Cross-College Entrepreneurial Challenge
Cross-College Entrepreneurial Challenge
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Data Analytics

GESCSDATA
Closed
Main contact
Georgetown University
Georgetown University
Washington, District of Columbia, United States
Lindsey Thomas
Director of Integrated Career Development
2
Timeline
  • October 26, 2021
    Challenge start
  • June 12, 2021
    Mid-point status check
  • November 27, 2021
    Challenge end
Challenge
4/1 project matches
Dates set by challenge
Preferred companies
Anywhere
Any
Any industries

Challenge scope

Categories
Data analysis
Skills
statistical analysis artificial intelligence data analysis research
Learner goals and capabilities

Student consultants are ready to use their technical and analytical skills to support data-driven decision-making. Beginning with the study of SQL and Python, students will learn how to store, access, and manipulate data in relational databases. Students will use statistical tools to understand uncertainties and the predictive capabilities of data models in supporting decisions. Students will develop visualization techniques to understand how the presentation and communication of data provide insight into the analysis and decision-making.

Learners

Learners
Continuing Education
Any level
1 learner
Project
30 hours per learner
Learners self-assign
Individual projects
Expected outcomes and deliverables

Deliverables will vary depending on the scope of the project. Some Example Project deliverable include, but are not limited to:

  • Infographics and visual abstracts
  • Manuals
  • Data sets
  • Process improvement recommendations
Project timeline
  • October 26, 2021
    Challenge start
  • June 12, 2021
    Mid-point status check
  • November 27, 2021
    Challenge end

Project examples

Students will be able to help with data analytics and solving data-driven analytics challenges faced by your organization.

Student(s) work will include, but is not limited to:

  • Framing the problem and helping programs, monitor their progress, analyze data, and seek ways to improve the outcomes.
  • Acquiring and managing large data sets. Students will collect and analyze data—through observations, interviews, and surveys—to find the causes of diseases or other health problems. Our students have a range of training in different statistical packages, including Python and SQL.
  • Applying modern statistical techniques to help with decision-making.
  • Explore the programming technologies involved in data analysis and visualization
  • Acquire an understanding of how data analysis improves the decision-making process
  • Explore the strategic and operational value of using data for decision-making.
  • Identify data sources and create analytical data sets
  • Perform statistical analysis to test the validity of data analysis and decisions
  • Demonstrate the ability to communicate analysis results clearly
  • Explain ethical considerations in data analysis and decision making

Additional company criteria

Companies must answer the following questions to submit a match request to this challenge:

  • Q1 - Checkbox
    Be available for a quick phone call with the instructor to initiate your relationship and confirm that your scope is an appropriate fit for the course.
  • Q2 - Checkbox
    Provide a dedicated contact who will act as the student's primary supervisor over the duration of the virtual placement. A secondary contact should be provided as a backup. Students will interact virtually with their primary contact regularly and as needed.