Data Analytics Capstone Project
General
- Certificate
- 46 learners; teams of 6
- 30 hours per learner
- Dates set by experience
- Learners self-assign
Preferred companies
- 10/10 project matches
- Canada
- Academic experience
- Any
- Any
Categories
Skills
Project timeline
-
November 1, 2021Experience start
-
October 19, 2021Data Understanding/Data Preparation
-
November 10, 2021Project Scope Meeting
-
November 24, 2021Check-in
-
December 11, 2021Managing Data in the Cloud
-
December 11, 2021Check-in
-
December 25, 2021Experience end
Timeline
-
November 1, 2021Experience start
-
October 19, 2021Data Understanding/Data Preparation
Students should generate documentation on data understanding for the data assets available, provided, or to be gathered. Documentation should also be provided on the data preparation steps utilized to prepare the data for further analysis.
-
November 10, 2021Project Scope Meeting
Meeting between project teams and company to confirm: project scope, communication styles, and important dates.
-
November 24, 2021Check-in
Present the preliminary work completed thus far, which may include research, findings and recommendations.
-
December 11, 2021Managing Data in the Cloud
Students will demonstrate ways to manage data in the cloud using MS Azure as a platform, and provide recommendations on cloud solutions.
-
December 11, 2021Check-in
Present the preliminary work completed thus far, which may include research, findings and recommendations.
-
December 23, 2021Final Report/Presentation
Final deliverables, materials, and generated reports should be ready for presentation and submission.
-
December 25, 2021Experience end
Overview
- Details
-
Are you a firm looking to explore the value of data analytics? Students in the SAIT Data Analytics certificate are trained in data extraction and transformation as well as data preparation, data modeling and reporting on pre-existing data gathered by the organization. These students will work with your organization to analyze your data sets and provide any recommendations they may have as a result of the analysis.
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.
This program is funded by the Level UP program (powered by Riipen). Students are paid a $1400 CAD stipend on completion of the project by Riipen. Employers are not responsible for payment. You can learn more here.
- Learner skills
- Business analytics, Business consulting, Data analytics, Storytelling and data visualization, Data analysis
- Deliverables
-
The final project deliverable will include:
- A report outlining the work they performed, 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.
- A 20-minute presentation of the project and results to the industry partner and classmates.
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 is an innovative Work Integrated Learning program that helps small and medium-sized employers grow their businesses by providing the wage subsidy for hiring EDGE UP 2.0 participants. The wage subsidy is at 75% of salary up to a maximum of $7500. The employer must provide a meaningful work integrated learning opportunity for EDGE UP 2.0 participants. The placement takes place between Jan- Mar 2022.
Employers, please indicate your interest in WIL Digital by writing to ICTC: edgeup@ictc-ctic.ca
Project Examples
Beginning in October, students in groups of 4-5 will spend around 100 hours assisting your company by providing analytical research and recommendations tailored to one of your company’s data opportunities or challenges.
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. They will accomplish this using a foundation of data management and ethics. The students are developing skills in the Microsoft stack and IBM SPSS, and will be expected to use these technologies for the project.
Program Outcomes
- Understand database concepts and how to design and implement databases to maintain data integrity.
- Develop skills to query data using SQL scripting.
- Manipulate data using ETL principles (extract, transform, load) to develop a data repository that can then be analyzed in a business context that is relevant to decision-making.
- Apply fundamental data analytics principles, aligning data and business processes to create accurate, actionable insights.
- Use industry-recognized programs and tools to extract meaning from data (SPSS, Power BI).
- Present data that communicate data analysis effectively and accurately for a business audience using visualizations (dashboards) and reports.
- Develop skills in Python programming, specific to data analysis functions.
- Introduce cloud principles for managing data in the cloud, using Microsoft Azure as the platform.
Students may work with the company in one of three ways
- Assist organizations in data gathering research and/or prepare data for future use by the organization. Students can help design and model databases to gather and store data for future analysis.
- Assist organizations in preparing existing data for analysis. Students may perform data quality checks, data cleaning, and data transformation exercises on existing data to ready data for analysis by the organization.
- Assist organizations in data analysis. Using organizational data, students may conduct data analysis and design data analytics reports to be delivered to the firm.
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.
Participating industry partners provide data sets.
Additional company criteria
Companies must answer the following questions to submit a match request to this experience:
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.
Provide data sets for students to analyze