Assignment Remit
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Programme Title |
MSc Accounting |
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Module Title |
Business Analytics |
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Assignment Title |
Individual analytics portfolio |
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Level |
M |
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Weighting |
20% |
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Assignment Length |
6 analytics tasks with commentary |
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Submission Format |
Online |
Individual |
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Assignment:
This assignment is based on the analytics tasks in Tableau completed in seminars during the module as well as the requirement for you to complete the Python module from datacamp below.
https://app.datacamp.com/learn/courses/intro-to-python-for-data-science
The aim is for you to build up a personal portfolio of completed tasks that show you developing skills. We want you to build the confidence to develop your own solutions to data manipulation and communication tasks as well as your technical skills in Excel, Python and Tableau. Developing these skills will allow you to contribute to the group assessment task in full.
The five Tableau seminars will start with basic Tableau analytics tasks and will build up to complex dashboards and data stories. This will be a learning journey for you and this assignment will help you record and reflect on your progress. Each task will be handed out before the seminar, and you will have a chance during the seminar and afterwards to develop and refine your own work. For each task we will be using the Tableau software that forms the core of the module’s technical content and you should provide a link to your work by uploading it to the tableau public gallery.
In your portfolio we will require you to provide a short reflection on what you learned undertaking the task, the strengths and weaknesses of your solution and how the skills developed may be used in other tasks. This will also include reflections on the programming language Python as well as work with Excel.
You will be required to reflect on your use of Tableau verbally in a seminar and this will form part of the assessment criteria.
Module Learning Outcomes:
In this assessment the following learning outcomes will be covered :
• Select, apply, and evaluate common analytics techniques and implement them using appropriate software tools.
• Develop solutions to analytics problems using Python.
Grading Criteria:
Please see marking rubric below
Feedback to Students:
Both Summative and Formative feedback is given to encourage students to reflect on their learning that feed forward into following assessment tasks. The preparation for all assessment tasks will be supported by formative feedback within the tutorials/seminars. Written feedback is provided as appropriate. Please be aware to use the browser and not the Canvas App as you may not be able to view all comments.
Plagiarism:
It is your responsibility to ensure that you understand correct referencing practices. You are expected to use appropriate references and keep carefully detailed notes of all your information sources, including any material downloaded from the Internet. It is your responsibility to ensure that you are not vulnerable to any alleged breaches of the essment regulations.
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Criteria |
Ratings |
Pts |
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Tableau and Excel Tasks completed? Has a full set of completed Tableau tasks been uploaded to the Tableau Gallery? Have Excel seminar questions been included in the portfolio. (50%) |
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50 pts |
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40 to >28 Pts Distinction Complete set of tasks uploaded with answers completed to a good standard. This will include evidence of Excel and Tableau and may include some Python coding. |
28 to >24 Pts Merit Complete set of answers uploaded from both Excel and Tableau. |
24 to >20 Pts Pass Tableau and Excel Answers have been uploaded but maximum of 1 are incomplete or missing. |
20 to >0 Pts Fail Answers not uploaded and/or are all incomplete |
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Criteria |
Ratings |
Pts |
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Python Certification from Datacamp Has the Introduction to python course on datacamp been completed with appropriate personal certification? (5%) |
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5 pts |
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comp(ficate)lishmen(include)t(d) with clear evidence of student’s award |
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Tableau Skills Has the student displayed skills in Tableau use other than replicating answers worked on in seminars? (25%) |
25 to >17.5 Pts Distinction Detailed commentary on each activity included alongside additional information. Work is innovative and competed to a very high standard |
17.5 to >15 Pts Merit All answers show original work beyond techniques used in class. |
15 to >12.5 Pts Pass Answers just about cover what was expected in classes. |
12.5 to >0 Pts Fail Answers do not cover work done in class. |
25 pts |
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Criteria |
Ratings |
Pts |
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Reflective Commentary Has a reflective commentary on each task been completed? (0%) |
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20 pts |
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20 to >14 Pts Distinction Detailed commentary on each answer uploaded to a high standard. |
14 to >10 Pts Merit Commentary on each answer uploaded that evidence some thoughtful reflection. |
10 to >8 Pts Pass Commentaries completed but not to a high standard. |
8 to >0 Pts Fail Answers not uploaded and/or are all incomplete |
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Total points: 100 |
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