DAT7302 Big Data Analytics Assessment 1 Brief | UoB

DAT7302 Learning Outcomes Assessed:

• LO1: Formulate appropriate queries to interrogate data based on a given brief. LO2: Devise an effective process to capture, organise and store data for analysis.
• LO3: Effectively utilise Cloud technologies for processing and analysing Big Data.

DAT7302 Assessment Task

Based on the given dataset/s, clearly define the business problem and identify specific business questions that can be addressed using data analysis. You are required to use appropriate data analysis methods and visualisation techniques to answer those questions. You are required to create a data pipeline to prepare data for analysis. Based on your analysis, conclude, provide actionable insights, and suitable recommendations to the business.

The broad set of sub-tasks that you are required to perform (not in specific order): 

• Define the business problem and develop at least eight business questions
• Use SQL to join/merge different datasets to create a single file/dataset
• Use AWS to create a data pipeline using AWS S3 and AWS Glue
• Use AWS Athena to query data
• Use IAM role/policies if required
• Use AWS Cloud9 and AWS CloudFormation if required
• Use appropriate data wrangling techniques for transformation
• Use Python and Spark to create a data pipeline for data analysis, perform exploratory data analysis, and data visualisation
• Use MongoDB to query the dataset (JSON format) for data analysis
• Review previous scholarly literature/articles on similar datasets or business problems. The intent should be to identify various business problems/questions that have been raised and addressed using the data analytical and visualisation techniques
• Reflect on how different data analysis and visualisation techniques have addressed the business questions
• Derive insights from the data analysis performed
• Provide recommendations to the business based on your data analysis and derived insights

Structure of the Report (for reference)

1. Title Page
2. Declaration
3. List of Figures
4. List of Tables
5. Table of Contents (with page numbers)
6. Introduction

• Business Problem
• Business Questions

7. Review of Literature
8. Methodology

• This section will explain the techniques that will be used to address the business problem and business questions.

9. Implementation
10. Results
11. Discussion

• Derived Insights
• Recommendations

12. Conclusions
13. Personal Reflection (maximum of 500 words)

• Explain what you learned while completing this assignment, the challenges you faced, and your future action plans

14. References
15. Appendices (if any)

Presentation:

All submitted work must be accompanied by a formal presentation, and attendance is obligatory. Students who do not participate in the presentation will receive a failing grade for the assignment. The evaluation panel will ask questions during the presentation to assess each student's understanding of the project and to verify the originality of their work. Successfully passing the presentation is a prerequisite for passing the Assessment.

Late Work:

Late work will be subject to the following penalties:

• Up to 7 calendar days late = 10 marks subtracted, but if the assignment would normally gain a pass mark, then the final mark is no lower than the pass mark for the assignment.
• More than 7 calendar days late = This will be counted as non-submission, and no marks will be recorded.
• Late submission of assessments on refers and those that are graded Pass/Fail only is not permitted unless an extension is approved. See below.

Extensions

• In the case of exceptional and unforeseen circumstances, an extension of up to 14 days after the assessment deadline may be requested using the standard University Extension Request Form. For approval, there would need to be an explanation and evidence of relevant circumstances. Longer extensions for individual projects and artefacts may be granted at the discretion of the Programme Leader.
• Requests for extensions that take a submission date past the end of the module (normally week 15) must be made using the Mitigating Circumstances procedure.
• Some students with registered disabilities will be eligible for revised submission deadlines. Revised submission deadlines do not require the completion of extension request paperwork.
• Please note that the failure of data storage systems is not considered to be a valid reason for an extension. It is, therefore, important that you keep multiple copies of your work on different storage devices before submitting it.

Academic misconduct:

Academic misconduct may be defined as any attempt by a student to gain an unfair advantage in any assessment. This includes plagiarism, collusion, commissioning (contract cheating), among other offences. To avoid these types of academic misconduct, you should ensure that all your work is your own and that sources are attributed using the correct referencing techniques. You can also check originality through Turnitin. P

Minimum Secondary Research Source Requirements:

Level HE7 - It is expected that the Reference List will contain between fifteen to twenty sources. As a MINIMUM, the Reference List should include four refereed academic journals and five academic books.

Specific Assessment Criteria/Marking Scheme:

Distinction (70% and above)

An excellent data analysis and visualisations would be presented that are appropriate to the business problem and business questions. The business problem and questions are clearly defined and relevant. The insights drawn from the analysis are relevant and impactful. The data pipeline is functional, efficiently and accurately implemented. Queries are accurate, efficient, and optimised for performance. There is a use of some advanced queries. The visualisations are clear and appropriate to support the analysis and address business questions and problems. The visualisations are well-designed, have clear labels, and use colours to enhance the understanding and readability. The code is clean, readable, and follows best practices. The documentation is supported by appropriate comments. The results are supported by appropriate and adequate justifications.

Personal Reflections will be succinct, insightful and original. Extensive research demonstrating the use of a wide range of contemporary and seminal sources will be evident. Academic writing style, English and referencing will be excellent.

Merit (60%-69%)

Good data analysis and visualisations would be presented that are appropriate to the business problem and business questions. The business problem and questions are mostly clearly defined and relevant. The insights drawn from the analysis are mostly relevant and impactful. The data pipeline is functional and accurate, and mostly efficiently implemented. Queries are mostly accurate, efficient, and optimised for performance. There is a use of some advanced queries. The visualisations are clear and appropriate to support the analysis and address business questions and problems. The visualisations are designed with some design issues. The code is mostly clean, readable, with minor style issues. The documentation is supported by comments. The results are mostly supported by adequate justifications.

Personal Reflections will be succinct and original. Research demonstrating the use of a wide range of relevant research sources will be evident. Academic writing style, English and referencing will be good.

Pass (50%-59%)

Data analysis and visualisations would be presented with an attempt to support the business problem and business questions. The business problem and questions are defined. The insights drawn from the analysis. The data pipeline is functional. Queries are accurate but not optimised for performance. An attempt has been made to use some advanced queries. The visualisations are not understandable. The code is readable but lacks structure. The documentation is mostly supported by comments. The results are not supported by adequate justifications in some places.

Some original reflections will be presented. Research demonstrating the use of a range of relevant research sources will be evident. Academic writing style, English and referencing will be satisfactory.

Fail (Below 50% )

Students who do not meet the requirements of the Pass criteria will not complete the assessment activity.