Introduction to Analytics and Big Data
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  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: Spring/Summer 2014
Prerequisites: N/A
Corequisites: N/A
Pre/Co/Equiv Notes: N/A

Program(s): Business Analysis
Program Coordinator(s): Jonathan Nituch
Course Leader or Contact: Multiple Course Leaders
Status: Approved (APPR)

Section I Notes: 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 examine the organizational goals and value provided by analytics and big data systems and processes. They learn the terminology and operating principles of these powerful technologies, as well as the planning aspects to implement them. Studies include: analytics as it applies to various business needs, predictive analytics and the role of statistical analysis and modelling, visualization, the concepts of business intelligence and decision support. Students also examine aspects of data management to facilitate analytics: data cleansing, the concepts of ETL (Extract, Transform, Load) systems, the role of big data technologies and the new dimensions of data management and insight they provide. Students review the goals and roles of the stakeholders involved in analytics projects as well as key planning aspects for these projects.

Program Context

Business Analysis Program Coordinator: Jonathan Nituch
This is an elective course in the Business Analysis Sheridan Certificate offered through the Faculty of Continuing and Professional Studies.

Course Critical Performance and Learning Outcomes

 Critical Performance 

By the end of the course, students will have demonstrated the ability
to discuss the goals, value(s), terminology and planning aspects of
analytics and big data projects.  

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

 1. Recognise the data and information attributes requiring big data
    solution elements. 
 2. Describe the purpose and value of using analytics systems to 
    achieve organizational goals.
 3. Define the various terms currently applicable to the problem and 
    solution areas addressed by analytics and big data technology.
 4. Analyze the goals and roles of the various stakeholders in an 
    analytics project. 
 5. Determine the key tasks and components required for an analytics 

Evaluation Plan
Students demonstrate their learning in the following ways:

In-Class and Online Evaluation Plan

*Class Exercises (2 x 5%)                      10% 
Group Assignments ([1x15%)+(1x20%)]            35%
Individual Assignments                         15%
Quizzes	                                       25%
**Final Exam	                               15%
Total                                          100%


1) *Class Exercises are made up of online discussions for online 
    students and in-class exercises for students taking this course on
    campus in a classroom.
2)  **The Final exam in the Online Course will be administered and
    completed online.

3)  Unless otherwise specified in writing by the instructor, 
    assignments must be completed as individual efforts. Assignments
    will allow students to propose solutions and recommendations to 
    practical project related issues.

4)  For all Group  Assignments as well as Individual Assignments (In 
    Class and Online), the instructor will specify in writing:

  a)  due dates and special instructions for submissions for both In 
      Class and Online.
  b)  deductions for overdue submissions.

5)  Quizzes will consist of True/False, Multiple Choice and Short 
    Answer questions for both In Class and Online courses.

6)  Quizzes will be administered and completed online for both In
    Class and Online courses.

7)  Exams will consist of True/False, Multiple Choice and Short 
    Answer questions for both In Class and Online courses.
Provincial Context
The course meets the following Ministry of Advanced Education and Skills Development requirements:


Essential Employability Skills
Essential Employability Skills emphasized in the course:

  Communication   Critical Thinking & Problem Solving   Interpersonal
  Numeracy   Information Management   Personal

Notes: N/A

Prior Learning Assessment and Recognition
PLAR Contact: Registrar’s Office

Students may apply to receive credit by demonstrating achievement of the course learning outcomes through previous life and work experiences. This course is eligible for challenge through the following method(s):

Challenge Exam Portfolio Interview Other Not Eligible for PLAR

Notes: N/A

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.
Effective term: Spring/Summer 2014
Professor: Multiple Professors
No textbook required

Applicable student group(s): Students in the online class in the Faculty of Continuing and Professional Studies.
Course Details:
Orientation Module   	
 - Welcome and Introductions

Module 1: Analytics: What Is It?  	
 - Top Buzzwords in "Dataland" 
Learning Outcomes covered: 1,2,3,4
Learning activities and Assessments: In Class Exercise / Online
Discussion 5%

Module 2: Applied Analytics and Its Multiple Uses.  	
 - What value do analytics bring to organizations?
 - Business Intelligence, visualization and KPIs
 - Statistical models & predictive analytics
Learning Outcomes covered: 1,2,3,4  
Learning activities and Assessments: In Class Exercise / Online
Discussion 5%, Quizzes 5%, Group Assignment 15%

Module 3: Dealing with Data	
 - What data is needed?
 - What is available?
 - What form is the data?
 - Does it need cleaning?
 - What components are needed?
Learning Outcomes covered: 1,3,4,5
Learning activities and Assessments: Quizzes 15%, Individual
Assignment 15%

Module 4: Pulling It All Together	
 - Understanding the key roles of stakeholders and technologies
 - What are the appropriate project stages?
 - Organizational analytics maturity
Learning Outcomes covered: 2,4,5
Learning activities and Assessments: Quiz 5%, 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)

Couse 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.

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