Big Data Analytics -Ecommerce/Retail/Technology/Investments
General
- Post-graduate; Capstone
- 160 learners; teams of 3
- 120 hours per learner
- Dates set by experience
- Educators assign learners to projects
Preferred companies
- 8/8 project matches
- Anywhere
- Academic experience
- Any company type
- Any industries
Categories
Project timeline
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July 4, 2023Experience start
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August 18, 2023Requirements
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October 13, 2023Design
-
November 20, 2023Development
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December 4, 2023Testing
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December 15, 2023Release
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December 22, 2023Experience end
Timeline
-
July 4, 2023Experience start
-
August 18, 2023Requirements
Requirements
-
October 13, 2023Design
Design
-
November 20, 2023Development
Development
-
December 4, 2023Testing
Testing
-
December 15, 2023Release
Release
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December 22, 2023Experience end
Overview
- Details
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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. Students from Georgian College's Big Data Analytics program will develop and complete data analytics to uncover the insights that drive innovation and change data analytics to uncover insights into challenges or opportunities specific to your organization.
- Deliverables
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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 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?
Required questions to apply
Companies must answer the following custom questions in order to apply to this experience:
Do you have available data?
Do you have in place your company NDA?
Are you available for Weekly/Bi-weekly meetings with the students?
Is your company Start-up , Government owned or Not for profit?
Number of employees?