Data Analytics for Business | St. Clair College

Program Overview

The Data Analytics for Business program prepares students to visualize past, present, and future patterns by linking and presenting information in meaningful ways. The area of data analytics offers deeper insight and meaning of data sets for users by telling the story behind the information. This type of detailed and defined information enables graduates to effectively predict trends, understand the needs of customers, as well as make more informed business decisions.

Students will learn a unique blend of theoretical knowledge and advanced applicable skills. Students will also learn large scale data manipulation, how to collect, curate, encode, and store data sets, which can be analyzed and mined in ways that can be reused and repurposed to solve challenges and predict future patterns for business decision making. Students will gain critical thinking skills that demonstrate the ability to use existing and discoverable data to solve business problems.

Career Opportunities

Graduates may find employment in various information technology companies throughout both the public and private sectors. Positions within these sectors include data administrators, database administrators (DBA), database analysts, database architects, data custodians, data warehouse analysts, technical database architect, or in other capacities dealing with big data within the information technology field. Those with an entrepreneurial spirit may prefer self-employment opportunities within the field such as database development or design of data management solutions.

Admission Requirements

Diploma or degree in a relevant field from a recognized college or university or demonstrated competence through related work.

International Students: See Admission Policies for details.

Laptop Requirements

MINIMUM RECOMMENDED HARDWARE

  • Intel I7 or AMD A10 processor or better with chipset that must support virtualization
  • 16 GB of RAM
  • 1 TB hard drive
  • Ethernet Network Card
  • Wireless Network Card
  • One USB 3.0 port (two preferred)
  • 3 Yr comprehensive parts and labour (Recommended)

SOFTWARE REQUIREMENTS

  • Windows 10 Professional Edition

 

Courses

The curriculum below is for incoming students:

Semester 1
Code Title Credits
DAB100
Introduction To Data Analytics
3
DAB501
Basic Statistics And Exploratory Data Analysis
5
DAB101
Introduction To Artificial Intelligence
2
DAB102
Information Management
3
DAB103
Analytic Tools And Decision Making
5
Semester 2
Code Title Credits
DAB200
Machine Learning 1
5
DAB201
Data Visualization And Reporting
4
DAB502
Advanced Statistics For Data Analytics
5
DAB202
IT Service Management
3
DAB203
Business Analytics And Decision Making
4
Semester 3
Code Title Credits
DAB300
Machine Learning 2
5
DAB301
Project Management Analytics
4
DAB302
Ethics For Analytics
2
DAB303
Marketing Analytics
5
DAB304
Healthcare Analytics
5
Semester 4
Code Title Credits
DAB400
Supply Chain Analytics
5
DAB401
Financial Analytics
5
DAB402
Capstone Project
1

Your Investment

The standard tuition and compulsory fees for the current academic year:

2019-2020 Tuition Fees

For programs with Experiential Learning (Work Placement/Internship): Costs for accommodation, if needed, travel and related expenses is at the student's own expense. It is recommended for most programs, that students have access to a laptop or desktop computer while away from home during experiential learning periods.

Textbooks and other materials are in addition to Tuition Fees. Textbook prices may be found through the Bookstore website.

Please be aware that tuition and compulsory fees are subject to adjustment each year. The College reserves the right to change, amend or alter fees as necessary without notice or prejudice.

Program Vocational Learning Outcomes

Data Analytics for Business (Ontario College Graduate Certificate) (70717)


The graduate has reliably demonstrated the ability to:

  1. Analyze, organize, and manipulate data to support problem solving, business decision-making, and opportunity identification.  
  2. Develop statistical and predictive models that use operational and marketing data to identify patterns and provide insights to business stakeholders.
  3. Assess and apply business intelligence and Big Data tools appropriate to the business decisions, business problems, data movement, and system workloads.
  4. Prepare and communicate complex materials verbally, in writing, and digitally for a variety of audiences, purposes, and levels of detail.
  5. Analyze and interpret data as it relates to various aspects of a business organization’s readiness to change.
  6. Conduct data analysis and research in a respectful and ethical manner that protects privacy and maintains dignity to all involved.
  7. Deliver data-oriented projects using data science, business analysis, and project management principles, tools, and techniques to ensure clients’ business needs are achieved.