Continuing Education

CCTB675 - Big Data Insights

Course Code

A unique identifier used at NAIT for this specific course.

Campus

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Course Overview

Data insights provide organizations with knowledge gained from analyzing sets of information. The value of these insights increases when they are presented to the right stakeholder in the right format at the right time. Big data insights imply working with data sets that require new platforms and technologies given the large volumes of data that need to be extracted rapidly, in real or near-real time, from heterogeneous source systems in a variety of formats. Data engineers play a key role in this process by ensuring data readiness. With the skills gained in this fifth course in the Data Engineering program, you will be able to describe the close relationship between data engineering and advanced analytics practices that use machine learning, artificial intelligence, and cognitive computing to support decision making.

It is recommended that you complete CCTB674 and have experience with computer programming (preferably Python coding), data architecture, data modeling, and databases before enrolling in this course.

Upcoming Offerings

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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