Big Data Analytics

Program: BDAT
Credential: Ontario College Graduate Certificate
Delivery: Full-time + Part-time
Length: 2 Semesters
Duration: 1 Year
Effective: Fall 2024, Winter 2025, Summer 2025
Location: Barrie


Big Data allows users to visualize past, present, and future patterns by linking and presenting information in meaningful ways. Data Analytics offers deeper insight into the meaning of data sets by telling the story behind the information. This enables stakeholders to make more informed decisions, predict trends and better understand the needs and sentiments of customers. This program provides students with a unique blend of theoretical knowledge and applied skills. Students learn how to collect, curate, manipulate, encode, and store data sets so they can be analyzed and mined in such a way that they can be reused and repurposed to solve present challenges as well as those that do not yet exist.

Career Opportunities

Graduates of this program are able to collect, organize and correlate data for a wide range of industries including government, applied research, human resources, health care, and sales and marketing. Leveraging prior background, skills and experience, students may be employed in roles such as Data Analyst, Business Analyst, BI Developer, ETL Developer, Database Developer, NoSQL Developer, Data Visualization Developer, Business Intelligence (BI) Specialist, Analytics Specialist, BI Solutions Architect, or Business Analytic Specialist.

Program Learning Outcomes

The graduate has reliably demonstrated the ability to:

  1. collect, manipulate and mine data sets to meet an organizational need;
  2. recommend different systems architectures and data storage technologies to support data analytics;
  3. design data models that meet the needs of a specific business process;
  4. develop software applications to manipulate data sets, correlate information and produce reports;
  5. design and present data visualizations to communicate information to business stakeholders;
  6. apply business analytics and business intelligence tools to support evidence-based decision making;
  7. employ environmentally sustainable practices within the field of data analytics;
  8. apply basic entrepreneurial strategies to identify and respond to new opportunities.

Program Progression

The following reflects the planned progression for full-time offerings of the program.

Fall Intake

  • Sem 1: Fall 2024
  • Sem 2: Winter 2025

Winter Intake

  • Sem 1: Winter 2025
  • Sem 2: Summer 2025

Summer Intake

  • Sem 1: Summer 2025
  • Sem 2: Fall 2025

Admission Requirements

  • Ontario College Diploma, Ontario College Advanced Diploma, Degree, or equivalent. It is recommended that the applicant have a specialty in science, technology, engineering, mathematics, or business.

Additional Information

To be successful in this program, students are required to have a personal notebook computer (either PC or Mac architecture) prior to the start of the program that meets or exceeds the following hardware specifications:

  • Intel i7 processor or AMD equivalent 
  • Dedicated graphics card/processor 
  • 16GiB of memory (32GiB recommended) 
  • 500GB hard drive (SSD recommended)

Graduation Requirements

12 Program Courses

Graduation Eligibility

To graduate from this program, a student must attain a minimum of 60% or a letter grade of P (Pass) or S (Satisfactory) in each course in each semester. The passing weighted average for promotion through each semester and to graduate is 60%.

Program Tracking

The following reflects the planned course sequence for full-time offerings of the Fall intake of the program. Where more  than one intake is offered  contact the program co-ordinator for the program tracking.

Plan of Study Grid
Semester 1Hours
Program Courses  
BDAT 1002 Data System Architecture 42
BDAT 1003 Business Processes and Modelling 42
BDAT 1004 Data Analytics Programming 42
BDAT 1005 Mathematics for Data Analytics 42
BDAT 1006 Data Visualization 42
BDAT 1010 Business Intelligence 42
Semester 2
Program Courses  
BDAT 1007 Social Media Analytics and Data Mining 42
BDAT 1008 Cloud Based Data Engineering 42
BDAT 1009 Business Analytics 42
BDAT 1011 Data Analytics Project 42
BDAT 1015 Applied Machine Learning 42
BDAT 1016 NoSQL Databases 42
 Total Hours504

Graduation Window 

Students unable to adhere to the program duration of one year (as stated above) may take a maximum of two years to complete their credential. After this time, students must be re-admitted into the program, and follow the curriculum in place at the time of re-admission.

Disclaimer: The information in this document is correct at the time of publication. Academic content of programs and courses is revised on an ongoing basis to ensure relevance to changing educational objectives and employment market needs. 

Program outlines may be subject to change in response to emerging situations, in order to facilitate student achievement of the learning outcomes required for graduation. Components such as courses, progression, coop work terms, placements, internships and other requirements may be delivered differently than published.

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