Big Data Analytics - Winter 2023

BDAT 1011
Closed
Brunilda Xhaferllari
Project Analyst
(6)
3
Timeline
  • February 27, 2023
    Experience start
  • August 12, 2023
    Experience end
Experience
20 projects wanted
Dates set by experience
Preferred companies
Anywhere
Any
Any industries

Experience scope

Categories
Information technology Databases Data analysis Communications Product or service launch
Skills
problem solving sales & marketing data analytics data visualization big data
Student goals and capabilities

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.

Students

Students
Certificate
Any level
140 Students
Project
70 hours per Student
Students self-assign
Teams of 3
Expected outcomes and 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 timeline
  • February 27, 2023
    Experience start
  • August 12, 2023
    Experience end

Project Examples

Requirements

Beginning this June, 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:

  • Q - Checkbox
  • Q - Checkbox
  • Q - Checkbox
  • Q - Checkbox