Dublin Business School Assessment Brief
Assessment Details
| Unit Title | Advanced Data and Network Mining |
| Unit Code | B9DA110 |
| Unit Leader | |
| Level: | 9 |
| Assessment Title | Big Data Mining Process and Application |
| Assessment Number | 1 |
| Assessment Type: | Individual |
| Assessment Weighting | 30% |
| Issue Date: | Week of 23 January 2023 |
| Hand in Date: | Sunday 11 June 2023 (23:55) |
| Mode of Submission: | On-line Moodle |
Assessment Task [100 Marks]
- Read the journal article available on Moodle “The CRISP-DM Model: The New Blueprint for Data Mining” Shearer 2000. Write a critique of this article as it applies to the mining of ‘Big Data’ in 2023. Your appraisal should include a review of two related journal articles (the original paper and two other published on or after 2018). Approximate length 1500 words. Cite all references using Harvard referencing (guidelines on Moodle). (50 Marks)
- Select a Big Data mining case study published either in a journal; conference paper or vendor report. Discuss the data mining techniques applied and tools used. Highlight the benefits to the business together with measurable implementation success criteria. Approximate length 1500 words. Cite all references using Harvard referencing (guidelines on Moodle). (50 Marks)
The grade assessment will be based on the DBS CA grading scheme which has been included at the end of this document.
Include a cover page and cite all references. Two files should be loaded to Moodle on or before Sunday 11 June 2023 (23:55).
- A SINGLE pdf file named CA01_Surname_First-Name_Student-ID including answers to parts a) and b).
- A zipped file including your reference documents.
DBS Grade Assessment Policy (B9DA110)
| Module Descriptor | Mark Band | Criteria | Determinator within grade band |
| A (Outstanding) | 80-100 | Displays a thorough and systematic knowledge of module content through choice of scenario, solution and handover process and documentation.Clear grasp of the issues involved, with evidence of innovative and original use of learning resources.Knowledge beyond module content.Clear evidence of independence of thought and originalityMethodological rigourHigh critical judgement and confident grasp of complex issues | Originality and depth of insight into critique and analysis. |
| A (Clear) | 70-79 | Methodological rigourOriginalityCritical judgementUse of additional learning resources | Methodological rigour, insight |
| B | 60-69 | Very good knowledge and understanding of the module content.Well-argued answerSome evidence of originality and critical judgementSound methodologyCritical judgement and some grasp of complex issues. | Extent of use of additional or non- core learning resources |
| C | 50-59 | Good knowledge and understanding of the module content.Reasonably well-argued answerLargely descriptive or narrative in focusMethodological application is not consistent or thorough | Understanding of the main issues, sound approach |
| D | 40-49 | Lacking methodological applicationAdequately arguedBasic understanding and knowledgeGaps or inaccuracies but not damaging | Knowledge of and application of data mining tools, techniques and methodology |
| E (Fail) | 0-39 | Weakness of approach |
General Requirements for Students:
PLEASE READ CAREFULLY
- It is your responsibility to ensure your file is uploaded correctly.
- Students are required to retain a copy of each assignment.
- When an assignment is submitted, it is the student’s responsibility to ensure that the file is in the correct format
and opens correctly.
- Students should refer to the assessment regulations in their Course Guide.
- DBS penalises students who engage in academic impropriety (i.e. plagiarism,
- Collusion and / or copying). Please refer to the referencing guidelines on Moodle for information on correct referencing.
- All relevant provisions of the Assessment Regulations must be complied with.
- Penalties for late submission of assignments are as follows:
- 25% penalty for assignments submitted within 5 working days of the deadline.
- No marks for assignments submitted more than 5 working days after the deadline.
- Extensions to assignment submission deadlines will be granted in exceptional circumstances only. The appropriate “Application for Extension” form must be used and supporting documentation (e.g. medical certificate) must be attached. Applications for extensions should be made directly to the Head of Year or Programme Leader in advance of the deadline date.
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