Analytics and Big Data, Introduction to
Sheridan College Logo
  I: Administrative Information   II: Course Details   III: Topical Outline(s)  Printable Version
Section I: Administrative Information
  Total hours: 21.0
Credit Value: 1.5
Credit Value Notes: N/A
Effective: Fall 2018
Prerequisites: N/A
Corequisites: N/A
Equivalents: N/A

Pre/Co/Equiv Notes: N/A

Program(s): Business Analysis, Project Management - Other rel
Program Coordinator(s): Maria Amuchastegui
Course Leader or Contact: N/A
Status: Approved (APPR)

Section I Notes: This is a Sheridan College course that is offered through Sheridan FCAPS. Students who register for the course through Sheridan will receive credit from Sheridan College only. Access to the course materials will be through This course is offered in a classroom version and an online version. In the classroom version, classes are conducted on campus, students engage in classroom instruction. The online version is a web-based course offered entirely online through Sheridan. Students taking this course will need reliable access to the internet, and should have a basic level of comfort using computers as well as the self-discipline to study online.

Section II: Course Details

Detailed Description
Students learn to examine organizational goals and the value provided to a range of stakeholders by data analytics and big data systems and processes. They explore the concepts, and operating principles, techniques, and technology of the field. Students study how data analytics systems and skills, including planning, can inform business decision makers and meet their needs, and how predictive analytics, statistical analysis and modelling, visualization, business intelligence and decision support can play an important role in modern business success. Students also explore data management techniques including data cleansing and ETL (Extract, Transform, Load) systems.

Program Context

Business Analysis Program Coordinator(s): Maria Amuchastegui
This is an elective course in the Business Analysis Sheridan Certificate offered through the Faculty of Continuing and Professional Studies.

Project Management - Other rel Program Coordinator(s): N/A

Course Critical Performance and Learning Outcomes

  Critical Performance:
By the end of the course, students will have demonstrated the ability to describe the key steps, tasks, roles and components required to plan and implement analytics and big data projects
Learning Outcomes:

To achieve the critical performance, students will have demonstrated the ability to:

  1. Describe the key terminology and elements of analytics and big data systems
  2. Explain how analytics, visualization and predictive models can be used to achieve organizational goals
  3. Determine how to identify, collect and interact with data
  4. Analyze the goals and roles of various stakeholders in an analytics project
  5. Determine the key tasks and components required to plan and implement an analytics project

Evaluation Plan
Students demonstrate their learning in the following ways:

 Evaluation Plan: ONLINE
 Class Exercises (2x5%)10.0%
 Group assignments (1x15%)+(1x20%)35.0%
 Individual Assignment15.0%
 Quizzes (5%+15%+5%)25.0%
 Final Exam15.0%

Evaluation Notes and Academic Missed Work Procedure:

Evaluation Plan: IN-CLASS
 Class Exercises (2x5%)10.0%
 Group assignments (1x15%)+(1x20%)35.0%
 Individual Assignment15.0%
 Quizzes (5%+15%+5%)25.0%
 Final Exam15.0%

Evaluation Notes and Academic Missed Work Procedure:
3 week on-campus delivery evaluation plan is as follows: Discussion 2 x 5% Case Study 15% Group Assignment 25% Group Assignment: Analytics Ideation Project 15% Quizzes 3 x 5%, 1 x 10% Final Quiz 10% The following protocol applies to every course offered by the Faculty of Continuing and Professional Studies 1. Students are responsible for staying abreast of test dates and times, as well as due dates and any special instructions for submitting assignments and projects as supplied to the class by the instructor. 2. Students must write all tests at the specified date and time. Missed tests, in-class/online activities, assignments and presentations are awarded a mark of zero. The penalty for late submission of written assignments is a loss of 10% per day for up to five business days (excluding Sundays and statutory holidays), after which, a grade of zero is assigned. Business days include any day that the college is open for business, whether the student has scheduled classes that day or not. An extension or make-up opportunity may be approved by the instructor at his or her discretion.

Provincial Context
The course meets the following Ministry of Training, Colleges and Universities requirements:


Prior Learning Assessment and Recognition
PLAR Contact (if course is PLAR-eligible) - Office of the Registrar

Students may apply to receive credit by demonstrating achievement of the course learning outcomes through previous relevant work/life experience, service, self-study and training on the job. This course is eligible for challenge through the following method(s):

  • Challenge Exam
  • Other
    Notes:  This course is delivered through OntarioLearn at and is hosted by (Sheridan College) SH-MGMT70045.

Section III: Topical Outline
Some details of this outline may change as a result of circumstances such as weather cancellations, College and student activities, and class timetabling.
Instruction Mode: Online
Professor: Multiple Professors
OptionalOtherNo textbook required

Applicable student group(s): Students in the online class in the Faculty of Continuing and Professional Studies.
Course Details:
Module 1: Key terminology and elements of analytics and big data systems
  • Key terms applicable  to analytics and big data systems
  • Data and information attributes that require big data solution elements
  • Using analytics and big data elements to solve business needs
Assessment: In Class Exercise / Online Discussion - 5%
Module 2: Analytics, visualization and predictive models
  • The value of using analytics systems to achieve organizational goals.
  • Using visualization to transform data into information
  • Infographics
  • The steps for creating and using predictive analytics models
Assessment: In Class Exercise / Online Discussion 5%, Quiz 5%, Group Assignment 15%
Module 3: Identifying, collecting and interacting with data
  • What data is needed, where it is and how to access it
  • Relational data base basic terms
  • The three levels of database models that a Business Analyst may interact with
  • The organization and structure of data storage systems
  • Conducting a multi-dimentional analysis of data
  • Key processes and tools for managing big data and analytics projects (e.g., ETL -- Extract, Transform, Load systems)
  • SQL vs. NoSQL databases
  • Managing big data with the Hadoop echo-system 
Assessment: Quizzes 5%+10%=15%, Individual Assignment (Case study)15%
Module 4: Stakeholders in an analytics project
  • The roles of the various stakeholders in an analytics project
  • Using the information generated through an analytics project – who will use what and how
Module 5: Planning an analytics project 
  • The key planning steps for building an analytics system
  • Advantages of deploying analytics projects incrementally
  • The analytics project plan: key steps, tasks, roles and components 

Assessment Quiz: 5%

Assessment: Group Assignment 20%, Final Exam 15%

Sheridan Policies

All Sheridan policies can be viewed on the Sheridan policy website.

Academic Integrity: The principle of academic integrity requires that all work submitted for evaluation and course credit be the original, unassisted work of the student. Cheating or plagiarism including borrowing, copying, purchasing or collaborating on work, except for group projects arranged and approved by the professor, or otherwise submitting work that is not the student's own, violates this principle and will not be tolerated. Students who have any questions regarding whether or not specific circumstances involve a breach of academic integrity are advised to review the Academic Integrity Policy and procedure and/or discuss them with the professor.

Copyright: A majority of the course lectures and materials provided in class and posted in SLATE are protected by copyright. Use of these materials must comply with the Acceptable Use Policy, Use of Copyright Protected Work Policy and Student Code of Conduct. Students may use, copy and share these materials for learning and/or research purposes provided that the use complies with fair dealing or an exception in the Copyright Act. Permission from the rights holder would be necessary otherwise. Please note that it is prohibited to reproduce and/or post a work that is not your own on third-party commercial websites including but not limited to Course Hero or OneNote. It is also prohibited to reproduce and/or post a work that is not your own or your own work with the intent to assist others in cheating on third-party commercial websites including but not limited to Course Hero or OneNote.

Intellectual Property: Sheridan's Intellectual Property Policy generally applies such that students own their own work. Please be advised that students working with external research and/or industry collaborators may be asked to sign agreements that waive or modify their IP rights. Please refer to Sheridan's IP Policy and Procedure.

Respectful Behaviour: Sheridan is committed to provide a learning environment that supports academic achievement by respecting the dignity, self-esteem and fair treatment of every person engaged in the learning process. Behaviour which is inconsistent with this principle will not be tolerated. Details of Sheridan's policy on Harassment and Discrimination, Academic Integrity and other academic policies are available on the Sheridan policy website.

Accessible Learning: Accessible Learning coordinates academic accommodations for students with disabilities. For more information or to register, please see the Accessible Learning website (Statement added September 2016)

Course Outline Changes: The information contained in this Course Outline including but not limited to faculty and program information and course description is subject to change without notice. Any changes to course curriculum and/or assessment shall adhere to approved Sheridan protocol. Nothing in this Course Outline should be viewed as a representation, offer and/or warranty. Students are responsible for reading the Important Notice and Disclaimer which applies to Programs and Courses.

[ Printable Version ]

Copyright © Sheridan College. All rights reserved.