Big Data Analytics
Tell the story behind the information! This major growth area for applied research has been called the "sexiest job of the 21st century."
General information
Intake information
| Start date | Campus |
|---|---|
| Fall 2021 | Barrie |
| Winter 2022 | Barrie |
| Summer 2021 | Barrie |
Program description
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.
Why study Big Data at Georgian?
The right time
Be among the first graduates in this dynamic and growing field of research.
The right mix of skills
Learn the mix of technical, business and communications skills you need to succeed.
The right experiences
Get the most from your education with our applied learning model, providing you with experience in working with organizations to help them solve real challenges in the community.
The right connections
Benefit from the connections you'll make with employers and expert faculty from the research analyst, computer studies and business faculties.
The right place
Join the only college graduate certificate program in Big Data. Enjoy a collegial atmosphere, caring faculty and a nice campus setting in a small city with a reasonable cost of living and great quality of life.
Part-time delivery option
We also offer a part-time delivery format for this program:
- Complete the program in two years
- Schedule includes two courses per semester, available in the evening
- Register on a course-by-course basis
- Apply if you have previous postsecondary education— such as a degree or diploma — from an accredited university or college
Visit the Big Data Analytics part-time program page for details and contact information.
NOTE: Use the major BDAX when applying to the part-time program through ontariocolleges.ca.
Hardware and software requirements
- Windows 10
- 16 Gb RAM
- 1 Tb hard drive
- Budget of $800
- If you are planning to use a Mac, you will want to Bootcamp the Mac and install Windows 10
- All other software will be installed in class
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, Data Visualization Developer, Business Intelligence (BI) Specialist, Analytics Specialist, BI Solutions Architect or Business Analytic Specialist.
Admission information
Admission requirements
- Post-secondary diploma, degree or equivalent. It is recommended that the applicant have a specialty in science, technology, engineering, mathematics, or business.
Admission details
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)
Courses
Program-specific Courses
- BDAT 1000 - Data Manipulation Techniques (Semester 1 / 42 hours)
- BDAT 1001 - Information Encoding Standards (Semester 1 / 42 hours)
- BDAT 1002 - Data Systems Architecture (Semester 1 / 42 hours)
- BDAT 1003 - Business Processes and Modelling (Semester 1 / 42 hours)
- BDAT 1004 - Data Programming (Semester 1 / 42 hours)
- BDAT 1005 - Mathematics for Data Analytics (Semester 1 / 42 hours)
- BDAT 1006 - Data Visualization (Semester 2 / 42 hours)
- BDAT 1007 - Social Data and Mining Techniques (Semester 2 / 42 hours)
- BDAT 1008 - Data Collection and Curation (Semester 2 / 42 hours)
- BDAT 1009 - Enterprise Analytics (Semester 2 / 42 hours)
- BDAT 1010 - Business Intelligence (Semester 2 / 42 hours)
- BDAT 1011 - Data Analytics Project (Semester 2 / 42 hours)
