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Data Analytics Capstone Project

PROJ 006
Closed
SAIT
SAIT
Calgary, Alberta, Canada
Mostafa Mohamed
Mostafa Mohamed
Instructor
(7)
3
Timeline
  • August 15, 2022
    Experience start
  • August 16, 2022
    Project Scope Meeting
  • August 25, 2022
    Check-in
  • September 3, 2022
    Final Report/Presentation
  • September 3, 2022
    Experience end
Experience
6/7 project matches
Dates set by experience
Preferred companies
Canada
Startup, Any, Small to medium enterprise
Any industries
Categories
Information technology Data visualization Data analysis Data modelling
Skills
business analytics business consulting data analytics storytelling and data visualization data analysis
Learner goals and capabilities

Is your organization looking to explore the value of data analytics? Students will work in teams applying critical thinking, skills and knowledge learned in their 12-week Data Analytics program to solve a problem or opportunity in your organization related to data.

Using a data set provided by your organization, students will use data analysis methods to help you and your organization derive insights and make more informed decisions.

Training Components:

  • Querying data using SQL scripting.
  • Data Visualization - present data to communicate data analysis effectively and accurately.
  • Python Programming Language - basic data science techniques using Python
  • MS Excel - using Power Pivot and Power Query
  • Database concepts - how to design and implement databases to maintain data integrity.
  • Cloud principles - managing data in the cloud through Microsoft Azure.
Learners
Certificate
Any level
23 learners
Project
80 hours per learner
Learners self-assign
Teams of 5
Expected outcomes and deliverables

Deliverables may vary depending on the scope of the project. It will be important to stick to the scope due to time limits and student abilities. The final project deliverable may include:

  1. A report outlining the work they performed, and analysis they conducted including visualizations and recommendations they may have as a result of the analysis. The students will provide a proof of concept of the solution.
  2. A 20-minute presentation of the project and results to the industry partner and classmates.
Project timeline
  • August 15, 2022
    Experience start
  • August 16, 2022
    Project Scope Meeting
  • August 25, 2022
    Check-in
  • September 3, 2022
    Final Report/Presentation
  • September 3, 2022
    Experience end
Project Examples

Students will develop the following skills and competencies and will develop the knowledge, skills, and aptitude to apply fundamental principles of data analytics to support business decision-making processes, creating accurate and meaningful storytelling with actionable insights.

Students may work with the company in the following ways:

  1. Assist organizations in preparing existing data for analysis. Students may perform data quality checks, data cleaning, and data transformation exercises on existing data to make the data ready for analysis by the organization.
  2. Assist organizations in data analysis. Using organizational data, students may conduct data analysis and design data analytics reports to be delivered to the firm.
  3. Create dashboards and reports to visualize the data and easy decision-making and insights.

Project examples include but are not limited to:

  • Analysis of customer segmentation relative to different products and services, to enhance marketing campaigns and refocus your products/services.
  • Investigate predictive models to understand trends in sales, attrition rates, and profits that impact your business.
  • Propose new ways to visualize data through tables and plots that can provide new insights for managers.

Project Timeline:

The project is expected to go into two phases as follows:

  1. Phase 1 (August 5 - 14): Students are focused on completing coursework in their full-time training program. Once a project is matched with a student project team, we expect that during this phase the initial project communications and sharing of project materials/resources can begin to ensure project objectives are agreed upon before starting Phase 2.
  2. Phase 2 (August 15 - September 2): Students have completed their coursework and will now be focused and working full time on your project.

Important notes:

  • Please set clear project objectives with your student project team. Given the short timeframes, the goal/objective of the proposed project should be relatively simple.
  • Your organization must offer a Non-disclosure agreement (NDA). The agreement should allow the students to show what they have done in the project and demonstrate samples of the work done. Confidential information can be removed.
  • An IP agreement should be provided by your organization and signed by the students and a representative from your organization.
  • If no IP or NDA is required for the project, please offer this in writing to the students to avoid future conflicts.
Linked templates
Artificial Intelligence & Machine Learning Application Analyzing Industry Data Financial Risk Analysis View all
Companies must answer the following questions to submit a match request to this experience:

Provide data sets for students to analyze and all necessary resources/access for the project.

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

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