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Big Data Analytics - Winter 2024

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Big Data Analytics Program, Georgian College
Big Data Analytics Program, Georgian College
Barrie, Ontario, Canada
SS
Shubhneet Sandhu
Junior Project Manager
2
General
  • Post-graduate
  • 60 learners; teams of 2
  • 70 hours per learner
  • Dates set by experience
  • Educators assign learners to projects
Preferred companies
  • 2/3 project matches
  • Canada
  • Academic experience
  • Any company type
  • Any industries
Categories
Data Data visualization Data analysis Data modelling Databases Data science
Skills
problem solving sales & marketing data analytics data visualization big data
Project timeline
  • February 26, 2024
    Experience start
  • August 6, 2024
    Experience end
Overview
Details

Big Data allows users to visualize past, present, and future patterns by linking and presenting information in meaningful ways. Data Analytics offers deeper insight into the meaning of data sets by telling the story behind the information. Graduate students from Georgian College's Big Data Analytics program will implement data analytics to uncover insights into challenges or opportunities specific to your organization.

Learner skills
Problem solving, Sales & marketing, Data analytics, Data visualization, Big data
Deliverables

The final project deliverables are:

  • A written report outlining conclusions and recommendations.
  • A team presentation to your organization explaining findings and recommendations.
  • Data files and models.
Project Examples

Beginning this Fall, teams of students will devote 50+ hours to solving a data analytics challenge faced by your organization. Student work will include:


1) Framing the problem.

2) Acquiring and managing large data sets.

3) Applying modern statistics.

4) Identifying and implementing the necessary technology infrastructure.

5) Providing a sustainable management-level solution.


Project examples include, but are not limited to:

  • Predictive analytics in ecommerce & retail: Which products/categories to market to a customer, given the customer profile?
  • Predictive analytics in investments & trading: Which stocks or securities to purchase following a sequence of events?
  • Pricing for new technology products & services: How to price a new tech product, based on competitive, customer, and transactional data?
  • Credit scores & ratings: How to assess the credit risk of a borrower, based on the borrower profile and meta data?
  • Financial fraud likelihood: What is the likelihood of fraud for a user attempting to access your personal finance solution?
  • Customer segmentation & targeting: What value to assign to a customer based on the past purchase and/or transactional data and customer profile?
Additional company criteria

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

Do you have any available data? Please describe it.

Do you have a NDA for your company?

Are you available for weekly/bi-weekly meetings with students?

Is your organization start-up, government owned or non-profit?

Number of employees?