Big Data Analytics
Credential: Ontario College Graduate Certificate
Delivery: Full-time + Part-time
Length: 2 Semesters
Duration: 1 Year
Effective: Fall 2021, Winter 2022, Summer 2022
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 challenges that don’t yet exist.
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, 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:
- collect, manipulate and mine data sets to meet an organizational need;
- recommend different systems architectures and data storage technologies to support data analytics;
- design data models that meet the needs of a specific business process;
- develop software applications to manipulate data sets, correlate information and produce reports;
- design and present data visualizations to communicate information to business stakeholders;
- apply business analytics and business intelligence tools to support evidence-based decision making;
- employ environmentally sustainable practices within the field of data analytics;
- apply basic entrepreneurial strategies to identify and respond to new opportunities.
The following reflects the planned progression for full-time offerings of the program.
- Sem 1: Fall 2021
- Sem 2: Winter 2022
- Sem 1: Winter 2022
- Sem 2: Summer 2022
- Sem 1: Summer 2022
- Sem 2: Fall 2022
- Post-secondary diploma, degree or equivalent. It is recommended that the applicant have a specialty in science, technology, engineering, mathematics, or business.
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 i5 processor or AMD equivalent
- 8GB of memory (16 GB recommended)
- 250GB hard drive (SSD recommended)
12 Program Courses
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%.
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.
|BDAT 1000||Data Manipulation Techniques||42|
|BDAT 1001||Information Encoding Standards||42|
|BDAT 1002||Data Systems Architecture||42|
|BDAT 1003||Business Processes and Modelling||42|
|BDAT 1004||Data Programming||42|
|BDAT 1005||Mathematics for Data Analytics||42|
|BDAT 1006||Data Visualization||42|
|BDAT 1007||Social Data and Mining Techniques||42|
|BDAT 1008||Data Collection and Curation||42|
|BDAT 1009||Enterprise Analytics||42|
|BDAT 1010||Business Intelligence||42|
|BDAT 1011||Data Analytics Project||42|
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.