go to google.com/scholar, and search for articles on stream analytics. Find at least three related articles. Read and summarize your findings.
Note: attached the original articles to your answer sheet.
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Marking criteria:
Marking criteria is shown in following table. Marks are allocated as follows:
Sections to be included in the report Description of the section Marks Problem-1 Discuss the main data mining methods. 15 Problem-2 Discuss data mining application using RFID data 25 Problem-3 Critically analyze the content of the chosen case studies 25 Problem-4 Critically analyze the content of the chosen articles. 30 Reference style Follow IEEE reference style 5 Total 100
Marking Rubric for Assignment-1: Total Marks 100
Note: The marking rubrics varies for each assignment
Mark 80-100% 70-88% 60-68% 50-58% <50% Excellent Very Good Good Satisfactory Unsatisfactory Problem-1 /15
All topics are pertinent and covered in depth. Ability to think critically and source material is demonstrated
Topics are relevant and soundly analysed. Generally relevant and analysed. Some relevance and briefly presented. This is not relevant to the assignment topic. Problem-2: /25
Logic is clear and easy to follow with strong arguments Consistency logical and convincing Mostly consistent logical and convincing
Adequate cohesion and conviction The argument is confused and disjointed Problem-3: /25
Demonstrated excellent understanding of the two case studies. Demonstrated very good understanding of defining the two case studies.
Demonstrate d good understanding of defining the two case studies.
Demonstrate d satisfactory understandin g of the two case studies.
Demonstrated unsatisfactory understanding of the two case studies. Problem-4: /30
Demonstrated excellent understanding of the three articles. Demonstrated very good understanding of defining the three articles. Demonstrate d good understanding of defining the three articles
Demonstrate d satisfactory understandin g of the three articles.
Demonstrated unsatisfactory understanding of the three articles. Reference style
/5
Clear styles with excellent source of references. Clear referencing style Generally good referencing style
Sometimes clear referencing style
Lacks consistency with many errors