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Big Data Analytics代写 大数据分析作业代写

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Big Data Analytics代写

Big Data Analytics

Coursework and marking schema

Big Data Analytics代写 1.General Information  A. This coursework is the replacement of the closed/open bookfinal examination due to covit19.

1.General Information  

A. This coursework is the replacement of the closed/open bookfinal examination due to covit19.

B. individual contribution around 150 -170 hours (three to four full weeks).

C. You will be penalized for late or non-submission according toXi’an Jiaotong- Liverpool University regulations.

D. Reports should be written in Word or PDF.

 

2.Learning Outcomes Addressed  Big Data Analytics代写

A. Demonstrate a solid understanding of processes and issues related toBig Data Analytics;

B. Identify applications of BDA that can help improve business operations;

C. Determine the appropriate use of technologies, tools, andsoftware packages to support data analysis involving practical scenarios;

D. Be proficient with at least one data analytics software package.

 

3.Feedback

The formal feedback for this assignment will be available after the exam board at the end of the semester. However, informal feedback can be provided during the lab sessions or tutorial time if you are asking.

 

 

4.1 Report No. 1 — Project Proposal (20% of 100 marks)  Big Data Analytics代写

Prepare a three-page document detailing your plan. This does not need to be too detailed, but needs to at least contain:

1.Individuals in the group.

2.Details about the problem:

A. What the problem is.

B. Why the problem is interesting – refer to the literature.

C. Relevant work – refer to the literature.

3.Information about the data source:

A. What data you plan to use.

B. Where you plan to get it from.

4.Proposed methodology (including subtasks, methods used in the analysis, tools, processes etc.).

5.Final evaluation methods and criteria.

6.Potential limitations and challenges.

Please note that it is quite likely that the instructor will provide feedback and alter or modify your proposed plans. This can either happen during the lab sessions or will come in feedback on the specific proposal.

See below for a list of 50 useful data sources: https://leaRN.G2.Com/open-data-sources

 

4.2   Report No 2 — Final Report (60% of 100 marks)  Big Data Analytics代写

Your final report should be seven pages long. However, you will be allowed an unlimited number of additional pages for references and appendices. This needs to contain at least the following:

1.Explain the problem and motivation. You can borrow some material from your proposal if you have not changed your plan.

2.Explain what data you explored, where it came from, and how you understand it.

3.Explain what you did for preprocess with the data. You should present the ideas in words instead of cut- paste your codes.

4.Explain what method you used to analysis the data.

5.How do you interpret you result.

6.Discuss limitations of your approach.

7.Discuss what you would do differently in the future.

A separate section in your final report addresses your personal contribution and learning. The section must not be longer than 500 words and must be attached to the Final Report. It must contain a discussion of the following issues from your individual perspective.

a.

A personal perspective of the problem addressed by the project. This may include discussing the aims of the project, the benefits the project might offer and to whom if it were successfully carried out, and the main benefits that pursuing the project would offer the teammembers.

 

Big Data Analytics代写
Big Data Analytics代写

 

b.

A critical appraisal of the methods applied to address the problem and manage the project. This may include an evaluation of the methods used from your perspective, a justification of why particular approaches have been taken and why alternatives have not been used, a discussion of how effective the selected approaches were and if, in hindsight, alternatives might have been better, a discussion of how changes in the project plan and execution have been handled and if the project execution progressed as initially expected, an evaluation of how successful the project was and whether the results could be used to continue the work, and suggestions for improving the approach to solving the problem and the project management. Write this from your personal perspective but relate this to the overall project.

c.

Reflections on your contributions to the project. Discuss which parts of the project you carried out/contributed to, how you approached these tasks and how you interacted with other members, both in sharing your results and in organizing the team’s activities. Also consider how your personal experience of the project compared to your expectations and experience before you started the project, how well your existing skills were utilized and what new skills you have learnt. Justify why you should get the full percentage of the project mark.

d. 

Lessons learnt and advice for the future. Discuss what lessons you learnt from executing the project about your discipline, project management and teamwork. Consider how and where you might apply this in the future. The content of your report must reflect the main items above. It is up to you how to structure the report. You must write a reflective report about your group project from your individual perspective. Whilst the above details are intendedto help you with deciding what to put in the report, they are not necessarily complete nor should be used as section headings.

e.

Peer review. Briefly discuss the contributions of each member and give a grade for each of your team members (100 marks maximum).

 

A.Report No 2 – Final report:

1.How well you can demonstrate you understand the data process procedure?

2.How well you can assess data quality and quantity?

3.How well you can manage data preparation methods?

4.How well you can chose from many data analysis methods and use one you choose well?

5.How well you can make data analyzing report?

6.How well you can interpret your results?

7.Did you consider legal, social, ethical and professional issues tojustify your choices and evaluate their results?

8.How well justified conclusions and concise discussion of futurework?

 

Big Data Analytics代写
Big Data Analytics代写

 

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