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Big Data Programming & Architecture

Uncover the Hidden Value of Big Data

Bridging theory and practical experience

DAT 202 - Data Management C01 Winter 2022

Academic Credit Value:
3 units
Course Delivery Mode:
Virtual Classroom
Hours of Study:
36 hours
Course Prerequisite(s):
Introductory statistics course, or DAT 101 Statistics for Data Analysis, or DAT 200 Statistical Analysis for Data Science
Course Anti-requisite(s):
No Anti-requisite(s)
Instructor Name:
Course Dates:
01/19/2022 - 04/06/2022

Required Course Materials:
Required readings and materials will be posted on the Avenue to Learn course site.
Optional Course Materials:
Supplemental readings and materials will be posted on the Avenue to Learn course site.
Course Description:

Students are advised to retain course outlines for future use in support of applications for employment or transfer of credits.

Refer to the Policy & Procedure section for further course and McMaster Continuing Education information. 

Data analytics problems require new tools/technologies to store and manage the data to realize the business benefit. This course explores the importance of managing data as an enterprise asset and the data management components required in terms of the acquisition, storage, sharing, validation and accessibility of data for addressing business problems. An examination of Database Management Systems, database architectures, the differences between OLTP (Online transaction processing) OLAP (online analytical processing), and the administrative processes that guide the data lifecycle will be a focus of the course.
Learning Outcomes:
Upon completion of this course, students will:
1. Identify the value of data in relation to information and knowledge; define the concepts of data, information and knowledge
2. Outline the approaches in preparing data for analysis when the data is sourced from multiple diverse environments
3. Explain the importance of metadata in understanding information and approaches to metadata management.
4. Examine the importance of data quality and data profiling in data analysis, understand the various approaches for improving data quality
5. Work with a number of industry tools used in performing data analysis (eg. Power BI, Data Profiling, Metadata Managers, Hadoop (Big Data Platform), etc.)
6. Define Data Governance and its importance to managing the data and information assets of the business.
7. Understand the analytical process to break down complex data problems into smaller steps for effective management and analysis
8. Explain the operational considerations in architecting   BI and Analytic Platforms and the factors to be considered in preparing big data for analysis and the need for various repositories for managing the data (e.g. warehouses, sandboxes, Hadoop)
9. Recognize data security and privacy concerns and their importance when performing data analytics
10. Demonstrate the approaches to documenting findings (e.g. insights, results, business performance) and presentation of the findings to the stakeholders 
Course Evaluation

The final grade is calculated based on the following components:

Online Discussion Participation


Topic Facilitation


2 Lab Assignments (Working with Sales Data-Technical Work)


Midterm Workshop


Final 3 Case Study Questions


Course Format:
This course is designed to present the fundamental concepts and theories in data management and data analytics to promote the application to the workplace and professional practice. Course activities will include instructor presentations, required readings, and experiential learning activities (ie. case studies, group discussions, projects, etc.)
Assignment Submission:
In-class and/or A2L assignment folder(s). Consult with Instructor.
Late Coursework:
Late assignments will be subject to a 2% per day late penalty (includes weekends and holidays) for up to seven (7) days. After this date, no assignments will be accepted and a grade of zero (0) will be applied.  Extensions for course work must be approved by the instructor before the due date (see Academic Regulations below), and will be granted for illness or emergencies only. Students may be asked to submit supporting documentation for an extension request. NOTE:  This policy applies to assignments and other hand in type coursework only.  This policy does not apply to discussion board topics/postings which do not allow for late postings/contributions.

Policy & Procedures:

Academic Regulations (Attendance, Coursework, Tests/Exams):
In accordance to McMaster University’s General Academic Regulations, “it is imperative that students make every effort to meet the originally scheduled course requirements and it is a student’s responsibility to write examinations as scheduled.” Therefore, all students are expected to attend and complete the specific course requirements (i.e. attendance, assignments, and tests/exams) listed in the course outline on or by the date specified. Students who need to arrange for coursework accommodation, as a result of medical, personal or family reasons, must contact the course instructor within 48 hours of the originally scheduled due date. It is the student’s responsibility to contact the Program Manager to discuss accommodations and procedures related to deferred tests and/or examinations within 48 hours of the originally scheduled test/exam, as per policy. Failure to contact the course instructor, in the case of missed coursework, or the Program Manager, in the case of a missed test/examination, within the specified 48-hour window will result in a grade of zero (0) on the coursework/exam and no further consideration will be granted.

*Note: Supporting documentation will be required but will not ensure approval of accommodation(s).
Academic Integrity
You are expected to exhibit honesty and use ethical behaviour in all aspects of the learning process. Academic credentials you earn are rooted in principles of honesty and academic integrity. Academic dishonesty is to knowingly act or fail to act in a way that results or could result in unearned academic credit or advantage. This behaviour can result in serious consequences, e.g. the grade of zero on an assignment, loss of credit with a notation on the transcript (notation reads: “Grade of F assigned for academic dishonesty”), and/or suspension or expulsion from the university.

It is your responsibility to understand what constitutes academic dishonesty. For information on the various types of academic dishonesty please refer to the Academic Integrity Policy, located at

The following illustrates only three forms of academic dishonesty:
  1. Plagiarism, e.g. the submission of work that is not one’s own or for which other credit has been obtained.
  2. Improper collaboration in-group work.
  3. Copying or using unauthorized aids in tests and examinations.
Academic Accommodations:


Students with disabilities who require academic accommodation must contact Student Accessibility Services(SAS) at 905-525-9140 ext. 28652 or  to make arrangements with a Program Coordinator. For further information, consult McMaster University’s Academic Accommodation of Students with Disabilities policy.

 Academic Accommodation for Religious, Indigenous or Spiritual Observances (RISO)
Students requiring academic accommodation based on religious, indigenous or spiritual observances should follow the procedures set out in the RISO policy. Students will need to contact their instructors as soon as possible to make alternative arrangements for classes, assignments, and other coursework. It is thestudent’s responsibility to contact McMaster Continuing Education to discuss accommodations related toexaminations.
On-line Elements:

Conduct Expectations:

As a McMaster student, you have the right to experience, and the responsibility to demonstrate, respectful and dignified interactions within all of our living, learning and working communities. These expectations are described in the Code of Student Rights & Responsibilities (the “Code”). All students share the responsibility of maintaining a positive environment for the academic and personal growth of all McMaster community members, whether in-person or online.

It is essential that students be mindful of their interactions online, as the Code remains in effect in virtual learning environments. The Code applies to any interactions that adversely affect, disrupt, or interfere with reasonable participation in University activities. Student disruptions or behaviours that interfere with university functions on online platforms (e.g. use of Avenue 2 Learn, WebEx or Zoom for delivery), will be taken very seriously and will be investigated. Outcomes may include restriction or removal of the involved students’ access to these platforms.

 Copyright and Recording:

Students are advised that lectures, demonstrations, performances, and any other course material provided by an instructor include copyright protected works. The Copyright Act and copyright law protect every original literary, dramatic, musical and artistic work, including lectures by University instructors.

The recording of lectures, tutorials, or other methods of instruction may occur during a course. Recording may be done by either the instructor for the purpose of authorized distribution, or by a student for the purpose of personal study. Students who wish to record sessions need to acquire permission from the instructor. Students should be aware that their voice and/or image may be recorded by others during the class. Please speak with the instructor if this is a concern for you.
In this course, we may be using a web-based service ( to reveal plagiarism. Students will be expected to submit their work electronically to and in hard copy so that it can be checked for academic dishonesty. Students who do not wish to submit their work to must still submit a copy to the instructor. No penalty will be assigned to a student who does not submit work to All submitted work is subject to normal verification that standards of academic integrity have been upheld (e.g., on-line search, etc.). To see the Policy, please go to McMaster Academic Integrity Policy.
Course Changes:

The instructor reserves the right to modify elements of the course and will notify students accordingly.

Extreme Circumstances:

The University reserves the right to change the dates and deadlines for any or all courses in extreme circumstances (e.g., severe weather, labour disruptions, etc.). Changes will be communicated through regular McMaster communication channels, such as McMaster Daily News, A2L and/or McMaster email.

Course Withdrawal Policy:
Policies related to dropping a course and course withdrawals are posted to the Centre for Continuing Education’s program webpage, FAQs & Policies (
Storm Closure Policy:

In the event of inclement weather, the Centre for Continuing Education will abide by the University’s Storm Closure Policy:, and will only close if the University is closed. All in-class courses, exams and room bookings by internal and external clients will be cancelled if the Centre for Continuing Education is closed. On-line courses will take place as scheduled.

Grading Scale:
 Grade Equivalent
Grade Point
Equivalent Percentages
A+ 12 90-100
A 11 85-89
A- 10 80-84
B+ 9 77-79
B 8 73-76
B- 7 70-72
C+ 6 67-69
C 5 63-66
C- 4 60-62
D+ 3 57-59
D 2 53-56
D- 1 50-52
F 0 0-49
Course Schedule:


Lesson/Module Title

Activity & Due Date


Data as an Enterprise Asset

Class exercise-Discussion of the importance of data in today’s business environment 

Introduce Case Study


Introduction to Meta Data

Lab: Preparing business and technical metadata

Tool: Metadata Manager / Excel

Due: In Class


Data Life Cycle & Data Quality

Lab: Importance of data preparation. Case Study on data profiling and data cleansing

Tool: Ataccama DQ / Power BI

Due: In Class


Data Governance

Lab: Application of Data Visualization tools.

Tool: SQL Server / PowerBI

Due: In Class


Data Security and Privacy

Lab: Implementing data masking to protect data

Tools : SQL Server

Due : In Class


Approach to Addressing Data Analytical Problem

Workshop Group Activity - preparing an analytical plan.

Due: In class


Data Operations

Class exercise / discussion - Operational considerations in performing data analytics.

First part of the class will be a short quiz.


Database Architecture /

Data Modeling

Class Exercise - applying Visualization tools.

Tool: Tableau / PowerBI

Due: In class


Database Systems / Hadoop / Databricks

Lab: Case Study using Hadoop, Databricks

Tools: Hadoop / MapReduce / HDFS/ PIG


Group Activity

Workshop Group Activity - applying concepts/tools presented to date to address a business issue

Due: In class


Present Research Papers

Class presentations/review of Research Papers


Course Wrap-up

Overview of course, lessons learned & tool wrap-up.