Analytics Solution Consulting Projects - For Corporate Organizations

Contact principal
McGill University
Montreal, Quebec, Canada
Elle / Elle
Industry Liaison
(3)
6
Chronologie
  • septembre 20, 2024
    Début de expérience
  • mai 1, 2025
    Fin de expérience
Expérience
6 projets souhaités
Dates fixées par le expérience
Entreprises privilégiées
N'importe où
Large enterprise, Small to medium enterprise
N'importe qu'elle industrie

Portée de Expérience

Catégories
Technologie de l'information Analyse des données Étude de marché Opérations Gestion de projet
Compétences
competitive analysis business strategy marketing strategy data analysis research
Objectifs et capacités de apprenant.es

Masters of Analytics students, with the support of McGill University, are offering their analytic expertise to help professionals in various Corporate-based Organizations through our Practicuum course called “Analytics & Solution Consulting”.

A central component of this project is for organizations to leverage Masters students' skills in Advanced Analytics and Data Science to drive different utilizations of data and analytic techniques within your organizations so that you can have a greater on your company's goals. Our students can deliver new data and analytics-based solutions that could help you navigate and adapt to our new increasingly digital reality. Organizations that qualify include:

-Enterprise-sized organizations in any industry (preferred >500 employees)

You can have anywhere from 4-6 students for your project, and each student dedicates 200hrs towards a tangible Quantitative/Technological solution development. This is a $0-Fee engagement.

Apprenant.es

Apprenant.es
étudiant.e de cycle supérieur
Tout niveau
80 apprenant.es dans le programme
Projet
197 heures par apprenant.e
Les apprenant.es s'auto-attribuent
Projets individuels
Résultats et livrables attendus

Upon successful completion of this project a company will receive

Final Project Output

The final project output can include all of the following 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

Chronologie du projet
  • septembre 20, 2024
    Début de expérience
  • mai 1, 2025
    Fin de expérience

Exemples de projets

Exigances

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

Critères supplé mentaires pour entreprise

Les entreprises doivent répondre aux questions suivantes pour soumettre une demande de jumelage pour cette expérience:

  • Q1 - Case à cocher
  • Q2 - Case à cocher
  • Q3 - Case à cocher