Business Analytics Capstone - Winter 2022

BUS1141
Closed
Cambrian College
Sudbury, Ontario, Canada
Sidney Shapiro
Professor and Program Coordinator
(29)
3
Timeline
  • January 2, 2022
    Experience start
  • October 1, 2021
    Partner check in and feedback
  • January 26, 2022
    Partner check in and feedback
  • February 25, 2022
    Experience end
Experience
15/15 project matches
Dates set by experience
Preferred companies
Anywhere
Any
Any industries
Categories
Information technology Market research Operations Project management
Skills
business analytics big data analytics big data program evaluation dashboard research surveys
Learner goals and capabilities

This capstone project is part of the Business Analytics (BAPG) certificate program. The students will participate in research projects on very large and/or complex data, gather data, conduct program evaluation, develop and deploy surveys, help with funding applications, create dashboards and analysis, and work with various types of data to support your business decisions using Business Analytics.

Students apply analytical models, methodologies, and tools learned in the program to analyze data sets to predict trends and challenges, and investigate with the purpose of developing analytics solution for your organization. Faculty mentors will work with students to ensure the capstone project reflects, and encompasses, best practices for big data analytics and project management.

Learners
Graduate
Any level
30 learners
Project
210 hours per learner
Learners self-assign
Teams of 2
Expected outcomes and deliverables

The final project deliverables will include:

  • A report on students’ findings and details of the analytics solution.
  • A final presentation of the solution and recommendations to your organization.
  • Future collaboration ideas will be identified based on current project outcomes.
Project timeline
  • January 2, 2022
    Experience start
  • October 1, 2021
    Partner check in and feedback
  • January 26, 2022
    Partner check in and feedback
  • February 25, 2022
    Experience end
Project Examples

The capstone project provides an opportunity for businesses and learners to collaborate to identify and translate a real business problem into an analytics problem. The project can include elements of data collection & preparation, data modeling and analysis with the potential to include predictive modeling, machine learning implementation, constructing dashboards or spreadsheets, programming, statistical analysis, and a solution deployment plan. Capstone project results/recommendations will be communicated in a report document and a final presentation.

You should submit a high-level proposal/business problem statement including relevant data sets and definitions, a list of acceptable tools (if applicable), and expected deliverables. Business datasets could be provided based on a non-disclosure agreement or in an anonymized/synthetic data format that is relevant to your organization and business problem. The capstone course instructors will review the documents to confirm the scope and timing of the proposed problem and its alignment with the capstone course requirements.

Analytics solution may be applicable for (however they are not limited to) the following topics:

  1. Customer acquisition and retention
  2. Non profit program evaluation and funding
  3. Analyzing business data
  4. Merchandising for trade areas (categories)
  5. Quantifying Customer Lifetime Value
  6. Determining media consumption (mass vs digital)
  7. Reduction of client churn (lower abandonment)
  8. Cross-sell and up-sell opportunities
  9. Develop high propensity target markets
  10. Customer segmentation (behavioural or transactional)
  11. New Product/Product line development
  12. Market Basket Analysis to understand which items are often purchased together
  13. Ranking markets by potential revenue
  14. Consumer personification

To ensure students’ learning objectives are achieved, we recommend that the datasets are at least 20,000+ rows in size. Data need not be ‘clean’; it is advantageous to the students’ learning experience to require hygiene prior to analysis. Similarly, if more than one database is provided, which must be conjoined, students will be required to integrate them. This supports the learning experience and minimizes partner data preparation.

Note: Students can sign a NDA, if required.

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

Provide students with written feedback half way through the project and at its conclusion

Provide a dedicated contact who is available to answer periodic emails or phone calls over the duration of the project to address students' questions. Checking in with students as the project progresses with regular meetings, reviews, and updates.

Be available for a quick phone call or meeting with the instructor to initiate your relationship and confirm your scope is an appropriate fit for the course.