Sheridan Course Outlines

Land Acknowledgement

Sheridan College resides on land that has been, and still is, the traditional territory of several Indigenous nations, including the Anishinaabe, the Haudenosaunee Confederacy, the Wendat, and the Mississaugas of the Credit First Nation. We recognize this territory is covered by the Dish with One Spoon treaty and the Two Row Wampum treaty, which emphasize the importance of joint stewardship, peace, and respectful relationships.

As an institution of higher learning Sheridan embraces the critical role that education must play in facilitating real transformational change. We continue our collective efforts to recognize Canada's colonial history and to take steps to meaningful Truth and Reconciliation.

Section I: Administrative Information

Total hours: 42.0
Credit Value: 3.0
Credit Value Notes: TBD
Effective: Winter 2023
Prerequisites: INFO70279
Corequisites: N/A
Equivalents: N/A
Pre/Co/Equiv Notes: N/A

Program(s): Data Analyst
Program Coordinator(s): N/A
Course Leader or Contact: N/A
Version: 20230109_00
Status: Approved (APPR)

Section I Notes: Access to course materials and assignments will be available on Sheridan's Learning and Teaching Environment (SLATE). Students will need reliable access to a computer and the internet.

Section II: Course Details

Detailed Description
Students explore the steps in data analysis/transformation, data cleansing, and data modeling to build Business Intelligence (BI) dashboards in Power BI. Students use recommended Microsoft SQL Server Management Studio and Power BI tools, as well as the open source language R, to track and build business KPIs and manage data tasks. With the sample dataset, students will be able to develop their own Business Intelligence dashboard that could be used as a potential resource in a job interview.

Program Context

Data Analyst	Program Coordinator(s): N/A
This course is part of the Data Analyst Micro-Credential

Course Critical Performance and Learning Outcomes

	Critical Performance:
	By the end of this course, students will have the ability to clean, model, and analyze relational sample data using SQL and R language, visualized in Power BI dashboards, to create critical business KPIs and measures using DAX scripts.

Learning Outcomes:

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

Explain the function of different data processing systems such as OLTP, ROLAP, MOLAP and Hybrids.
Construct SQL queries for both basic and advanced levels of Merge/Append, Aggregations and Analytic queries.
Develop stored procedures using an SQL server.
Transform ("cleanse") raw data using SQL and R language.
Group and perform data normalizations.
Build a standard data model using the star and snowflake schemas.
Create BI dashboards and performance measures in Power BI using DAX scripts.

Evaluation Plan
Students demonstrate their learning in the following ways:

Evaluation Plan: ONLINE

	Quizzes (2 x 5 %)	10.0%
	Assignment 1	35.0%
	Assignment 2	35.0%
	Assignment 3	20.0%
	Total	100.0%

Evaluation Notes and Academic Missed Work Procedure:

TEST AND ASSIGNMENT PROTOCOL

The following protocol applies to every course offered by 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 Colleges and Universities requirements:

Essential Employability Skills
Essential Employability Skills emphasized in the course:

Communication Skills - Respond to written, spoken, or visual messages in a manner that ensures effective communication.
Critical Thinking & Problem Solving Skills - Use a variety of thinking skills to anticipate and solve problems.
Information Management Skills - Analyze, evaluate, and apply relevant information from a variety of sources.
Information Management - Locate, select, organize and document information using appropriate technology and information systems.
Personal Skills - Manage the use of time and other resources to complete projects.
Personal Skills - Take responsibility for one's own actions, decisions, and consequences.

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

Not Eligible for PLAR

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: N/A
Resource(s):

	Type	Description
Optional	Other	Recommended Reading: Definitive Guide to DAX, The: Business intelligence for Microsoft Power BI, SQL Server Analysis Services, and Excel 2nd edition ISBN: 9781509306978

Applicable student group(s): Students in the online class in the Continuing and Professional Studies.
Course Details:

Module 1: Introduction to Relational Databases

OLTP vs. OLAP and their variations
Relational engines and their frameworks

Module 2: SQL Scripting: Tables and Relational Databases

SQL Scripting to create tables
Populating and updating tables
Changing the structure of a table

Module 3: SQL Scripting: JOINS, Stored Procedures and Analytics

Types of Table JOINS and UNIONS
Building Stored Procedures
SQL Analytics – Rank, Row Number, Lead Lag, First Value and Last Value

(Quiz #1: 5%)

(Assignment #1: 35%)

Module 4 : Entity Relationship Diagram (ERD)

Normalization of Data
Building entity relationships using their keys constraints (PK/FK)
Introduction to star and snowflake schemas
Different Cardinalities and Dynamic Cardinalities

Module 5 : Business Intelligence Dashboard / Data Visualisation

Building a Dashboard using Power BI Desktop
Introduction to DAX (Data Analytic Xpressions)
Read data from a local server and from web transform

Module 6 : Building KPI’s and Measures

Building DAX scripts
Performance analysis of scripts
Most common functions in DAX

(Assignment #2: 35%)

Module 7: Data Cleansing using R

Types of data quality issues/checklists
Methods to handle data quality problems
Substitution and Imputation in R

(Assignment #3: 20%)

(Quiz # 2: 5%)

Sheridan Policies

It is recommended that students read the following policies in relation to course outlines:

Academic Integrity
Copyright
Intellectual Property
Respectful Behaviour
Accessible Learning

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

Appropriate use of generative Artificial Intelligence tools: In alignment with Sheridan's Academic Integrity Policy, students should consult with their professors and/or refer to evaluation instructions regarding the appropriate use, or prohibition, of generative Artificial Intelligence (AI) tools for coursework. Turnitin AI detection software may be used by faculty members to screen assignment submissions or exams for unauthorized use of artificial intelligence.

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. 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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