Analytics Capstone - Spring 2022

ANA1010
Fermé
Cambrian College
Sudbury, Ontario, Canada
Sidney Shapiro
Il / Lui
Assistant Professor, Business Analytics
2
Chronologie
  • mai 8, 2022
    Début de expérience
  • mai 31, 2022
    Partner check in and feedback
  • juin 26, 2022
    Fin de expérience
Expérience
34/37 match de projet
Dates fixées par le expérience
Entreprises privilégiées
N'importe où
Any
N'importe qu'elle industrie

Portée de Expérience

Catégories
Technologie de l'information Analyse des données Modélisation des données Étude de marché
Compétences
business analytics storytelling and data visualization data analysis research project planning
Objectifs et capacités de apprenant.es

This capstone project is part of the Business Analytics (BAPG), Health Analytics (HAGC), and Crime Analytics (CAGC) graduate certificate programs at Cambrian College. The students will participate in various projects involving different types of data, ranging from qualitative data gathering, quantitative data and analysis, technical projects, or other projects that align with their skillsets. This could include but is not limited to large and/or complex data, gathering data, conducting program evaluation, development and deployment of surveys, help with funding applications, create dashboards and analysis, and work with various types of data to support decisions using analytics in a wide array of industries.

Students can research, apply analytical models, methodologies, and tools learned in the program to analyze data. Faculty mentors will work with students to ensure the capstone project reflects, and encompasses, best practices for big data analytics and project management.

Apprenant.es

Apprenant.es
Finissant
Tout niveau
70 apprenant.es dans le programme
Projet
210 heures par apprenant.e
Les apprenant.es s'auto-attribuent
Équipes de 2
Résultats et livrables attendus

The final project deliverables will include:

  • A report on students’ findings and details of the analytics solution.
  • A final presentation of the solution and recommendations to your organization.
  • Future collaboration ideas will be identified based on current project outcomes.
Chronologie du projet
  • mai 8, 2022
    Début de expérience
  • mai 31, 2022
    Partner check in and feedback
  • juin 26, 2022
    Fin de expérience

Exemples de projets

Exigances

The capstone project provides an opportunity for organizations, businesses, partners, and learners to collaborate to identify and translate a real problems into an analytics problem. Students can research, apply analytical models, methodologies, and tools learned in the program to analyze data sets to predict trends and challenges, and investigate with the purpose of developing analytics solution for your organization. The project can include elements of data collection & preparation, data modelling and analysis with the potential to include predictive modelling, machine learning implementation, constructing dashboards or spreadsheets, programming, statistical analysis, and a solution deployment plan. Capstone project results/recommendations will be communicated in a report document and a final presentation.

You should submit a high-level proposal/business problem statement including relevant data sets and definitions, a list of acceptable tools (if applicable), and expected deliverables. Business datasets could be provided based on a non-disclosure agreement or in an anonymized/synthetic data format that is relevant to your organization and the project. The capstone course instructors will review the documents to confirm the scope and timing of the proposed problem and its alignment with the capstone course requirements.

Analytics solution may be applicable for (however they are not limited to) the following topics:

  1. Customer acquisition and retention
  2. Non profit program evaluation and funding
  3. Analyzing data
  4. Merchandising for trade areas (categories)
  5. Quantifying Customer Lifetime Value
  6. Determining media consumption (mass vs digital)
  7. Reduction of client churn (lower abandonment)
  8. Cross-sell and up-sell opportunities
  9. Develop high propensity target markets
  10. Customer segmentation (behavioural or transactional)
  11. New Product/Product line development
  12. Market Basket Analysis to understand which items are often purchased together
  13. Ranking markets by potential revenue
  14. Consumer personification
  15. Market research
  16. Development or integration of software or databases

Note: Students can sign a NDA, if required.

Critères supplé mentaires pour entreprise

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

  • Q - Case à cocher
  • Q - Case à cocher
  • Q - Case à cocher