Big Data Analytics
General
- Certificate
- 80 learners; teams of 3
- 70 hours per learner
- Dates set by experience
- Learners self-assign
Preferred companies
- 3/2 project matches
- Anywhere
- Academic experience
- Any, Startup, Non profit, Large enterprise, Small to medium enterprise, Sole proprietorship, Family owned, Incubator
- Any
Categories
Skills
Project timeline
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November 16, 2020Experience start
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December 8, 2017Final deliverables
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November 24, 2020Project Scope Meeting
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December 5, 2020Proposal and Project Charter Submission
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January 6, 2021Project Implementation and Weekly Status Meetings begin
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April 3, 2021Experience end
Timeline
-
November 16, 2020Experience start
-
December 8, 2017Final deliverables
-
November 24, 2020Project Scope Meeting
Meeting between students and organization to confirm: project scope, communication styles, and important dates.
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December 5, 2020Proposal and Project Charter Submission
Check-in on the progress of the project between students and instructor.
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January 6, 2021Project Implementation and Weekly Status Meetings begin
The team will begin implementing their solution. Weekly meetings will begin where the team will update the client on the progress of the project.
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April 3, 2021Experience 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. 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, Data analytics, Data visualization, Big data, Sales & marketing
- 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 October, 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:
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.
Allow meetings (virtual or physical) and/or emails with the team as needed and mutually agreed to answer ongoing questions.
Provide the necessary data for analytics or identify the data sources for the team to acquire the data free of cost.
Minimum of 10 interactions with the students in-person or remotely (approximately 10 hours over the duration of the project).