LO1: Critically evaluate the evolving use of data in solving business problems, presenting logical arguments based on evidence
2025-04-30 13:31:57
BPP Coursework Cover Sheet
Please use the table below as your cover sheet for the 1st page of the submission. The sheet should be before the cover/title page of your submission.
Programme
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Module name
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Data Driven Decisions for Business
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Student Reference Number (SRN)
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Report/Assignment Title
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Date of Submission
(Please attach the confirmation of any extension received)
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Declaration of Original Work:
§ I hereby declare that I have read and understood BPP’s regulations on plagiarism and that this is my original work, and that I have researched, undertaken, completed and submitted in accordance with the requirements of BPP School of Business.
- I declare that where I have used any AI tools, it was for the following reasons (highlight as appropriate):
- To review a draft
- To correct language errors
- Other (please describe)
I have copied & retained for BPP University’s reference, all AI prompts used in the creation of AI content and all AI-generated responses in support of my assignment and attached relevant evidence in the appendices.
I understand that I may be required to participate in a viva voce, where I will be questioned on any aspect of my assignment, including key concepts, theories, examples used, & any sources included.
The word count, excluding contents table, bibliography and appendices, is words.
Student Reference Number: Date:
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MSc Management
Data Driven Decisions for Business
Coursework Assessment Brief CW2
1.General Assessment Guidance
- Your summative assessment for this module is made up of this 2,500 submission which accounts for 100% of the marks
- Please note late submissions will not be marked.
- You are required to submit all elements of your assessment via Turnitin online access. Only submissions made via the specified mode will be accepted and hard copies or any other digital form of submissions (like via email or pen drive etc.) will not be accepted.
- For coursework, the submission word limit is 2,500 words. You must comply with the word count guidelines. You may submit LESS than 2,500 words but not more. Word Count guidelines can be found on your programme home page and the coursework submission page.
- Do not put your name or contact details anywhere on your submission. You should only put your student registration number (SRN) which will ensure your submission is recognised in the marking process.
- A total of 100 marks are available for this module assessment, and you are required to achieve minimum 50% to pass this module.
- You are required to use only Harvard Referencing System in your submission. Any content which is already published by other author(s) and is not referenced will be considered as a case of plagiarism.
You can find further information on Harvard Referencing in the online library on the Hub. You can use the following link to access this information: https://bpp.libguides.com/home/business
- BPP University has a strict policy regarding authenticity of assessments. In proven instances of plagiarism or collusion, severe punishment will be imposed on offenders. You are advised to read the rules and regulations regarding plagiarism and collusion in the GARs and UPPs which are available on the HUB in the Help and Support section under Documents and Forms.
- Use of AI in assessments is only allowed for the purposes of reviewing a draft, correcting language errors or if specified in the summative assessment brief. If you have used AI for any of these purposes, you should indicate this on the Assignment Cover sheet. For more information regarding acceptable and unacceptable use of AI, please enrol onto the Generative AI Foundations course on the HUB.
- You should include a completed copy of the Assignment Cover sheet. Any submission without this completed Assignment Cover sheet may be considered invalid and not marked.
1.Assessment Brief
2.1.Assessment learning outcomes
This assessment is designed to gauge your understanding, skills and application of common data analysis techniques used in business and other organisations today. As such you need to demonstrate your attainment in these areas according to the four Module Learning Outcomes (LOs):
- LO1: Critically evaluate the evolving use of data in solving business problems, presenting logical arguments based on evidence
- LO2: Explore how data analytics can be used within a business context
- LO3: Critically appraise the presentation of data within a business environment
- LO4: Critically evaluate different business analytical techniques as part of planning a data analytics initiative.
2.2.Scenario
You have recently been employed by BeeSafe Insurance as a data analyst.
BeeSafe Insurance is an international UK insurance company offering insurance products for businesses with over 30 subsidiaries in countries around the world. Its main services cover the areas of Motor, Home, Life, Health and Travel insurance.
BeeSafe Insurance has been providing exceptional business insurance services for over 80 years. Its commitment to people-centric insurance has allowed BeeSafe Insurance to give protection to business clients from the small, everyday business risk to the larger, unexpected compensations
claims. Its services protect organisations’ work, people, reputation, and ultimately, the future livelihood of the business. The company’s personalised approach to business insurance and the creative delivery of technology has helped fuel its continued growth.
As BeeSafe Insurance grows, it continues to increase its data analytic roles within the organisation to strengthen its strategic decision-making capabilities. The recruitment strategy is to employ young professionals with strategic and data analytics skills willing to provide BeeSafe Insurance’s top management with strong evidence-based foundation for their business decisions. They like recruits to have a broad management experience combined with a strong academic background. Your MSc degree at BPP University was a key element in their decision to recruit you.
As part of your first assignment at BeeSafe Insurance, you have joined the Underwriting department as data analyst. Other departments of the company bank include claims, finance and legal.
The underwriting department seeks to develop insurance products that can be sold to their customers at a premium. The department will craft its own collection of forms and endorsements to provide the marketing department with the ability to say “yes” to customers and potential customers. Whilst the underwriting and marketing departments want to sign up as many insureds as possible to collect premiums, the claims department manages claims when an insured seeks to
recover on its insurance assets. The marketing and underwriting departments are judged by their premium collections (the revenue of the company) and retention volume/ratios (i.e., the percentage of insureds who renew their policies with the company), Whilst the claims department is judged by how little it incurs resolving claims. These financial measures drive insurance company management and profits, as well as the bonuses paid to department management
Your manager requested you to complete a number of tasks to ensure that you have a grounded knowledge and understanding of data analytics and its application in decision-making. This is your opportunity to demonstrate your capability and give your employer the confidence to let you run your own project in the future.
The Underwriting team is analysing different growth options so they can provide a more balanced growth in the future, combining traditional face-to-face with online services. In particular, the Underwriting department has teamed up with the IT department to explore how AI based technologies can provide the basis for process automation, claims optimisation, and developing effective customer engagement strategies. However, it makes sense to define the growth strategy based on these technologies only if the current insurance business model does not provide the expansion and growth opportunities expected by the company’s top management. So, you have been given the responsibility to analyse BeeSafe Insurance current business performance.
Your job will be to analyse the performance of three of the best international subsidiaries of BeeSafe Insurance: Brazil, Australia and Norway. BeeSafe Insurance has experienced strong competition in these countries from multinationals insurance companies such as Aviva and AXA. So, the performance of these three subsidiaries is a good indication of the current global market performance of the company.
2.3.Research objectives and tasks
The Underwriting Director is interested in understanding the options available for an expansion strategy. For this purpose, he wants you to:
Perform an analysis of the revenue (written premiums) and retention volume (number of clients who renew their policies) of the three subsidiaries to identify the best country to start an expansion strategy.
As part of the analysis, the Marketing Manager wants to consider the re-development of company’s global brand strategy to better support the insurance service offering in each country. Her objective is to increase the number of customers covered by the company’s insurance products through a strong brand marketing plan. In order to do so, she wants to focus the promotion efforts only on the high-performance insurance products of the company, that is, those products with high
1 Leonard J., 2019. Inside an Insurance Company: How They Work and What Drives Them. Accessed De 2023. https://btlaw.com/insights/blogs/policyholder-protection/2019/inside-an-insurance- company#:~:text=Insurance%20companies%20are%20generally%20organized,referee%20between%20these%20competing%20interests
revenues and high retention volumes. The business insurance products BeeSafe Insurance offers in its three subsidiaries is made of the following insurance product categories
- Public liability insurance: it protects business if something happens at work that results in injury to a customer, a member of the public or damage to someone’s property.
- Employers` liability insurance: it protects business if employees get injured or become ill as a result of working for the business.
- Professional indemnity insurance: it protects if any recommendations or advice have caused a financial loss for a client and the company is found to be at fault.
- Contents & stock insurance: it covers the cost of replacing items that are important to the business such as goods or specific equipment used to run the operations.
- Cyber insurance: it protects from threats in the digital age, such as data breaches or malicious cyber hacks on work computer systems.
- Building insurance: it covers the costs of repairing the damage caused in an event such as flood or fire at the work premises.
In this respect, she wants you to:
Perform an analysis of the business insurance categories offered in the three subsidiaries to identify those categories with the best performance.
BeeSafe Insurance has used digital technologies in the last 20 years to increase speed, efficiency, and accuracy across every area of its business. Artificial Intelligence or AI is the latest technology the IT department wants to adopt to significantly accelerate its digitisation strategy. AI can assist the company in assessing risk, detecting fraud, and reducing human error in the application process, as well as enabling customer service using chatbots. However, there are also challenges and risks in adopting AI. It has been reported that financial institutions using AI have received numerous complaints from frustrated customers trying to receive timely, straightforward answers from their financial institutions.
The IT department has taken a careful approach to AI by implementing an AI chatbot in its Brazil subsidiary to test the technology. Other insurance companies have adopted AI enabled chatbots in India such as Zurich Insurance with its Zara chatbot. The test started in July 2023 and was available through its local website. Initially the system was used to answer customers’ enquiries about automated claims processing, lead generation and conversion with prospects, onboarding new clients and FAQs, collect feedback and customer support.
The IT Manager and the Underwriting Director are keen to understand if the implementation of AI chatbots could be applied to other subsidiaries across the company. So, he wants you to address the question:
Did the implementation in 2023 of the AI chatbot in Brazil have a positive impact on revenue (written premiums) of the subsidiary?
2 https://www.axa.co.uk/business-insurance/
3 https://www.directlineforbusiness.co.uk/
The responses to the issues detailed above should be included in a summary MS Word report that you save and submit.
2.4. Report Sections
Because this is your first project within BeeSafe Insurance, the management team has given you additional details regarding the structure and content that it is expected to see in your report. This is set out in Section 3 – Report Structure.
The set of data is available (see module dataset spreadsheet file). Since the data comes directly from the countries, quality issues are present which will require your attention!
You have four Sections to complete for your summative report
Section 1 (LO4): Introduction and project plan
Summarise what you are going to present in the report. Then justify your plan for delivering the research project to the management of BeeSafe Insurance, making sure you also clearly refer to a data analytics implementation framework as part of your plan. Finally, explain how data analytics can add value and help to drive business performance improvements to BeeSafe Insurance.
Section 2 (LO2):
a)Data quality issues and remedies
Proceed with preparing the dataset for the analysis. Discuss initially the general issues encountered in collecting, reviewing and cleansing data and then detail the specific data quality issues you found in the project dataset and how these issues will be addressed.
b)Data analysis and commentary
Using only tables, set out and explain the results of your numeric data analysis and supporting commentary. Start by including a summary of exploratory data analysis of the dataset. Then create tables where you can analyse the overall performance of BeeSafe Insurance as well as its performance by country and by business insurance category. To answer the Section, you should perform your analysis using at least 3 tables (see guidelines for further details).
Section 3 (LO3): Data charting and commentary
Use your data charting and interpretation skills to develop graphical presentations of the data together with bullet-points setting out the key findings and inferences from the analysis. Create charts where you can compare and analyse retention volume and revenue trends over time by country and by business insurance category, in particular where you can see evidence of any performance change due to the implementation of the AI chatbot in Brazil during 2023. To answes
the Section, you should perform your analysis using at least 3 charts (see guidelines for further details).
Section 4 (LO1): Conclusions and recommendations
Based on your analysis and findings in Sections 3 and 4 set-out your conclusions and recommendations to BeeSafe Insurance’s top management. As part of your conclusions, include answers to the three project objectives raised by the top management.
Report Structure and References
In addition, marks are awarded for the overall professionalism of your report and the adoption of academic standards.
2.5. Section guidelines
The following section provides guidelines on the steps needed to perform each one of the Sections of this assignment.
Section 1 (LO4)
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Critically evaluate different business analytical techniques as part of planning a data analytics initiative.
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Guidelines:
- State the purpose of the report and describe the report structure and contents
- Present your overall project plan for delivering the project
- Ensure that your project plan explicitly refers to a data analytics implementation framework and explain how the chosen framework is applied to the project and used to address the core project objectives assigned to you.
- To analyse the value of Data Analytics, suggest a list of Key Performance Indicators (KPIs) BeeSafe Insurance can use to measure its performance. Then explain how data analytics can help to improve the performance of the company by looking at how data analytics can improve these KPIs.
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Section 2 (LO2)
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Explore how data analytics can be used within a business context
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a) Data quality - Guidelines:
- List and explain generic data problems during the processes of data collection, integration and cleansing, and how to identify them. What are the different options for resolving these generic issues?
- Search and list all data quality problems you have identified in BeeSafe Insurance’s dataset. Explain how you identified the problems (e.g. give examples of the issues) and how you propose to address/solve them.
b) Data analysis - Guidelines
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- To fully complete the Section, it is recommended you support the analysis by producing the following data tables:
Ø Data and trends in total retention volume and revenue by month, by year across the 3 years period.
Ø Benchmark comparisons of retention volume and revenue value between cities by quarter, by year across the 3-year period.
Ø Benchmark comparisons of business insurance categories performance covering retention volume and revenue value by quarter, by year across the 3- year period.
- Include in a separate section the summary exploratory data calculations for total retention volume and total revenue value. The analysis could include for example top and bottom performing business insurance categories, averages, standard deviations; top and bottom performing time- periods, etc.
- Ensure your tables are professionally presented: Headings, units, data formats. Highlight and annotate key data elements.
- For each table, paste the table in your report, include firstly an explanation of the table and its contents, then a bullet- point list of what you can see or infer from your analysis of the data.
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Section 3 (LO3)
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Critically appraise the presentation of data within a business environment
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Guidelines:
- Start the analysis by producing different graphics/charts showing visually the performance of BeeSafe Insurance. It is suggested to produce the following charts showing:
- Comparison of revenue value trends across cities over time,
- Service categories retention volume and revenue value over the 3-year period
- Assess the impact of the AI chatbot in Brazil during 2023 in comparison with the previous years.
- Ensure you provide well-presented and labelled charts
- Use a combination of visual data presentation techniques such as bar charts, stacked bar charts, trend charts, pie charts and tree map charts (each graphic type has itsstrengths and weaknesses so choose the best graphic typethat suits your analysis)
- For each chart, paste the chart in the report, include firstly
an explanation of the chart and its contents, then a bullet-
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point list of what you can see or infer from your analysis of the data.
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Section 4 (LO1)
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Critically evaluate the evolving use of data in solving business problems, presenting logical arguments based on evidence
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Guidelines:
- What conclusions can be inferred regarding BeeSafe
Insurance’s performance? Remember to answer the three project objectives raised by the top management.
- What are your business recommendations to be presented
to BeeSafe Insurance’s CEO and Board of Directors?
- Include any suggestions related to data analytics and its better use within the company.
- Note that it is also acceptable to add to your data analytics recommendations, possible actions that BeeSafe Insurance might take, based not only on your findings but also on your wider knowledge of business and the business insurance sector (you can use what you have learned in GSS and LTDD modules!).
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Report structure and references guidelines:
- Your report should follow the section naming structure and order set out in the Brief. You should also add your own sub-headings as you see fit to demonstrate your ability to on- develop structure and content.
- Your report should include an auto-generated contents page including section headings and sub-headings. The contents page should also include a page-referenced list of all tables, charts and figures provided in your report. Remember to number all pages in your report, for example ‘Page 8 of 12’.
- Ensure you develop your discussion in a logical progression: Findings, inferences, conclusions, recommendations.
- Do not make general assertions without supporting evidence.
- Zero spelling errors and grammatical mistakes.
- Cite all your sources in the body of the text and in the Referencing using the Harvard Referencing style.
- Include a blend of industry research, case studies and academic references.
2.Report Structure
You should set out your report according to the following heading structure. You should add sub- headings under this overall structure as you feel fit to demonstrate your ability to on-develop the section themes and to provide meaningful sub-structure. But you must use this overall structure in order to provide a consistent framework against which your marker will allocate marks. You will be deducted marks if you do not follow this structure. Also note that there is no requirement for producing an Executive Summary.
University Cover Page Table of contents
- Introduction and project plan
- Data quality issues and remedies
- Data analysis and commentary
- Data charting and commentary
- Conclusions and recommendations
- References
- Appendix (optional)
In addition, you may wish to add further appendices as you see fit in order to support your work.
Word count: 2,500. Cover Page, Table of Contents, References, Appendices, Tables, Charts and Figures do not count towards word count.
1.Marking Guide
The assignment is marked out of 100 and counts towards 100% of your module mark. The following table shows the Sections, marks and marking rubric. You should iteratively self-assess your performance against the Marking Guide as you develop your draft submission, in order to evaluate your performance against your target grade.
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Fail
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Marginal Fail
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Pass
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Merit
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Distinction
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High Distinction
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Learning
Outcome
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(0-39%)
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(40-49%)
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(50-59%)
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(60-69%)
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70-79%
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(80-100%)
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LO1:
Critically evaluate the evolving use of data in solving business problems, presenting logical arguments based on evidence.
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Inadequate or weak critical evaluation of the use of data in solving business problems with some difficulties.
Largely imitative and descriptive consideration s on how to use data in business issues. Some difficulty with presenting logical based arguments/ab sence of evidence based
arguments.
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Limited critical evaluation of the use of data in solving business problems.
Original work with personal reflection and broad evidence- based critique.
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Satisfactory critical evaluation of the use of data in solving business problems.
Wholly original work with good reflection and solid, well- reasoned judgements forming from evidence- based critique.
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Good critical evaluation of the use of data in solving business problems.
Demonstrates intellectual originality and imagination in presenting logical arguments based on evidence.
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Excellent critical evaluation of the use of data in solving business problems.
Demonstrates intellectual originality, integrity, coherence and imagination in presenting logical arguments based on evidence.
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Outstanding critical evaluation of the use of data in solving business problems.
Demonstrates intellectual originality, integrity, coherence, creativity and imagination in presenting logical arguments based on evidence.
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LO2:
Explore how data analytics can be used within a business context.
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Inadequate or weak exploration of how the data can be used within a business context with some difficulties.
The analysis presented is not in line with requirements (e.g., data is not cleaned).
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Limited exploration of how data can be used within a business context.
Original work with an inappropriate breath of techniques explored to answer the business issues. The analysis presented is partially in line with requirements (e.g., data is not cleaned or poor understandin g of the cleaning process).
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Satisfactory exploration of how data can be used within a business context.
Wholly original work with an appropriate breadth of techniques explored to answer the business issues. The analysis presented is basically in line with requirements (e.g., data is not fully cleaned, but the approach is appropriate).
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Good exploration of how data can be used within a business context.
Demonstrates intellectual originality and imagination and presents a good breadth of techniques explored to answer the business issues. The analysis presented is in line with requirements (e.g., data is cleaned).
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Excellent exploration of how data can be used within a business context.
Demonstrates intellectual originality, integrity, coherence and imagination in exploring the best analytical solutions in answering the business issues. The analysis presented is in line with requirements and is clearly discussed with an evidence- based approach although the evidence shown lacks depth of
analysis.
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Outstanding exploration of how data can be used within a business context.
Demonstrates intellectual originality, integrity, coherence, creativity and imagination in exploring the best analytical solutions in answering the business issues based on evidence. The analysis presented is in line with requirements and is clearly discussed with an evidence- based approach with also a clear analysis of the
procedure.
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LO3:
Critically appraise the presentatio n of data within a business
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Inadequate or weak critical appraisal of the presentation of data within
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Limited critical appraisal of the presentation of data within a business
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Satisfactory critical appraisal of the presentation of data within a business
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Good critical appraisal of the presentation of data within a business environment.
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Excellent critical appraisal of the presentation of data within a business
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Outstanding critical appraisal of the presentation of data within a business
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environmen t.
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a business environment with some difficulties. Largely imitative and descriptive consideration s on how to present data in business contexts.
Some difficulty with presenting logical based arguments/ab sence of evidence based
arguments.
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environment. Original work with personal reflection and broad evidence- based critique.
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environment. Wholly original work with good reflection and solid, well- reasoned judgements forming from evidence- based critique.
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Demonstrates intellectual originality and imagination in presenting logical arguments based on evidence.
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environment. Demonstrates intellectual originality, integrity, coherence and imagination in presenting logical arguments based on evidence.
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environment. Demonstrates intellectual originality, integrity, coherence, creativity and imagination in presenting logical arguments based on evidence.
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LO4:
Critically evaluate different business analytical techniques as part of planning a data analytics initiative.
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Inadequate or weak critical evaluation of the techniques used and of their consequences with some difficulties.
Largely imitative and descriptive consideration s on how to plan a data project in business contexts and in how to
interpret the
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Limited critical evaluation of the techniques used and of their consequences within a business environment. Original work with personal reflection and broad evidence- based critique.
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Satisfactory critical evaluation of the techniques used and of their consequences within a business environment. Wholly original work with good reflection and solid, well- reasoned judgements forming from evidence- based
critique.
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Good critical evaluation of the techniques used and of their consequences within a business environment. Demonstrates intellectual originality and imagination in presenting logical arguments based on evidence.
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Excellent critical evaluation of the techniques used and of their consequences within a business environment. Demonstrates intellectual originality, integrity, coherence and imagination in presenting logical arguments
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Outstanding critical evaluation of the techniques used and of their consequences within a business environment. Demonstrates intellectual originality, integrity, coherence, creativity and imagination in presenting logical arguments
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conclusions. Some difficulty with presenting logical based arguments/ab sence of evidence based
arguments.
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based on evidence.
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based on evidence.
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Research Skills
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Inadequate academic/ intellectual skills with some difficulties. Largely imitative and descriptive. Some difficulty with structure and accuracy in expression, but developing practical/prof essional skills.
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Limited academic/int ellectual skills. Original work with personal reflection and broad evidence- based critique. Solid structure and accuracy in expression.
Practical/prof essional skills evident.
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Satisfactory academic/int ellectual skills. Wholly original work with good reflection and solid, well- reasoned judgements forming from evidence- based critique.
Consistent structure and accuracy in expression. Practical/prof essional skills
established.
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Good academic/int ellectual skills.
Demonstrates intellectual originality and imagination
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Excellent academic/int ellectual skills.
Demonstrates intellectual originality, integrity, coherence and imagination.
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Outstanding academic/int ellectual skills.
Demonstrates intellectual originality, integrity, coherence, creativity, and imagination working consistently in the higher cognitive domains to a professional standard.
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Referencing
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Inadequate references and notes but may contain inconsistencie s, errors or omissions.
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Limited and full and appropriate references and notes with minor or insignificant errors
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Satisfactory with precise, full and appropriate references and notes.
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Good with precise, full and appropriate references and notes at a high standard.
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Excellent with precise, full and appropriate references and notes at near- publishing
standard.
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Outstanding with precise, full and appropriate references and notes at publishing standard.
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