ADMN 873, Data Management & Visualization Project Instructions PROJECT GOALS The goal of this project is to allow students to apply the concepts that they learn during the course to

a problem (preferably related to business/economics but not essential) that they find important and interesting. During the project students will collect data from several sources, wrangle/clean it, relate the data sets together to the extent possible, design a means to store it, and conduct analyses and visualizations to develop insights. PROJECT TASKS 1. Form Your Groups. Before starting the project, read your classmates' self-introductions on Canvas, then identify those individuals who you believe have interesting and valuable ideas and work experiences from the standpoint of a project you would like to work on. Contact them and find out if they are interested in working with you on this project. Each group should have 4±1 members (this will depend on course enrollment). Groups must be formed by the date indicated on Canvas. 2. Define Your Problem: Research Question Identification/Problem Definition. Identify an interesting area you wish to investigate. Develop some questions you would like to be able to address. Identify several data sources that will permit you to address your research questions. 3. Submit Project Proposal. Submit your project description, including data sources, on Canvas. 4. Identify Data Sources & Collect Data. Identify Potential Data Sources. The data that you use in this project will be drawn from various electronic sources including databases (broadly defined), web pages, social media websites, etc. You must have at least 3 different sources of data and one of the data sources must be from a social media website (e.g. Twitter, Reddit, Facebook, LinkedIn, etc.). At least one of your datasets must have at least 1000 records. You may end up with three or more separate, but related data sets. This is OK. If possible, try to relate the dataset together based on a common field (which may be present in the original data, or that you add to the datasets). 5. Clean & Organize Your Data. Once you have collected your dataset you must clean and organize I it to prepare for analysis. Use R, Excel (functions/commands or Power Query), and/or Power BI to organize and clean your data. As part of your submission, include a detailed description of your data cleansing process (usually a bulleted list of steps is good for this). 6. Analyze Your Data. Use R, Excel, and/or Power BI to do Exploratory Data Analysis (EDA). Perform descriptive analytics and gain insights into your research question. This could include conducting some basic statistical analysis including examining the data distribution, computing means, medians, standard deviation, correlations, regression analysis etc. Note that through EDA it is common to find errors, omissions, and anomalies in the data. Make note of these and rectify them as appropriate. 7. Visualize Your Data. Use Power BI to visualize some of your interesting findings. Create multiple visualizations and organize them well with dashboard(s). Include documentation of data sources, assumptions, and key process steps within the Power BI file itself. The file should be able to stand independently so that someone could use it to gain insight into the issue you addressed. While your visualizations should be guided by your research questions, you should seek to create a tool that someone can use interactively to learn more about the situation. Thinking about different "personas" (perspectives, viewpoints) will help you in this process. PROJECT DELIVERABLES There are four main deliverables from this project: 1) project report; 2) technical work product, 2) project presentation and 3) project evaluations of others' projects. 1. Project Report: Your final project report should document each of the tasks outlined above. Please include the sections listed below. The report should be able to stand independently from your work product. That is, someone may only read the report, so include sufficient detail, summaries, and visualizations within the report itself. The report should be professional quality, as one may find in an industry publication, and written in the 3rd person. a. Title Page: Title, authors, course, date. b. Abstract (one-paragraph summary of the project and key findings; should be able to stand apart from the rest of the document). C. Problem Definition, Research Questions, and Key Assumptions d. Data Source Identification and Data Description e. Data Wrangling Process f. Data Analysis & Visualization (incorporate visuals directly in report, or in an appendix with appropriate references in the text). g. Conclusions. What are the key take-aways regarding the questions you are investigating, as well as any key insights gained from doing the analysis? h. Limitations. What are the limitations of the analysis? What would be required to remove or reduce the respective limitations? Lessons Learned - What did you do effectively for this project? If you had a chance to redo the project (or had more time), what would you have done differently (lessons learned)? References - References should be presented using the APA style. Appendix - Feel free to include any supplemental materials that do not fall under any of the above headings in the Appendix. i. j. k. 2. Work Product. This comprises the Power BI (PBIX), Excel, and, associated R files (scripts), and data file(s). Include documentation so that someone can use them to assess what you have done and to use what you have done to gain further insight into the issue. If it is not obvious, include a short file that documents what every file submitted is. Include the data files as separate files in their native format (e.g., CSV) or in Excel tables. 3. Project presentation. Each group will prepare a 12-15 minute video presentation. Explain each of the project tasks listed above. Also detail the data wrangling / analysis / visualization lessons learned from the project. Each student in the group is required to present a portion of the final project. Show the visual (e.g., PowerPoint) and the speaker in the video. Upload an MP4 video file or provide a link to the video. Also post the video to the Discussion Board on Canvas. For the presentation, it is important that students: a. be dressed appropriately (business casual), maintain eye contact with the audience (or camera) and seldom refer to notes. b. present materials in a clear, coherent, logical & interesting manner that can be followed easily. C. convey logical and persuasive arguments. d. demonstrate a strong command of materials that they are presenting. e. make effective use of visual aids. Submission: Submit the report (MS Word or PDF), files associated with the Work Product, the PowerPoint file used for the presentation, and links to any Power BI and/or Tableau visualizations that are web-based. Submit the MP4 presentation file to the Discussion Board provided. 4. Evaluation of Other Projects. After projects are submitted, each person will review 2 other projects based on the video presentations. A feedback form will be provided for this.