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商业分析作业写 Predictive Analytics代写

2021-11-16 14:21 星期二 所属: R语言代写 浏览:50

商业分析作业写

School of Continuing and Lifelong Education (SCALE)

 TBA2104 Predictive Analytics Final Assessment

 

商业分析作业写 Your first task at Shopee is to  propose  2  initiatives that utilize data and machine learning to enhance Shopee business  or  its  operations.

 

A. Learning Objectives

This final assessment is meant to be an open-ended individual take-home assessment. It aims to assess your ability to think critically and design solutions to tackle real-world problems. As the time  given for  this assessment is very short compared to the amount of time a data analyst/scientist will spend on similar projects, you will only be focusing on a few deliverables.

B.Opening Narrative  商业分析作业写

Shopee Pte Ltd is a multinational technology company that focuses mainly on e-commerce. To address    the different markets, the company has multiple websites such as shopee.sg, shopee.com.my, shopee.tw, shopee.com.mx, etc.

You have just graduated from the SCALE BTech (Business Analytics) degree program and were hired  as  a data analyst at Shopee Singapore (https://shopee.sg/). Your first task at Shopee is to  propose  2  initiatives that utilize data and machine learning to enhance Shopee business  or  its  operations.  You should research on Shopee Singapore’s business and/or by looking at shopee.sg to formulate  ideas  of  areas where machine learning could be used by shopee.sg to either (non-exhaustive):

  • Enhance the shopping experience of itscustomers
  • Empower the sellers with various useful sitefeatures
  • Improve its logisticoperations
  • Improve sales andrevenue
  • Etc

When proposing the 2 initiatives, you should adopt the Cross Industry Standard Process for Data Mining (CRISP-DM) methodology and describe the relevant details for each of the 6 phases (Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, Deployment) in CRISP-  DM. The following sections will provide some ideas of what you need to discuss in each of these  6  phases.

商业分析作业写
商业分析作业写

C.Discussion  商业分析作业写

There should be two separate sets of discussions – one set for each of the 2 initiatives. You  should  produce a single document (PDF) with two sections – one section for each initiative. For each of the sections, you should further divide into subsections one for each phase of CRISP-DM. For example, the report could be broken into the following structure:

  1. Initiative 1 :[PROVIDE_A_TITLE]

a.BusinessUnderstanding

b.DataPreparation

c.Modeling

d.Evaluation   商业分析作业写

e.Deployment

2.Initiative 2 :[PROVIDE_A_TITLE]

a.BusinessUnderstanding

b.DataPreparation

c.Modeling

d.Evaluation

e.Deployment

  C.1. Business Understanding 商业分析作业写

You should provide the context of the initiatives such as the potential inefficiencies  that  Shopee  Singapore is facing1 or the pain points that its customers are facing, etc. After you have discussed the context, you should provide the problem statement or provide the purpose of the initiative.  In addition,  you should include (but not limited to) the following information (where applicable):

  • Projectobjectives
  • Rough idea of potential types of data which will be useful for theanalysis
  • Preliminary plan (timeline, what sort of analysis to perform,etc)

  C.2. Data Understanding

You should imagine that you have access to Shopee Singapore’s proprietary data (e.g. data  from shopee.sg) such as item listing details, sales data, etc. In this subsection, you should  describe  the  details of the data. Pay careful attention to be as detailed as possible during the discussion rather than keeping it brief. For example, rather than saying that you will be using sales data for the study,  provide a  table  of  the column names, descriptions of each attribute, example of some of the values of each column, etc. 商业分析作业写

Apart from describing the data, you should also discuss what kind of analysis/techniques could be used to further make sense of the data (before the actual modeling).

  C.3. Data Preparation

In this subsection, you should illustrate the process of performing data preparation. As the  data  preparation process is very dependent on the problem, availability of data in the database, and the form     by which it is finally exported out, you can make certain reasonable assumptions. You should however, anticipate potential challenges that one would encounter and provides some possible resolutions to these challenges.

Try to keep this section relevant to the problem/data that you will be working with rather than being generic. For example, instead of just saying you will perform data cleaning, identify some potential non- deal situations where the data might have issues and how one can go about  address those  issues when  each of these non-ideal situations arises. You should also provide the rationale and explanation  why  certain data preparation technique is being adopted.

You should show how the data should look like after the data preparation process. I.e. what the columns are, what each column represents, and provide a snapshot of the data that will be used for modeling. For  the snapshot of the data, you do not need to mine the data manually on your own.

  C.4. Model Building 商业分析代写

In this subsection, you should discuss the modeling building process. You should include (but not limited to) the following for the discussion:

  • Modelingtechnique(s)
  • Consideration of why this modeling technique(s) is/areused
  • Explanation of the technique(s) (if it is/they are not discussed inclass)
  • Approach of generating themodel(s)
  • etc

1 This could be something that you observe or based on your own speculations.

  C.5. Evaluation

In this subsection, you should discuss the evaluation process. You should include (but not limited to) the following for the discussion:

  • Steps to perform theevaluation
  • The evaluationcriteria
  • Expectedresults
  • Potential steps taken if the results are notideal
  • Etc

  C.6. Deployment

Depending on the nature of the initiative, you should discuss the next step after the model(s)  has/have  been generated and evaluated. You might want to tie in this discussion with the problem statement and further illustrate how the success of this initiative will bring value for Shopee.   商业分析作业写

D.Evaluation Criteria

This final assessment is worth 30% of the course grade. Each initiative discussion is worth  15%.  You  will be evaluated on:

  • Feasibility of the initiative (does it provide value for thecompany?)
  • Approach (whether it issound?)
  • Analysis (did you think critically about theproblem?)
  • Writing of the document (overall organization of thereport)

E.Submission  商业分析作业写

For this final assessment, you need to provide a single PDF document with the above discussions. Embed any supporting images, charts, figures, in the PDF document itself

Deadline: 2 May 2020 (Sun) 11:59pm

Folder: Deliverables Submission > Final Assessment

The folder will close at 11:59 pm. If you are unable to complete your solutions before the deadline, you should submit what you have as we will not accept any more submissions after the deadline.  商业分析作业写

The University takes a serious view of plagiarism or any other form of academic dishonesty. This includes seeking assistance from third parties outside this module (e.g., classmates, friends, or industry practitioners). Students who are caught cheating, copying work done by someone else, or engaging third parties to participate in any aspects of the assessment will be severely dealt  with.  You can be certain that you will be given a FAIL grade for this module. Please take this warning seriously.

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