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Analytics Solution Development - For Social Organizations

BUSA649
Closed
McGill University
McGill University
Montreal, Quebec, Canada
Shoeb Hosain
Shoeb Hosain
Professor/Director - McGill Masters of Analytics
(2)
3
Timeline
  • May 16, 2022
    Experience start
  • June 15, 2022
    Project Scope Finalization
  • August 2, 2022
    Experience end
Experience
18/35 project matches
Dates set by experience
Preferred companies
Anywhere
Startup, Social enterprise, Non profit, Small to medium enterprise, Incubator
Any industries
Categories
Information technology Market research Operations Project management
Skills
modeling competitive analysis business strategy marketing strategy data analysis
Learner goals and capabilities

McGill University Masters of Analytics students are offering zero-fee analytic expertise to help professionals in various Community-based Organizations through a new initiative called “MMA Gives” to leverage Masters students' skills in Data Science to drive different utilizations of data and analytic techniques within your organizations, so that you can have a greater an impact on Society. Our students can deliver new data and analytics-based solutions that could help you navigate and adapt to our new reality. Organizations that qualify include:

-NGOs/ Learning or Research institutions/ Startups/ SMEs (<100 employees)/ Groups severely impacted by pandemic.

You can get up to 4 students assigned.

Overview and skills: please visit the interactive presentation

Examples of past work: please click on a Featured Project from the list.

Register for an Online Info Session to meet with us and learn more.

Learners
Post-graduate
Any level
80 learners
Project
100 hours per learner
Learners self-assign
Individual projects
Expected outcomes and deliverables

Upon successful completion of this project a company will receive

Final Project Output

The final project output can include one or multiple components:

  • Project Statement of Work
  • Technical data pipeline code and/or architecture (ie SQL/Python)
  • Quantitative model code (ie Python/R) or cloud based API builds (ie Google/Microsoft/Amazon clouds)
  • Dashboard files (ie PowerBI/Tableau) Business outcomes based on the analytic findings
  • Recommended next steps

Your business will have a much better understanding of the variables that are summarized and interpreted. The descriptive statistical summary will provide your business with the knowledge to optimize the various strategies you run at your organization

Project timeline
  • May 16, 2022
    Experience start
  • June 15, 2022
    Project Scope Finalization
  • August 2, 2022
    Experience end
Project Examples

For full portfolio and use case examples please click here.

Summary:

Students can work on 1 or multiple areas of the following:

1.Technical Data Management - Data Pipeline Development

Develop a more automated what to procure and/or manage your data structures to support any analytics/modeling work done. Examples include:

  • MySQL DB creation
  • ETL integration architecture development

2A.Analytics Strategy - Define and Collect the Data Attributes of Interest

Data strategy is a critical piece to enabling firms to implement more Data Driven Decisions. Our students can help you define this strategy from scratch or advance one you already have to take it to the next level. Examples include:

  • Social Media data extraction development
  • Public information analysis like Open.gov

2B.Analytics Modeling - Statistical Analysis/ Predictive

Depending on your Use Case, student work to test/apply a wide variety of methodologies to solve your business problem. Examples include:

  • Historical Descriptive KPI determination
  • Future Predictive modeling/forecasting
  • Efficiency Optimization

Students can employ a mix of supervised and unsupervised Machine-Learning techniques to give your firm an edge

3.Design Visualization - Dashboarding

Finally, in order to consume the analytic results efficiently within your organization, students can develop dashboarding. This ties the business objectives with the quantitative outcomes to help clients make better decisions. Examples include:

  • Smart Heat-Map Dashboards
  • User based views and data access control

Companies must answer the following questions to submit a match request to this experience:

Feedback on progress and final solution. Total Time to client approx 1hr/week

Be available for a quick meeting with the project administrator to initiate your relationship and confirm your scope is an appropriate fit for the course + Provide dedicated project liaison to provide support to students

Provide project scope, a mix of internal data and tips for external data sources.

If you accept our project it is imperative to connect with monika.brozyna@mcgill.ca to coordinate project onboarding.