代写BST811 Business Data Analytics Academic Year 2024-2025代做Python语言

BST811 Business Data Analytics

Academic Year 2024-2025

Coursework

The word count for this assignment is 3,000 words, excluding references, tables, figures, and the appendix. You are required to complete both tasks and should distribute the word count according to the percentage allocated to each task.

Task1  (70%)

Case Study: Evaluating Airline Customer Review Data

Background

AirCo, an airline company, engaged a consultancy firm, Heslington Consultancy (HesCo, a pseudonym), to conduct an in-depth evaluation of user-generated data from a customer review platform. AirCo will use this data to better understand the quality of service and characteristics of various competitors. Since AirCo was not registered on this platform, its own review data was not part of the dataset. However, the review data of other airlines was publicly available for web crawling, allowing them to obtain several years' worth of customer reviews.

AirCo had concerns that its marketing team might struggle to analyse the vast volume of review data, as they were still relying on manual annotation to assess the content of reviews. They realised that this method was insufficient for gaining a comprehensive understanding of customer perceptions and feedback. To address this, HesCo was tasked with analysing both the customer reviews of AirCo's competitors, aiming to uncover insights into customer sentiments, and with identifying areas for potential improvement based on competitor performance.

HesCo assigned a recently graduated data analyst with a background in computer science to carry out the analysis. The analyst employed advanced data-mining techniques, including text mining and sentiment analysis, to extract insights from the large dataset and produced various visualisations, such as charts and graphs, to present the findings (see *remarks). Despite the technical accuracy and thoroughness of the analysis, HesCo’s manager expressed difficulty in interpreting the results and questioned whether the insights were actionable for strategic decision-making.

As a newly appointed management trainee, you have been tasked with reviewing the analysis and assessing its value. Your task is to assess the usefulness and effectiveness of the data analysis in providing a meaningful evaluation of customer reviews, and to determine whether the findings should be shared with AirCo’s senior management. You are required to submit a written report detailing your assessment. Below are the key points your line manager would like you to address:

*Remarks: Please refer to the data analysis result document – “Analysis for AirCo.html” for the data-mining results.

A) You need to explain why text mining analytics is a valid approach for exploring review data in this project. Additionally, you should provide an overview of the techniques the Data Analyst has employed (such as LDA, sentiment analysis), explaining the rationale behind them and how they can yield valuable insights. It is important to communicate the purpose of this project clearly to our client, AirCo. You should include relevant literature to support your arguments

B) Your line manager expects the following content to be found in the data-mining results. You need to determine whether these questions have been answered. If they have, discuss the findings; if not, recommend how to revise the analysis. Your suggestions will serve as action points for the Data Analyst to follow up on:

· What are the main topics discussed in the review data?

· What are the strengths of AirCo's competitors, and do these strengths lead to higher customer satisfaction? (hints: What are the topics that provide positive feedback?)

· Which airline has the best positive feedback from customers, Discuss this in terms of ratings (structure data) and feedback (unstructured data)

· How have airlines' performance varied across the years? How did different airlines perform?

· The analyst has generated various visualizations, including word clouds, frequency distributions of review topics, sentiment analysis over time, and comparative analyses between airlines. Do these visualisations provide meaningful insights for AirCo? Why?

C) Your manager has asked you to identify and evaluate the top 3 airlines for family customers. Using the techniques learned in class, identify these airlines and discuss the characteristics of their services that make them family-friendly. Be sure to include relevant figures and diagrams to support your analysis.

Task 2 (30%)

Throughout the course, you took part in several sessions of the Simulation Game. You should include a screenshot from the simulation to highlight your best result. In addition, explain how you achieved this success by focusing on key parameters and strategies. You can also utilise tools (e.g., various diagrams introduced in this module) to analyse your decision-making process in selecting the optimal production line settings and other parameters to improve outcomes. Reflecting on the lessons learned from the simulation is crucial, as it will demonstrate how well you managed the simulation and your understanding of key principles in business analytics and their application within a supply chain context.

Note: The simulation score does not affect the assessment. The focus is on demonstrating the reasoning behind your best production line setup and other related decisions. (Simulation URL: https://www.leangame.management)

Submission Requirements

The submission deadline is 7/1/2025. Please submit your assignment through Learning Central. Files should be submitted in pdf format, as this should ensure that both the text and diagrams are not distorted when uploaded. Please check that the document has saved correctly before uploading. Marking is done anonymously, and so please only include your student number in the document. The file name should include both the module code and student number.

Marking Criteria

A marking grid for the coursework can be found at the end of this document.

Any Questions?

If you have any questions, then please contact Professor Mike Tse at [email protected]. Please note that emails sent outside of office hours will not be read until the next working day at the earliest.

Mark

Assessment Descriptor

80+

An outstanding piece of work, showing total mastery of the subject matter, with a highly developed and mature ability to analyse, synthesise and apply knowledge and concepts.  All objectives of the set work are covered and the work is free of error with very high level of technical competence.  There is evidence of critical reflection; and the work demonstrates originality of thought, and the ability to tackle questions and issues not previously encountered.  Ideas are expressed with fluency.  All intended learning outcomes are exceeded.

70-79

An excellent piece of work, showing a high degree of mastery of the subject matter, with a well-developed ability to analyse, synthesise and apply knowledge and concepts.  All major objectives of the set work are covered, and work is free of all but very minor errors, with a high level of technical competence.  There is evidence of critical reflection, and of ability to tackle questions and issues not previously encountered.  Ideas are expressed clearly. However the originality required for a 80+ mark is absent.  All intended learning outcomes are achieved and some are exceeded.

60-69

A good piece of work, showing a sound and thorough grasp of the subject-matter, though lacking the breadth and depth required for a distinction mark.  A good attempt at analysis, synthesis and application of knowledge and concepts, but more limited in scope than that required for a mark of 70+.  Most objectives of the work set are covered.  Work is generally technically competent, but there may be a few gaps leading to some errors.  Some evidence of critical reflection, and the ability to make a reasonable attempt at tackling questions and issues not previously encountered.  Ideas are generally expressed with clarity, with some minor exceptions.  All intended learning outcomes are achieved.

50-59

A fair piece of work, showing grasp of major elements of the subject-matter but possibly with some gaps or areas of confusion.  Only the basic requirements of the work are covered.  The attempt at analysis, synthesis and application of knowledge and concepts is superficial, with a heavy reliance on course materials.  Work may contain some errors, and technical competence is at a routine level only. Ability to tackle questions and issues not previously encountered is limited.  Little critical reflection.  Some confusion and immaturity in expression of ideas.  Most intended learning outcomes are achieved.

40-49

Not of a passable level for a postgraduate programme.  A poor piece of work, showing some familiarity with the subject matter, but with major gaps and serious misconceptions.  Only some of the basic requirements of the work set are achieved.  Little or no attempt at analysis, synthesis or application of knowledge, and a low level of technical competence, with many errors.  Difficulty in beginning to address questions and issues not previously encountered.

Below 40

Work not of passable standard, with serious gaps in knowledge of the subject matter, and many areas of confusion.  Few or none of the basic requirements of the work set are achieved, and there is an inability to apply knowledge. Technical competence is poor, with many serious errors.  The level of expression and structure is very inadequate.  Few intended learning outcomes are achieved.



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