Data mining for business analytics
General
- Undergraduate; 4th year, 3rd year
- 50 learners; teams of 4
- 40 hours per learner
- Dates set by experience
- Learners self-assign
Preferred companies
- 6 projects wanted
- Anywhere
- Academic experience
- Any
- Any industries
Categories
Skills
Project timeline
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January 14, 2020Experience start
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March 7, 2020Students present of a first draft of their project.
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April 11, 2020In-class presentation
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April 21, 2020Final report presentation
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April 21, 2020Experience end
Timeline
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January 14, 2020Experience start
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March 7, 2020Students present of a first draft of their project.
Based on the information that you provide, students will submit a comprehensive analysis roadmap to propose solutions and implementation strategies to address a managerial issue.
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April 11, 2020In-class presentation
Students will present the results of their analysis during an in-class presentation.
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April 21, 2020Final report presentation
Students will present their final report which will include the patterns identified in the data set, their analysis as well as actionable implementation strategies.
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April 21, 2020Experience end
Overview
- Details
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Student-consultants will analyze data sets using state-of-the-art technologies to identify trends, and submit recommendations based on predictive models that can enhance decision-making in your organization.
- Learner skills
- Python, Big data, Sas em, R, Data mining
- Deliverables
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Final deliverables will include:
- A slide deck with conclusions and recommendations for a 15-minute consulting presentation.
- A written report with details of the predictive models that were developed, including insights and overall recommendations that are inferred from such models.
- All applicable source code.
Project Examples
Data Mining for Business Analytics has become one of the most dynamically growing areas of business and knowledge discovery. Data Mining, an art-and-science of identifying useful patterns in data, has become an indispensable tool for companies operating in a highly competitive environment.
Beginning in late February, a class of student-consultants in groups of four will spend 60 hours per team performing a thorough investigation of data sets to tackle a managerial question. Tools such as SAS EM, and Python packages will be leveraged for data modeling, machine learning, and visualization.
Based on the information that you provide, groups will develop predictive models and managerial insights into key aspects of your organization. Each team will propose solutions and implementation strategies to improve your decision making processes and outcomes.
Example projects include, but are not limited to:
- Analysis of customer segmentation relative to different products and services, to enhance marketing campaigns and refocus your products/services.
- Investigate predictive models to understand trends in sales, attrition rates, and profits that impact your business.
- Propose new ways to visualize data through tables and plots that can provide new insights for managers.
- Reduce customer churn.
- Maximize revenue through up-sell and cross-sell.
- Determine sales trends.
- Accurately predict customer behaviours.
- Improve new customer acquisition.
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.
Be available for an introductory session at the beginning of the project (in person or virtual).
Be available for a quick phone call with the organizer to initiate your relationship and confirm your scope is an appropriate fit for the experience.
Minimum of 2-4 interactions with the students in-person or remotely (approximately 4-6 hours over the duration of the project).
Provide students with the data necessary to conduct their data mining analysis.