Data Driven Decisions for Business CW6 Summative Assessment Brief | BPP

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: BPP Business Guide
• 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.

2.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 EverBlue Investment Ltd. to join the Pension Investment department.

EverBlue Investment Ltd. is a finance advisory firm for private investors. For over 20 years, the company has helped clients improve their investments for a better future. Today the firm is trusted by thousands of clients managing a combined wealth value of more than £100 billion. EverBlue Investment Ltd. has successfully grown its business and reputation over the years by providing high net worth clients with expert pension and wealth management. The firm’s investment management and pension planning specialists work in cross-disciplinary financial advisory teams to ensure the services work holistically together. The company offers a full range of pension and wealth management services, including investment advice, estate planning, tax planning, risk management, retirement planning, and more.

EverBlue Investment Ltd. decided to increase its data analytic roles to strengthen its strategic and operational decision-making capabilities. The recruitment strategy is to employ young professionals with strategic and data analytics skills willing to provide EverBlue Investment Ltd. top management with strong evidence-based foundation for their business decisions. They like recruits to have a broad data analytics and business experience combined with strong academic background. Your MSc degree at BPP University was a key element in their decision to recruit you.

The top management is preparing for the next Quarterly Governing Board meeting, and they are interested in showing to the non-executive members of the board the kind of investment performance the company is achieving in the different stock exchange markets. The CEO asked the Pension Investment Director to produce a presentation showcasing the performance of the company’s portfolio of shares in their pension funds.

You have joined the Pension Investment department as data analyst as your first assignment at EverBlue Investment Ltd. As part of the market analysis required to support the presentation to the board, your manager, the Pension Investment Director, 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.

Your job will be to analyse the performance of the investment portfolio held by EverBlue Investment Ltd. in three of the top stock exchange markets where it invests:

Nasdaq (USA), Euronext (EU) and National Stock Exchange (India)

EverBlue Investment Ltd. has experienced strong competition to attract new investors for its pension services, in particular from other pension management firms such as Aegon, Fidelity and Hargreaves Lansdown. So, the investment portfolio performance in these three stock exchange markets is a good indication of the current global attractiveness of the company for pensioners and other investors.

You have been given two kinds of information for your data analysis: the Market Capitalisation and Trade Volume of the aggregated portfolio of investments held by EverBlue Investment Ltd.:

• Market capitalisation refers to the total market value of a company’s outstanding shares. It is thus calculated by multiplying the total number of a company’s shares by the current market price of one share1. Therefore, the market capitalisation of a sector or a stock exchange market is the aggregated market capitalisation of all companies in that sector or stock exchange market. Market capitalisation is a useful figure to examine a company’s structure and profitability, and a stock’s value. Because different corporations have different amounts of shares available for trading, the market cap produces an apples-to-apples comparison regardless of the actual price of a company’s stock. Market capitalisation can be used to determine a variety of key performance metrics, including price-to-earnings and price-to-free-cash flow.
• Trade Volume is the total number of shares of a company (e.g. security) that were traded during a given period of time2. A sector or stock exchange trade volume is the aggregated volume of all transactions (buy and sell of shares) done during that period of time. Trading volume represents the overall activity of a security or a market. Investors often use trading volume to confirm the existence or continuation of a trend, or a trend reversal. It also gives information about the liquidity of a stock. Liquidity refers to the ease with which securities/shares can be bought and sold quickly at stable prices: higher trading volumes are considered more positive than lower trading volumes because they mean more liquidity and better order execution. Essentially, trading volume can legitimize a security’s price action, which can then aid an investor in their decision to either buy or sell that security.

2.3.Project objectives

As part of the presentation to the Board of Directors, you have been approached by the top management with specific objectives related to three decisions they have to present in the meeting.
The Pension Investment Director is interested in identifying the best performance stock exchange. For this purpose, he wants you to:

1  How to Use Market Capitalization to Evaluate a Stock
2  Why Your Health Insurance Expenses Might Soa

best liquidity, so it would be the best candidate to increase the investment in the short term.
As part of the analysis, the Pension Investment Director also wants to understand the company’s performance of the investment portfolio by stock market sector. The goal is twofold: firstly, the analysis will provide indications of the level of diversification of the investment portfolio so that investment can capitalise on sectors which may outperform others during certain periods due to economic conditions, technological advancements, or changing consumer. Secondly, the analysis provides indication of risk levels in different stock market sectors, since some sectors are inherently more volatile than others due to factors such as regulatory changes, competition, or geopolitical events. Assessing risk levels is crucial for investors seeking to balance potential returns with their risk tolerance. EverBlue Investment Ltd. current stock investment is made on the following six stock market sectors:

• Consumer
• Health care
• Industrials
• Technology
• Telecommunications
• Utilities

In this respect, he wants you to:
Perform an analysis of the investment performance by market sector to identify:

• the highest growth market sector which might be considered the best option to increase the investment level in the long-term.
• the lowest growth market sector which might be considered for a review of its investment strategy, and

In 2024, EverBlue Investment Ltd. started the use of artificial intelligence (AI) in the trading process to analyse market data, get investment ideas, and build portfolios. The key AI trading tools adopted by EverBlue Investment Ltd. include machine learning, natural language processing, and big data analytics. The use of AI in trading has enabled EverBlue Investment Ltd. to make better decisions by analysing vast amounts of data quickly and accurately. In addition, AI has enabled the company to automate its trading strategies, allowing to take advantage of market opportunities 24/7.

So, the Pension Investment Director wants to include in the presentation to the Board of Directors the results of the AI implementation in the company trading operations. He wants you to address the objective:

Did the use of the AI trading tools in 2024 have a positive impact on the overall growth of the total market capitalisation hold by the company in the three Stock Exchanges?

The responses to these three objectives should be included in summative report that you save and submit as a PDF format file.

Are You Looking The Solution of This Assignment

Order Non Plagiarized Assignment

2.4.Report Sections

Because this is your first project within EverBlue Investment Ltd., 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 trader analysts, quality issues are present which will require your attention!

IMPORTANT CONSIDERATION FOR YOUR ANALYSIS: The market capitalisation performance is defined as the growth or decline for a particular period of time. It is calculated as the difference between the market capitalisation value at the end of the period and the value at the beginning of the period. For instance, the market capitalisation gain (growth) or loss (decline) of a stock market sector such as Utilities in one year (annual performance) is calculated by subtracting the total market capitalisation value of the sector in December to the total value in January of that year (the percentage growth/loss is calculated as (Dec-Jan)/Jan).

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 EverBlue Investment Ltd., 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 EverBlue Investment Ltd.

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 EverBlue Investment Ltd., as well as its performance by stock exchange and by stock market. 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 Market Capitalisation and Trade Volume trends over time by market sector and by stock exchange, in particular where you can see evidence of any performance change due to EverBlue Investment Ltd.’s use of AI trading tools in 2024. To answer 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 EverBlue Investment Ltd.’s top management. As part of your conclusions, include answers to the three project objectives raised by the Pension Investment Director.

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)
Critically evaluate different business analytical techniques as part of planning a data analytics initiative.	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) EverBlue Investment Ltd. 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.
Section 2 (LO2)
Explore how data analytics can be used within a business context	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 EverBlue Investment Ltd.’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 · To fully complete the Section, it is recommended you support the analysis by producing the following data tables: Ø Data and trends in Market Capitalisation and Trade Volume by month, by year across the 3 years period. Ø Benchmark comparisons of stock market sectors performance covering Market Capitalisation and Trade Volume by month, by year across the 3 years period, Ø Benchmark comparisons of Market Capitalisation and Trade Volume between stock exchanges by month, by year across the 3 years period. · Include in a separate section the summary exploratory data calculations for total Market Capitalisation and total Trade Volume. The analysis could include for example top and bottom performing stock market sectors, 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.
Section 3 (LO3)
Critically appraise the presentation of data within a business environment	Guidelines: · Start the analysis by producing different graphics/charts showing visually the performance of EverBlue Investment Ltd. It is suggested to produce the following charts showing: Ø Comparison of Market Capitalisation trends across stock exchanges over time, Ø Market sectors annual growth/decline over the 3- year period (between 2022 and 2024), Ø Assess the impact of EverBlue Investment Ltd. implementation of AI trading tools in 2024 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 its strengths and weaknesses so choose the best graphic type that 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- point list of what you can see or infer from your analysis of the data.
Section 4 (LO1)
Critically evaluate the evolving use of data in solving business problems, presenting logical arguments based on evidence	Guidelines: · What conclusions can be inferred regarding EverBlue Investment Ltd.’s performance? Remember to answer the three project objectives raised by the Pension Investment Director. · What are your business recommendations to be presented to EverBlue Investment Ltd.’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 EverBlue Investment Ltd. might take, based not only on your findings but also on your wider knowledge of business and the pension and investment sector (you can use what you have learned in GSS and LTDD modules!).

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.

3.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

1.Introduction and project plan

2.Data quality issues and remedies

3.Data analysis and commentary

4.Data charting and commentary

5.Conclusions and recommendations

6.References

7.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 (Student version)

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.

	Fail	Marginal Fail	Pass	Merit	Distinction	High Distinction
Learning Outcome	(0-39%)	(40-49%)	(50-59%)	(60-69%)	70-79%	(80-100%)
LO1: Critically evaluate the evolving use of data in solving business problems, presenting logical arguments based on evidence.	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.	Limited critical evaluation of the use of data in solving business problems. Original work with personal reflection and broad evidence- based critique.	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.	Good critical evaluation of the use of data in solving business problems. Demonstrates intellectual originality and imagination in presenting logical arguments based on evidence.	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.	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.

LO2: Explore how data analytics can be used within a business context.

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).

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).

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).

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).

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.

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.

LO3: Critically appraise the presentatio n of data within a business environmen t.	Inadequate or weak critical appraisal of the presentation of data within 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.	Limited critical appraisal of the presentation of data within a business environment. Original work with personal reflection and broad evidence- based critique.	Satisfactory critical appraisal of the presentation of data within a business environment. Wholly original work with good reflection and solid, well- reasoned judgements forming from evidence- based critique.	Good critical appraisal of the presentation of data within a business environment. Demonstrates intellectual originality and imagination in presenting logical arguments based on evidence.	Excellent critical appraisal of the presentation of data within a business environment. Demonstrates intellectual originality, integrity, coherence and imagination in presenting logical arguments based on evidence.	Outstanding critical appraisal of the presentation of data within a business environment. Demonstrates intellectual originality, integrity, coherence, creativity and imagination in presenting logical arguments based on evidence.
LO4: Critically evaluate different business analytical techniques as part of planning a data analytics initiative.	Inadequate or weak critical evaluation of the techniques used and of their consequences with some difficulties. Largely imitative and descriptive consideration	Limited critical evaluation of the techniques used and of their consequences within a business environment. Original work with personal reflection and broad	Satisfactory critical evaluation of the techniques used and of their consequences within a business environment. Wholly original work with good reflection and	Good critical evaluation of the techniques used and of their consequences within a business environment. Demonstrates intellectual originality and imagination	Excellent critical evaluation of the techniques used and of their consequences within a business environment. Demonstrates intellectual originality, integrity,	Outstanding critical evaluation of the techniques used and of their consequences within a business environment. Demonstrates intellectual originality, integrity,

	s on how to plan a data project in business contexts and in how to interpret the conclusions. Some difficulty with presenting logical based arguments/ab sence of evidence based arguments.	evidence- based critique.	solid, well- reasoned judgements forming from evidence- based critique.	in presenting logical arguments based on evidence.	coherence and imagination in presenting logical arguments based on evidence.	coherence, creativity and imagination in presenting logical arguments based on evidence.
Research Skills	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.	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.	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.	Good academic/int ellectual skills. Demonstrates intellectual originality and imagination	Excellent academic/int ellectual skills. Demonstrates intellectual originality, integrity, coherence and imagination.	Outstanding academic/inte llectual skills. Demonstrates intellectual originality, integrity, coherence, creativity and imagination working consistently in the higher cognitive domains to a professional standard.
Referencing	Inadequate references and notes but may contain inconsistencie	Limited and full and appropriate references and notes	Satisfactory with precise, full and appropriate	Good with precise, full and appropriate references	Excellent with precise, full and appropriate references	Outstanding with precise, full and appropriate references

s, errors or omissions.

with minor or insignificant errors

references and notes.

and notes at a high standard.

and notes at near- publishing standard.

and notes at publishing standar