Project:

Advanced Big Data Computing and Programming 
(BAN 5600 – I)
Instructor: Hamidreza Ahady Dolatsara (Hamid)

The final project should address an analytic problem or be driven by your literature review. It must be developed in PySpark or SparkR environments and the results should be achieved through one of them. The project is to be done individually. The below items are to be added to the workflow of the project:

1. A programming over GitHub.
2. The project should be performed on two different platforms (AWS, DataBricks, Google Cloud, local installation, etc.)

You need to provide  your  justification  for  the  project  topic,  the  research  questions,  methods, reproducible  results, and the methods  you  choose. The last week is for the project presentation. All the students should make  a  (YouTube)  video  for  their  presentation. 

There are three deliverables for the final project as follows:

• Project Proposal (10 points), Due date: 03/10/2023, submission through Moodle
  • Problem statement (including but not limited to) motivation, introducing the data and
    the topic, and the project scope.
  • Data source, and description of the data set (including the data dictionary)
• Project Introduction (10 points), Due date: 03/10/2023, submission through Moodle
  • Literature review (including citation), identifying the gap in the literature
  • Research questions, and the significance of the study
  • Descriptive statistics, and visualizations
• Final products (80 points), Due date: 04/10/2023, submission through Moodle
  • Presentation (YouTube)
  • Final Report as below:
    • It should include the previous deliverables and these: methods, analyzes,
      conclusions, business suggestions, codes, and software outputs.
    • There is no specific instruction on how many lines or pages of write-ups should be delivered but  each  section  of  the  report  should  be  well-developed  and  explained clearly.
    • In this report, students must submit a complete project as described above.
    • This report should be comprehensive and reproducible. It means TA or instructor  should use the codes and data and reproduce the same outputs.
• Important Points:
  • The project is not just an implementation of a python project in the Spark environment.
    The expectation is much more. It should be a professional report.
  • You can use your knowledge in other programming languages such as R, SQL, etc.
  • According to CRISP-DM, your  project  is  a  cyclical  one.  It means you  should  try  to improve the performance of your project and try at least 3 different approaches. Here is a link to know more about this standard
  • You should provide clear and well-developed comments, so everyone who reads your
    codes can understand the workflow.
  • You may submit  a  video though zoom.
  • A good “Literature Review” means reading plenty of scientific papers and citing them
    professionally.

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