This assignment relates to the following Learning Outcomes: 1). Analyse data req

This assignment relates to the following Learning Outcomes:
1). Analyse data requirements and implement queries in an organisational context
2). Apply statistical tools and techniques to support decision-making in an organisational context
3). Discuss the ethical implications associated with data utilisation in an organisational context
Aim of the Assignment:
– The aim of the assignments is to develop the knowledge, skills, and competencies relevant to business data and decision-making
Assignment Instructions:
For this assessment, you are not allowed to use Generative AI to:
– Generate definitions or writing used in your final report
-Produce counter argguements or refine thinking on your final submission
-Write any code that is needed for the assessment.
Requirements: PART A – DATA PREPARATION (20 MARKS)
-You will be provided an Access database containing two tables, a financial data table and a company table. The financial data table includes 190+ financial indicators, such as revenue, cost of revenue, gross profit, R&D expenses, free cash flow margin, EBITDA, etc., for 3500+ stocks within the US stock market from 2014 to 2018. The financial indicators have been scraped form Financial Modelling Prep API and are those found in the 10-K filings that publicly traded companies release yearly. The class column (distinct from financial indicator) in financial data table is your target variable which represents,
– if the value of a stock increases during that year, then class = 1.
– if the value of a stock decreases during that year, then class = 0.
(For example) : stocks that belong to class 1 are stocks that one should buy at the start of year 2015 and sell at the end of year 2015.
Part A: Before commencing the analysis, kindly complete the following tasks:
– Randomly select a set of 100 company stocks along with 15 financial indicators according to your preferences from the provided database. Upon completion of the data selection, store the chosen data within a new table in Access. Then, demonstrate your final data selection with your Access SQL in the word (including the list of 15 chosen financial indicator, the list of selected company and overall row count in your join dataset). (8 marks)
– Examinse the ethical implications of data utilisation concerning data accuracy and bias and provide two comments in word (6 marks)
-Use Power Query to clean the selected data and provide a comprehensive statement about your data cleaning procedures n the word. Include step by step explanations ( 6 marks).
PART B : Data Analysis and Report (80 marks)
In this part, kindly complete following tasks:
– Employ Excel to perform an in-depth exploratory data analysis (EDA) on the chosen data in part A and generate visualizations to present the findings and insights form your analysis. The outcomes should integrate into your report.
– Ascertain the top 10 most significant financial indicators from 15 financial indicators in part A with respect to the target variable. And then, contract a predictive machine learning model (decision tree) in Orange to understand whether it is prossible to classify the future perforance of a stock by looking at the chosen financial indicators. Ensure that the model performance outputs and comments regarding both the model and its outputs are integrated into your report.
– The report should be no more than 1,000 words and no les than 900 words (not include cover page, table of contents, reference, and Appendix). There will be penalty for exceeding the maximum word limit specified.
You are free to generally follow the reports structure below:
1). Cover page
2). Introduction
3). Visualization & Data Analysis
4). Investigations and Findings
5). Conclusion
6). References
7). Appendix (if applicable)
Please refer to the Grading Rubric on the mark allocation and as a guide to ensure you satisfy the criteria for the Assignment.