University of North Dakota (UND)
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Data Mining, Analytics and Visualization

Closed
Northeastern University
Northeastern University
Boston, Massachusetts, United States
Tracy Robin
XN Partnership Development Coordinator
(7)
5
Timeline
  • September 17, 2024
    Experience start
  • December 10, 2024
    Experience end
Experience
2/5 project matches
Dates set by experience
Preferred companies
Anywhere
Any company type
Any industries
Categories
Information technology Databases Data analysis Data modelling
Skills
python business analytics big data data analysis data mining
Learner goals and capabilities

Students from a global, experiential, research university built on a tradition of engagement are ready to contribute to your organization's mandate in areas ranging from dashboarding/data visualization, data mining, statistical analysis and modeling, evidence-based management (analysis yielding business insights), and/or AI/machine learning. This is your opportunity to connect with students and faculty from a renowned institution in New England that consistently ranks among the top universities in the United States and globally and is known for its focus on interdisciplinary education, extensive research output, and collaborative student culture.

Learners
Graduate
Beginner, Intermediate, Advanced levels
80 learners
Project
40 hours per learner
Learners self-assign
Individual projects
Expected outcomes and deliverables

Final deliverables will be confirmed in consultation with the course instructor and may include but are not limited to:

  • A slide deck with conclusions and recommendations for a 15-minute consulting presentation.
  • A written report with details of the developed predictive models, including insights and overall recommendations inferred from such models.
  • All applicable source code.
Project timeline
  • September 17, 2024
    Experience start
  • December 10, 2024
    Experience end
Project Examples

We invite you to identify your project in the title using the associated keywords. For most projects, we require at least 500 data points, and all data must be provided by the industry partner or publicly available with guidance on how to access it. The focus of the project will be the analysis, not the gathering of data. In your project scope, please address:

  1. Define the problem to be solved and how data analytics will help.
  2. What tools will the students use?
  3. What format is the data in currently?
  4. How large is the data set?
  5. How will you share the data?
  6. Describe your desired deliverable.

Sample project areas

  • A data mining project would allow student teams to evaluate, analyze, and report data for the methods used and insights discovered during case studies.
  • A communication and visualization project utilizing R Shiny, Tableau, and R as data visualization tools.
  • An integrated project offers a practicum in developing and delivering predictive data analysis for strategic decision-making in organizations. It offers students an opportunity to apply the principles and tools of analytics to real-world problems in business organizations and to develop and present analytical insights and recommendations for the successful implementation of their capstone project. (500+ data points, simple analysis, dashboarding, and visualization working in Tableau and Python, modeling.)
  • A capstone project expects students to present analytical insights and recommendations for successfully implementing their capstone project and their individual project proposal. (500+ data points (1000+ is better) much more advanced technical course. Statistical analysis and modeling, evidence-based management (analysis yielding business insights), AI/machine learning. predictive modeling.)
  • Analyze customer segmentation relative to different products and services to enhance marketing campaigns and refocus your products/services.
  • Investigate predictive models to understand trends in sales, attrition rates, and profits that impact your business.
  • Propose new ways to visualize data through tables and plots that can provide new insights for managers.
  • Reduce customer churn.
  • Maximize revenue through up-sell and cross-sell.
  • Determine sales trends.
  • Accurately predict customer behaviors.
  • Improve new customer acquisition.
Companies must answer the following questions to submit a match request to this experience:

Participating industry partners should supply at least 500 data points, and all data must be provided or publicly available with guidance on how to access by the sponsor. The focus of the project will be the analysis, not the gathering of data. In your project scope, please address: Define the problem to be solved and how data analytics will help. What tools will the students use? What format is the data in currently? How large is the data set? How will the sponsor share the data? Describe your desired deliverable.

Be available for a quick phone call with the organizer to initiate your relationship and confirm your scope is an appropriate fit for the experience.

Provide a dedicated contact who will be available to answer periodic emails or phone calls over the duration of the project to address students questions or provide additional information.

Be available for an introductory session at the beginning of the project (in person or virtual).

Minimum of 2-4 interactions with the students in-person or remotely (approximately 4-6 hours over the duration of the project).

Provide students with the data necessary to conduct their data mining analysis.