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Data Analytics Capstone Project

PROJ 006
Closed
EDGE UP
EDGE UP
Calgary, Alberta, Canada
Mostafa Mohamed
Mostafa Mohamed
Instructor
(7)
3
General
  • Certificate
  • 18 learners; teams of 5
  • 80 hours per learner
  • Dates set by experience
  • Learners self-assign
Preferred companies
  • 5/6 project matches
  • Alberta, Canada
  • Academic experience
  • Any
  • Any
Categories
General Information technology Databases Data visualization Data analysis Environmental sustainability
Skills
business analytics business consulting data analytics storytelling and data visualization data analysis
Project timeline
  • April 16, 2023
    Experience start
  • April 18, 2023
    Project Scope Meeting
  • April 27, 2023
    Check-in
  • May 6, 2023
    Experience end
Overview
Details

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 17-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.

Skill set:

  • Manipulate data using modelling, ETL in a business context relevant to decision-making.
  • Contextualize data in a format that maps to business objectives and aligns data analysis to strategic outcomes.
  • Present data that communicates analysis effectively and accurately for a business audience using visualizations (dashboards) and reports.
  • Python programming specific to data aggregation, preparation, visualization and analysis.
  • Managing data in the cloud (Microsoft Azure).
  • Understand the intersection of emerging clean technologies and data analytics.
Learner skills
Business analytics, Business consulting, Data analytics, Storytelling and data visualization, Data analysis
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.

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If you're interested in working with students beyond their capstone projects, we invite you to look into the work-integrated learning placement opportunity:

ICTC’s WIL Digital program helps companies grow and expand their impact by providing employers with the EDGE UP 2.0 program, wage subsidy, onboarding support, and a meaningful WIL experience for both employers and students.

The wage subsidy is at 50% of the participant’s salary up to $5,000, or 70% up to $7,000 for underrepresented students, for a three-month work term. ICTC provides one-on-one support to make the application process as simplified as possible for employers providing work integrated learning for local talent.

Employers, please indicate your interest in WIL Digital by writing to ICTC: edgeup@ictc-ctic.ca

EDGE UP (Energy to Digital Growth Education and Upskilling Project) is a multi-stakeholder program launched in Calgary in 2019 to test new approaches to skills development for workers to re-engage with technology jobs being created in all sectors of Calgary’s economy. The program targets professionals displaced from the structural change in the oil and gas sector.

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 (before April 14, 2023): 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 (April 17 - May5, 2023): 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
Financial Risk Analysis Artificial Intelligence & Machine Learning Application Analyzing Industry Data View all
Additional company criteria

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.

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

Be available for an online call with the capstone instructor to initiate your relationship and to confirm that your scope and timelines are an appropriate fit for the course.