Final Project

The final project is to replicate the pipeline approach to data analysis on a topic of your choice.

Written proposal due date: Wednesday, April 18th

Project due date: Tuesday, May 8th

Please turn it in by email to myself (galkamaxd at gmail) and Evan (ecernea at sas dot upenn dot edu).

Deliverable:

The final deliverable should include all three of the below items:

• a web-based data visualization with a URL (public or private)
• a document describing the project, the results, and the technical methods used in each step (collection, storage, analysis and visualization)
• all code/spreadsheets/datasets used

Guidelines:

The project is open-ended. The topic and technologies used are up to you. However, the it must satisfy at least two of the items below:

• Data is collected through a means more sophisticated than downloading (e.g. scraping, API).
• At least one of the datasets contains more than 1,000,000 records.
• It combines data collected from 3 or more different sources.
• The analysis of the data is reasonably complex, involving multiple steps (geospatial queries, data shaping, data frame operations, etc).
• The data visualization includes a time component (e.g. moving parts, changing colors).
• The webpage includes a significant interactive component.

As a rough guideline, you should shoot for something that is 3-4 times as involved as the required assignments.

Group projects are permitted. You are also permitted to combine this assignment with one you are working on for another course. But keep in mind that if you choose either of these options, the expectations for the project's scope will be adjusted accordingly.

Submitting work you are already doing for another course is not permitted. If you combine this assignment with one from another course, the portion that you are submitting for this final project must be a clearly defined addition to the original project. In such a case, you will be graded only on the portion submitted for this course, not on the entire project.

Note: The above criteria are guidelines. To receive credit, final projects must receive prior approval in the form of a written proposal.

Grading:

The project will be graded on four criteria:

• Concept: Is it sufficiently complex/challenging/sophisticated? Is the final product useful/interesting/novel? Creativity counts.
• Technical implementation: Was it well thought out? Was each step done correctly? Does it work as described? Is it consistent with the proposal?
• Visualization: How well does the data visualization serve its purpose? Does it tell a clear story? Are the colors/layout/titles well-chosen?
• Writeup: Is all of the above explained clearly? The writeup should be a multi-page document that explains in depth all aspects of the project's implementation as well as the final results.