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Data Analytics - Virtual Capstone

PROJ 006
Closed
SAIT
SAIT
Calgary, Alberta, Canada
Mostafa Mohamed
Mostafa Mohamed
Instructor
(7)
3
Timeline
  • January 25, 2022
    Experience start
  • February 13, 2022
    Experience end
Experience
4/8 project matches
Dates set by experience
Preferred companies
Canada
Any
Any industries
Categories
Data visualization Data analysis Data modelling
Skills
data analytics
Learner goals and capabilities

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. Based on the information you provide and the goals that you've shared with the students, they will provide you with an analysis and recommendations on issues of your choice.

In this training program, students are developing the knowledge, skills, and aptitude to apply fundamental principles of data analytics to support business decision-making processes.

Key Skills:

  • Cloud principles - managing data in the cloud through Microsoft Azure.
  • Database concepts - how to design and implement databases to maintain data integrity.
  • Querying data using SQL scripting.
  • Manipulate data - using ETL principles to develop a data repository that can then be analyzed.
  • Data Visualization - present data to communicate data analysis effectively and accurately.

Learners
Certificate
Any level
23 learners
Project
78 hours per learner
Learners self-assign
Teams of 6
Expected outcomes and deliverables

The final project deliverable will include:

  1. 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.
  2. A 20-minute presentation of the project and results to the industry partner and classmates.
Project timeline
  • January 25, 2022
    Experience start
  • February 13, 2022
    Experience end
Project Examples

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.

Work Expectation:

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

  1. Phase 1: from the project start till January 25, 2022, the students will be focusing on their coursework. At this phase, we expect the students to be learning about your project and preparing for it. Team introductions, initial project communications, and sharing of project materials/resources can begin during this phase and the teams will work on the project based on availability.
  2. Phase 2: from January 26 till February 11, 2022, the students will be working full time on your project. Most of the work will be done during this time period.

Important notes:

  • You should set clear project objectives.
  • The project to be valid must have existing datasets to work on. If there is no available data or not enough data for the target objectives, the project will not be considered valid.
  • Market research and data research/collection are not valid project objectives.
  • The main objective of this project is for the students to learn. They are not to be considered temporary or full-time employees. The best is to offer them a low-priority project to investigate a project idea or a new solution.
  • 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.
Companies must answer the following questions to submit a match request to this experience:

Be available for a virtual meeting or 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.

Have data sets ready and provide them to students to analyze.