4033.1.1 : Advanced Elements of Data Visualization
The graduate describes the fundamentals of effective story-telling through data visualization.
4033.1.2 : Configure Data for Visualization
The graduate configures data for visualization.
4033.1.3 : Visualizing Data Patterns and Proportions
The graduate creates patterns and proportions for effective data visualization.
4033.1.4 : Visualizing Relationships and Differences
The graduate creates visualizations representing the relationships and differences of the data.
4033.1.5 : Data Visualization Presentation
The graduate implements best practices using data visualization techniques for effective storytelling.
The purpose of this task is for you to visually showcase data by identifying appropriate sources of data, scraping and cleaning data, and presenting those data in different formats. As you complete this task, you will create a dashboard with multiple visualization formats, use your data to effectively tell a story, and justify the choices you make. Your choices will be based on the criteria in the scenario and requirements sections below. You will also submit a brief written response to explain how you chose to present your data and why your methods are appropriate.
You must submit all your data files (both raw and cleaned) in spreadsheet format (e.g., .csv, .xls, .xlsx). To scrape your data, choose reliable web sources and use tools common to the industry such as Python, R, or other industry standard tools. You should use Tableau to create all your graphic representations (e.g., scatter plots, bubble charts, density plots, histogram matrices, heat maps, parallel coordinate plots, multidimensional scaling). Submit these Tableau outputs as .pdf files. Use a word processor to create your accompanying written report, as outlined in the requirements. This report should be two pages long, formatted in 12-point Arial font, and double spaced. Submit the reports as a .doc, .docx, or .pdf file.
The following artifacts are required to be submitted as part of this task:
Your submission will not be evaluated if these three artifacts are not submitted in the proper format.
You have been hired as a data analyst and one of your first tasks includes selecting a car, primarily for your use, that will become part of the company fleet. Your manager has already narrowed down the choices to four vehicles: a 2019 Ford Escape, 2019 Honda CRV, 2019 Hyundai Santa Fe, or 2019 Toyota Rav 4. Because you will purchase the car with company funds, your manager has asked you to select a vehicle based on the company’s criteria; however, your own criteria for choosing a car are different. You must use data visualization best practices to create a dashboard, using data you will scrape, and tell a story for your manager to support your car selection.
Criteria 1 (Company Criteria):
Safety features – weighted at 10
Maintenance cost – weighted at 5
Price point – weighted at 7
Criteria 2 (Your Criteria):
Note: You should include your personal weighting for the individual aspects of your criteria as part of your response to the requirements below.
Your submission must be your original work. No more than a combined total of 30% of the submission and no more than a 10% match to any one individual source can be directly quoted or closely paraphrased from sources, even if cited correctly. An originality report is provided when you submit your task that can be used as a guide.
You must use the rubric to direct the creation of your submission because it provides detailed criteria that will be used to evaluate your work. Each requirement below may be evaluated by more than one rubric aspect. The rubric aspect titles may contain hyperlinks to relevant portions of the course.
File name may contain only letters, numbers, spaces, and these symbols: ! – _ . * ‘ ( )
File size limit: 200 MB
File types allowed: doc, docx, rtf, xls, xlsx, ppt, pptx, odt, pdf, txt, qt, mov, mpg, avi, mp3, wav, mp4, wma, flv, asf, mpeg, wmv, m4v, svg, tif, tiff, jpeg, jpg, gif, png, zip, rar, tar, 7z
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