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CSMBD21 Big Data and Cloud Computing
创建日期：2024-08-13 16:08:23
标签： CSMBD21
Big Data and Cloud Computing

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  CSMBD21

Big Data and Cloud Computing

Type of Assignment: Coursework

Individual/group Assignment: Individual

Total Weighting of the Assignment: 50% comprising of 25% for each of Big Data and Cloud Computing

Page limit/Word count for the technical report of the results:

Approximately 3000 words max, consisting of two sections of 3 (max) pages each, to report on the

implementation of two tasks (Task A and Task B); Section A to report on the Big Data Task (Task A) and Section

B to report on the Cloud Computing (Task B) – Maximum of 6 pages excluding appendices and should follow

the School Style Guide.

Expected hours spent for this assignment: 30 hrs.

Items to be submitted: Two PDFs to be submitted via BB, each of 3 pages max, one for Section A (Task A) and

one for Section B (Task B). The PDFs are to include, on the first page, a link to the code to be made accessible to

assessors [[email protected] (rk929650), [email protected] (sis04ab), [email protected]

(ei194011), [email protected] (in928478)] through GitLab or similar repository. For Section A, as the

solution is to be provided in your free Azure account, please provide a temporary username and password to

your azure account; for Section B the link can be a GitLab.

Work to be submitted on-line via Blackboard Learn by: 12:00 hrs, Wednesday 20th March 2024

Work will be marked and returned by: 15 working days after the date of submission.

NOTES

By submitting this work, you are certifying that it is all your own work and that use of material from othersources

has been properly and fully acknowledged in the text. You are also confirming that you have read and

understood the University’s Statement of Academic Misconduct, available on the University web-pages.

If your work is submitted after the deadline, 10% of the maximum possible mark will be deducted for each

working day (or part of) it is late. A mark of zero will be awarded if your work is submitted more than 5 working

days late. You are strongly recommended to hand in your work by the deadline as a late submission on one piece

of work can have impacts on other work.

If you believe that you have a valid reason for failing to meet a deadline then you should complete an

Extenuating Circumstances form and submit it to the Student Support Centre before the deadline, or as soon as

is practicable afterwards, explaining why.

2

Section A (The Big Data Task):

? Task A: Implement a solution to predicting flight delays based on historical

weather and airline data as provided in your free azure account and

explain the reason for your preferred Machine Learning (ML)model.

Section B (The Cloud Computing Task)

? Task B: Implement a MapReduce solution to determine the passenger(s)

having had the highest number of flights based on flights and

passenger data provided in the Assignment Folder of the Module on

Blackboard.

Assignment Tasks based on the explanatory notes in the Appendix to this document

If you face any difficulties, make clear, in your submission, how far you were able to proceed with the

implementation and explain the challenges you faced.

Marking Criteria for Task A:

? Total marks for this Task A will be normalised for 25% credit towards the overall coursework.

? The table below indicates the level of performance expected for each range of assessment:

Classification Range Typically, the work should meet these requirements

First Class (>= 70%) The assignment demonstrates:

? Excellent technical skills in implementing the system, possibly also suggesting

any other solution deemed viable; including reasons for the preferred solution.

? Professional technical writing skills and style.

Upper Second (60-69) The assignment demonstrates:

? Excellent technical skills in implementing the solution.

? Appropriate technical writing skills and clear presentation; including reasons for

the preferred solution.

Lower Second (50-59) The assignment demonstrates:

? Excellent technical skills in implementing the system.

? Moderate technical writing skills and clear presentation; including reasons for

the preferred solution.

Third (40-49) The assignment demonstrates:

? Satisfactory technical skills in implementing the system.

? Some technical writing ability and clear presentation; including some reasoning

for the preferred solution.

Fail (<40) The coursework fails to demonstrate technical skills to implement and technical

writing and clear presentation; inadequate or non-existent reasoning for the

preferred solution.

3

Marking Scheme and feedback template for Task A (Big Data Task)

? Total marks for this Task A will be normalised for 25% credit towards the overall coursework assessment

The key criteria for the assessment of the submitted coursework Contribution to Mark in %

Introduction

? Brief description of the background of the case study.

? Description of the tools and techniques deployed, including “Data

Factory”, “Data Bricks”, “Power BI” as used to analyse this solution

(explaining the solution architecture).

5

10

Solution Implementation

Implementation of Solution:

? Creating the Data Bricks cluster

? Load sample data

? Setup the Data Factory

? Data factory pipeline

? Operation of ML

? Summarizing data

? Visualisation of data


Evaluation:

Your personal reflections on:

? Stating reasons for your preferred solution 10

Presentation of the report:

? Structure and layout of the report

? Professional writing style

? Use of figures, tables, references, citations, and captions


Marking Criteria for Task B (Cloud Computing Task)

? Total marks for this Task A will be normalised for 25% credit towards the overall coursework.

? The table below indicates the level of performance expected for each range of assessment:

Classification Range Typically, the work should meet these requirements

First Class (>= 70%) The assignment demonstrates:

? Deep understanding of the MapReduce paradigm and excellent technical skills in

implementing the system to fulfil the objectives of the task.

? Highest quality technical reporting including solution evaluation, addressing all

aspects, completely and clearly.

Upper Second (60..69) The assignment demonstrates:

? Good understanding of the MapReduce paradigm and good implementation

consistent with the objectives of the task.

? Good quality technical reporting, inclusive, complete, and clear.

Lower Second (50..59) The assignment demonstrates:

? Sufficient understanding of the MapReduce Paradigm and satisfactory

implementation consistent with the objective of the task.

? Acceptable technical writing reporting tackling the key aspects.

Third (40..49) The assignment demonstrates:

? Basic understanding of MapReduce and basic level of implementation of the

task.

? Basic standard of technical reporting; with some notable shortcomings.

Fail (<40) The coursework fails to demonstrate sufficient understanding of the MapReduce

paradigm and fails to provide reporting even to a basic standard.

5

Marking Scheme and feedback template for Task B (Cloud Computing Task)

? Total marks for this Task B will be normalised for 25% credit towards the overall coursework assessment

MapReduce Concepts

Concept Example Max.

Map Phase Inputs and Outputs 5

Reduce Phase Inputs and Outputs 5

Segmentation of Roles Split of work 2

File Handling Use of Files and Buffers 3

Distributed parallelism Advantages, fault tolerance etc. 3

Explanation of additional process Combining/Shuffling/partitioning etc.

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