Continuing Education

CCTB672 - Big Data Architecture

Course Code

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Campus

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Course Overview

Volume, variety, and velocity were the initial characteristics associated with big data. More recently, veracity and value have been added to provide a more comprehensive description of this term. Architecting a big data solution is a complex task since it refers to data that cannot be computed or analyzed using traditional processes, platforms, or tools. With the skills gained in this second in a series of courses in the Data Engineering program, you will be able to provide recommendations to address edge computing requirements and contribute to the design of a data lakehouse. Explore data architecture concepts and technical considerations and recommendations required by data engineers to design and implement big data solutions.

It is recommended that you complete CCTB671 and have experience with computer programming (preferably Python coding), data architecture, data modeling, and databases before enrolling in this course.

Upcoming Offerings

This course is part of these programs or course groups:

Business Intelligence & Data Engineering

Data Engineer Certificate


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Delivery Methods

  • Face to Face: Where: In-person meetings. When: Course is scheduled at a specific time for students to attend. Face-to-face instruction at all class meetings. Location may be on campus or at a worksite.
  • Blended: Where: Mixture of in-person & online components. When: Course is scheduled at a specific time for students to attend. Combination of face-to-face and online components at specific times. Some online components may be accessed online anytime.
  • Hyflex: Where: Choice to attend in-person or online meetings. When: Course is scheduled at a specific time for students to attend. For each class, students choose to attend in-person with the instructor or online at a specific time.
  • Remote Live Delivery: Where: Online with instructor. When: Course is scheduled at a specific time for students to attend. Instruction is delivered at set times online. Students do not come to campus.
  • Remote On-Demand Delivery: Where: Online anytime. When: No set class meetings. Coursework is accessed on-demand and online. While there are no set class meetings, there may be set due dates and deadlines for some activities. Students may interact with peers through virtual tools.
  • Remote Independent: Where: Online anytime. When: No set class meetings. Coursework is accessed on-demand and online, with no instructor support. While students choose when to do coursework, there may be set due dates and deadlines. 
  • Work Placement: Where: In-person meetings. When: Work is scheduled at a specific time for students to attend. Onsite work integrated learning. Location at a worksite.
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