Big Data Programming and Architecture Capstone - Winter 2025

DAT 305
Ouvert Clôture le janvier 18, 2025
McMaster University Continuing Education
Hamilton, Ontario, Canada
Instructor
(14)
6
Chronologie
  • janvier 22, 2025
    Début de expérience
  • avril 10, 2025
    Fin de expérience
Expérience
6 projets souhaités
Dates fixées par le expérience
Entreprises privilégiées
N'importe où
Tout type de entreprise
N'importe qu'elle industrie
Catégories
Analyse des données Stratégie de vente Marketing strategy
Compétences
business and analytical problem framing model development deployment and documentation business analytics storytelling and data visualization data analysis, data science concepts, text analytics
Objectifs et capacités de apprenant.es

This course covers advanced-level topics in the areas of data science, machine learning, and technical/software applications. Students in the program are adult learners with a post-secondary degree/diploma in computer science, engineering, business, etc. They will practice their knowledge of using various technologies as part of the course, such as real-time analytics tools (e.g., Kafka and HBase), NoSQL databases, and cloud technologies.


Students will apply analytical models, methodologies, and tools learned in the program to create an analytics solution for your organization, with support from faculty mentors, who will work with students.

Apprenant.es
Certificat
Niveau Débutant, Intermédiaire
20 apprenant.es dans le programme
Projet
60 heures par apprenant.e
Les apprenant.es s'auto-attribuent
Équipes de 4
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
  • janvier 22, 2025
    Début de expérience
  • avril 10, 2025
    Fin de expérience
Exemples de projets

The capstone project provides an opportunity for businesses and learners to collaborate to identify and translate a real business problem into an analytics problem. The project also includes data collection & preparation, data modeling, and analysis with the potential to incorporate predictive modeling, machine learning implementation, a solution deployment plan and the results of the deployment. The 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 business problem. 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. Demand for social services (healthcare, emergency services, infrastructure, etc.)
  2. Customer acquisition and retention
  3. Merchandising for trade areas (categories)
  4. Quantifying Customer Lifetime Value
  5. Determining media consumption (mass vs. digital)
  6. Reduction of client churn (lower abandonment)
  7. Cross-sell and upsell opportunities
  8. Develop high propensity target markets
  9. Customer segmentation (behavioral or transactional)
  10. New Product/Product line development
  11. Market Basket Analysis to understand which items are often purchased together
  12. Ranking markets by potential revenue
  13. Consumer personification


Data need not be ‘clean’; it is advantageous to the students’ learning experience to require cleansing and profiling of the data prior to analysis. This supports the learning experience and minimizes partner data preparation.

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

Provide a dedicated contact who is available to answer periodic emails or phone calls over the duration of the project to address students' questions.

Be available for a quick phone call with the instructor to initiate your relationship and confirm your scope is an appropriate fit for the course.