Unlock Business Insights Through Data-Driven Solutions

BANA 5000
Closed
University of Lethbridge
Lethbridge, Alberta, Canada
Sidney Shapiro
Sidney Shapiro He / Him
Assistant Professor, Business Analytics
2
Timeline
  • October 29, 2024
    Experience start
  • December 10, 2024
    Experience end
Experience
4 projects wanted
Dates set by experience
Preferred companies
Anywhere
Any company type
Any industries
Categories
Data analysis Competitive analysis
Skills
business analytics microsoft excel key performance indicators (kpis) process mapping
Learner goals and capabilities

The University of Lethbridge, Dhillon School of Business, is offering a unique opportunity for employers to collaborate with learners enrolled in the Business Analytics course. These learners are equipped with foundational knowledge in statistical and computing technologies, designed to analyze past business trends and develop future strategies. They are skilled in building models, process mapping, and defining key performance indicators (KPIs) that align with business goals. Employers who engage in this collaboration will provide mentorship and support, enabling learners to apply their academic knowledge to real-world business problems.

Learners
Graduate
Beginner, Intermediate levels
12 learners
Project
50 hours per learner
Learners self-assign
Teams of 4
Expected outcomes and deliverables

By participating in this experience, learners aim to enhance their abilities in data analysis, predictive modeling, and decision-making through hands-on business analytics projects.


Deliverables are subject to the employer's needs, but can include:

  • A comprehensive final report detailing key findings and recommendations based on the analysis conducted.
  • A virtual final presentation where learners will present their results and answer any questions.
Project timeline
  • October 29, 2024
    Experience start
  • December 10, 2024
    Experience end
Project Examples

An ideal project would involve tasks that allow learners to apply data-driven techniques to solve business challenges. The focus should be on leveraging historical data to predict future trends and optimize decision-making processes.

  1. Sales Forecasting: Analyze historical sales data to develop predictive models for future sales trends, incorporating seasonality and market factors.
  2. Customer Segmentation: Use customer data to identify distinct segments and recommend targeted marketing strategies to increase engagement.
  3. Supply Chain Optimization: Analyze data on supply chain performance to identify bottlenecks and propose solutions for reducing lead times and costs.
  4. Financial Performance Analysis: Examine financial data to identify trends and provide recommendations on improving profitability.
  5. Process Improvement: Analyze business processes and data flows to identify inefficiencies and suggest optimization strategies.
Companies must answer the following questions to submit a match request to this experience:

What is the primary business challenge you would like the students to address?

How frequently are you available to meet with the learners for progress updates?