Data Analytics with Business Intelligence

Overview

Business Intelligence (BI) entails the integration of data, technology, business processes, and analytics to enhance business decisions and drive success. In today’s landscape, BI has emerged as a technological imperative for organizations, with its tools, approaches, and methods increasingly recognized as valuable skillsets. Transforming data into actionable insights is no longer optional but essential to navigate our dynamic markets.

The Data Analytics with Business Intelligence program focuses on the four key pillars of the BI Body of Knowledge: people, process, technology, and data. Through four core courses, students gain foundational knowledge and exposure to the essential technologies and processes underpinning BI projects. Students will learn to navigate every stage of a project, from gathering requirements to developing solutions and leveraging data across organization.

672 Hours / 36 Weeks

Certificate

In-class, Distance, Combined

Learning Objectives / Outcomes

Upon successful completion of this program, the student will have reliably demonstrated the ability to:

  • Recognize and grasp the advantages of employing business intelligence and data analytics tools.
  • Assess and select data sources suitable for business intelligence and data analytics initiatives.
  • Strategize, develop, and construct solutions for business intelligence and data analytics projects using various datasets.
  • Showcase proficiency in business intelligence and data analytics by tackling actual business challenges with real-world datasets from diverse sectors like IT, finance, healthcare, public service, social welfare, retail, and beyond.
  • Employ fundamental programming abilities to manage data and streamline workflows.
  • Play a role in facilitating, communicating, and advocating for data-driven decisionmaking throughout an organization.

Career Occupation

*Based on the NOC (National Occupation Classification) Version 2016 1.3
Unit Group 2172 – Database analysts and data administrators

Career options* available but not limited to:

  • Individuals responsible for data analytics tasks
  • Junior/Intermediate Data Analyst
  • Junior Data Scientist
  • Retail Manager
  • Business Analyst
  • Advertising/Marketing/PR Manager

Admission Requirements

To be eligible for admission, applicants must meet the following criteria:

1. Basic Admission Requirements

  • High School Completion: Applicants must have a high school diploma or an equivalent qualification.
  • Age Requirement: Minimum 19 years of age
  • Mature Student Status*: Applicants who have not completed high school and are at least 19 years of age, may apply as a mature student.

*Mature student status may be granted to applicants who are over 19 years old and have not completed high school or equivalent. The applicants will be considered for admission based on the skills and experience they have acquired since leaving school. The applicant is required to provide the most recent transcripts or proof of academic accomplishments, a resume or summary of professional accomplishments, and two professional letters of recommendation. The applicant may be interviewed by the Registrar’s or Academic office to further assess their suitability for admission to the program of study.

2. English Language Proficiency

Applicants must meet one of the following:

  • Minimum scores from accepted English tests (e.g., IELTS 5.5, TOEFL iBT 46, Duolingo 95, etc.).
  • Recent English proficiency test (within 2 years).
  • Proof of English-language education:
    • 2–3 years of secondary or post-secondary education completed in English in eligible countries.

Please see the Admission Requirements Guide for more information

Minimum Technology Requirements

  • Domain and Hosting
  • Student Edition Adobe Creative Suite
  • Personal Notebook Computer or MacBook, with following specifications:
  • Processor Chip: Intel Core i7 or i9
  • Speed: 3.9 GHz or higher
  • Example: Intel Core i7-7820HQ, 4-core 3.9 GHz
  • RAM: 8 GB or higher (Note: Windows 10 requires 4 GB minimum)
  • Graphics Card: NVIDIA GeForce GTX 1080 with 4 GB of dedicated RAM
  • (recommended: NVIDIA GeForce GTX 1080 Ti)
  • Graphics card must have dedicated RAM separate from the computer’s main RAM

Fee Details

Tuition CAD 13,500
Application Fee CAD 150
Administration Fee CAD 1,000
Textbooks CAD 1,400
Course Materials CAD 150
Other Fee CAD 100
Course Retake CAD 850 per course
Copy of Transcript CAD 20 per copy

Curriculum

Basic Courses
Introduction to Data Science 48 hours
Data Preprocessing and Cleaning 48 hours
Data Analytics with Excel 48 hours
SAS for Beginners 48 hours
Tableau 48 hours
Microsoft Power BI 48 hours
Intermediate Courses
Machine Learning Fundamentals 48 hours
Exploratory Data Analysis 48 hours
Deployment and Ethics in Data Science 48 hours
Informatica and Datastage 48 hours
Advanced Courses
Advanced Machine Learning 48 hours
Big Data and Distributed Computing 48 hours
Natural Language Processing 48 hours
Time Series Analysis and Forecasting 48 hours
Total 672 hours

Intakes – Bi-Weekly

9 Mar 2026 | 30 Mar 2026 | 13 Apr 2026 | 27 Apr 2026 | 11 May 2026 | 25 May 2026 | 8 Jun 2026 | 22 Jun 2026 | 6 Jul 2026 | 27 Jul 2026 | 10 Aug 2026 | 24 Aug 2026 | 7 Sep 2026 | 21 Sep 2026 | 5 Oct 2026 | 19 Oct 2026 | 2 Nov 2026 | 16 Nov 2026 | 30 Nov 2026 | 14 Dec 2026 | 11 Jan 2027 | 25 Jan 2027 | 8 Feb 2027 | 22 Feb 2027 | 8 Mar 2027 | 29 Mar 2027 | 12 Apr 2027 | 26 Apr 2027 | 10 May 2027 | 24 May 2027 | 7 Jun 2027 | 21 Jun 2027 | 5 Jul 2027 | 26 Jul 2027 | 9 Aug 2027 | 23 Aug 2027 | 6 Sep 2027 | 20 Sep 2027 | 4 Oct 2027 | 18 Oct 2027 | 1 Nov 2027 | 15 Nov 2027 | 29 Nov 2027 | 13 Dec 2027

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