BUSAN300-23B (HAM)

Management of Big Data

15 Points

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The University of Waikato
Academic Divisions
Division of Management
School of Accounting, Finance and Economics

Staff

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Convenor(s)

Narges Safari

Narges Safari
4477
MSB.2.30
See Moodle
narges.safari@waikato.ac.nz

Lecturer(s)

Administrator(s)

: tarryn.nel@waikato.ac.nz

Placement/WIL Coordinator(s)

Tutor(s)

Student Representative(s)

Lab Technician(s)

Librarian(s)

: em.pooley@waikato.ac.nz

You can contact staff by:

  • Calling +64 7 838 4466 select option 1, then enter the extension.
  • Extensions starting with 4, 5, 9 or 3 can also be direct dialled:
    • For extensions starting with 4: dial +64 7 838 extension.
    • For extensions starting with 5: dial +64 7 858 extension.
    • For extensions starting with 9: dial +64 7 837 extension.
    • For extensions starting with 3: dial +64 7 2620 + the last 3 digits of the extension e.g. 3123 = +64 7 262 0123.
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What this paper is about

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This paper addresses the key issues associated with the management of big data addressing the what, when, and how questions when faced with complex data sets unsuitable for traditional data processing applications.
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How this paper will be taught

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This paper will consist of a combination of theoretical concepts, cases, and hands-on workshops. Every week, online content will be uploaded to explain the current understanding of the technology, the basic aspects of the technology, and its various configurations. The two-hour face-to-face workshop will be used to demonstrate the hands-on application of the technology, simulations, and guest lecturers wherever applicable. Assignments for the paper will be based on the hands-on workshops.

A workshop on Monday from 11.00 AM to 1:00 PM every week will be held on campus in MSB.0.26. These sessions will build on that week's topic and will be a hands-on practice on how to implement the learnings from the week's topic. Before attending the workshop, students need to have completed their study of the specific topics provided online in Moodle. The content of the workshops is an important part of learning and assessment.

Students are strongly encouraged to attend sessions in person at the Hamilton campus. The teaching philosophy of this paper benefits most from in-person interaction with the lecturer and fellow students. Workshop attendance via Zoom is possible but not recommended as there will be some hands-on activities in these workshops. Only those students who have a legitimate reason for not attending in person should plan to attend it online. Further details on these options will be provided via Moodle.

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Required Readings

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All materials will be supplied via Moodle. These materials are essential for students to develop their knowledge of the concepts explored in the paper. It is, therefore, expected that students have read the relevant material prior to attending each session.
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Learning Outcomes

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Students who successfully complete the course should be able to:

  • Articulate to business clients the function and purpose of common big data tools and techniques
    Linked to the following assessments:
  • Carry out basic data modelling and design
    Linked to the following assessments:
  • Demonstrate basic knowledge of big data tools such as Google BigQuery, Python, SQL & NoSQL
    Linked to the following assessments:
  • Manage data across cloud platforms, either with or instead of on-premise storage
    Linked to the following assessments:
  • Translate business information needs to technical specialists
    Linked to the following assessments:
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Assessments

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How you will be assessed

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PLEASE NOTE: The University has zero tolerance for plagiarism and cheating.

"Homework Helper" sites: The use of online “homework helper” sites including, but not limited to, Chegg, NoteHall, Quizlet and Koofers is not permitted in this course. Using any such services, or having someone else complete your assignments (whether voluntarily or for a fee) is considered cheating and such cases will be referred directly to the Disciplinary Committee.

If you are unsure what constitutes plagiarism or cheating, please contact academic.integrity@waikato.ac.nz

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The internal assessment/exam ratio (as stated in the University Calendar) is 100:0. There is no final exam. The final exam makes up 0% of the overall mark.

The internal assessment/exam ratio (as stated in the University Calendar) is 100:0 or 0:0, whichever is more favourable for the student. The final exam makes up either 0% or 0% of the overall mark.

Component DescriptionDue Date TimePercentage of overall markSubmission MethodCompulsory
1. Assessment 1
4 Aug 2023
11:00 PM
20
  • Online: Submit through Moodle
2. Assessment 2
19 Sep 2023
11:00 PM
20
  • Online: Submit through Moodle
3. Group Project Presentation
9 Oct 2023
11:00 AM
30
  • In Class: In Lecture
4. Lab Activities
30
  • In Class: In Tutorial
Assessment Total:     100    
Failing to complete a compulsory assessment component of a paper will result in an IC grade
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