1) Executive summary – Max 1 pg. This should concisely summarize your report including your questions, analyses, key insights, and recommendations.

I provide the instructions and and PowerPoint sides. Just Ineed Executive summary – Max 1 pg. This should concisely summarize your report including your questions, analyses, key insights, and recommendations. Final Project Description I. Introduction The final project will simulate a scenario in which a consulting group is hired to provide recommendations to the management team of a business/organization on an accounting, finance, or other business-related issue. Individuals/groups of up to 4 students will identify both a dataset and a business or organizational problem to address. You will provide a write-up containing a comprehensive summary and analysis, as well as recommendations for further action. Furthermore, you will present your findings to the class and answer questions simulating a presentation to the management team. At a minimum, your write-up should include the following: 1. Background Overview Summarize key facts about the business/organization. Describe key factors that affect the organization’s performance as a business or other organizational entity. If relevant, describe important current events affecting the organization. 2. Your Role and Motivation What is the big picture problem you have been asked to address or solve with data analytics? Why is addressing this issue relevant and important to your organization? 3. Ask the Questions Specifically, what questions will you address as part of your solution to this problem? How will you use data analytics to address these issues? 4. Master the Data Describe your dataset. Include a description of important data elements/fields and relevant summary statistics. Identify issues with data quality and describe important data manipulations/transformations and additional variables you developed. 5. Perform the Test Plan How will you analyze the data? Describe the appropriate models and other specific techniques that you apply towards addressing your questions. What are the main limitations of your analyses? Are you concerned about data quality issues or bias in your dataset or analysis? 6. Share the Story Provide a clear dashboard of key insights from your analysis. What are the key takeaways of your analyses? Provide two recommendations for your business/organization. These should be directly supported from your data analysis and visualizations. 7. Extensions What additional actions or analyses would be useful to conduct in the future? What additional questions would be useful to answer that is beyond the scope of your project? You will be graded on four components: (1) The relevance of your project towards identifying and addressing an important business/organizational/governmental issue. (2) The quality and depth of your execution. This includes the appropriateness of your methodology and analysis in answering your questions and supporting your recommendations, as well as the validity of assumptions made in your analysis. (3) The overall persuasiveness and clarity of your write-up. (4) Presentation - including the use of tables, graphs as well as the clarity and persuasiveness of the presentation. (5) Last, you will be graded on appropriate use of course material. II. Deliverables Part 1: A team member should email me your group member names and group member emails. You must also specify the proposed dataset you are currently interested in. However, you may change your final dataset choice for the final project deliverable if you choose. Part 2.1: Write-Up Required (12-point font, single spaced) 1) Executive summary – Max 1 pg. This should concisely summarize your report including your questions, analyses, key insights, and recommendations. 2) Report – Max 3 pg. This should detail your analyses, including your responses to the seven discussion topics described above. 3) Report Appendix – 3 pgs. This should contain supporting tables, figures, visualizations, and calculations for your report. Include a table with variable definitions if necessary to understand your figures. Every table should be clearly labeled with a title. Descriptions (10-pt font) should be included underneath tables that are not easily understandable. Part 2.2: Supplementary Project Files In addition to the write-up, you may include any other relevant Tableau/Excel/other project files. You may submit this as a file attachment or a file sharing link (e.g., Dropbox). You do not need to submit your dataset, but you should include a link or description for how to download it. Part 3: Final Project Presentation (December 2nd and December 9th) Presentations will be made during the last two classes of the semester. All teams should be ready by December 2nd with their presentation. Each team will present the project as follows: 1) A 10-minute presentation and 3-5 minutes for questions and answers. 2) All team members must be active in the presentation. III. Suggestions and Tips 1. The final project description is intentionally broad, and I encourage you to spend time exploring datasets that would allow you to answer important, contemporary, and interesting questions. There is an enormous variety of public, open datasets available online. Popular sources of data for this project include governmental data sources, such as NYC Open Data and the Chicago Data Portal. You may also use any of the WRDS databases Baruch is subscribed to. Additional data sources are listed in chapter 11 of the textbook. However, you are free to use any publicly available dataset, as well as combine datasets from multiple sources for your project. 2. Your project should emphasize your recommendations and insights of your analyses. While it is necessary to discuss data issues (e.g., data cleaning procedures), only discuss this in as much detail as is necessary to understand your analysis. Be bold with your analysis, and when possible make assumptions and estimate relevant quantities for your analysis. For example, you could estimate the impact of your recommendation on sales revenue, costs, profits, prices, customer demand, or various other key metrics. 3. Start exploring datasets EARLY to identify data issues that will be time consuming or challenging to deal with. For example: a. Your dataset may require a lot of manual data cleaning before you can analyze it. b. Your dataset may be missing important values that you need for your analysis. c. Your dataset may be too large to download all at once. In this case, you may need to work with subsets of the data. d. Your analysis may benefit from learning a new software tool to work with your dataset