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Home » Course Catalogue » MBA Electives » RSM2401H – Data and Information Management for Business Analytics

RSM2401H – Data and Information Management for Business Analytics

General Information


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Target Audience

This course is for those that want to gain the foundational skills of working with data. 80% of business analysis efforts are spent on finding, extracting, cleaning, and visualizing data prior to performing the actual data analysis. Whether or not you are considering a career in data sciences, this course introduces the essential skills for working with data that can apply to careers in; information technology, business, finance, marketing analysis, or data sciences. This is a hands on course focused on developing practical skills across a broad range of the most common data management and analysis concepts, such as relational database design and its implementation with SQL and Python, programming fundamentals, data manipulation and data cleaning and preparation, and data analysis and visualization techniques using Python.


Intensive format – 2 weekly classes over 6 weeks

Course Mission

  1. Apply the principles of Database Management System Design concepts from analysis to full implementation
  2. Create Structured Query Language (SQL) queries appropriate for data extraction and summarization tasks
  3. Demonstrate the ability to prepare, explore and validate data for business analysis
  4. Apply advanced data analysis techniques towards the development of decision-making tools
  5. Develop Business Intelligence Dashboards to support business decision-making

Course Scope

This course focuses on the fundamentals of data management for the purposes of producing information and supporting advanced techniques of business analytics. This applied learning course will expose the learner to a broad range of technical skills that are required to access, prepare and visualize data for advanced analysis. The course introduces the fundamental skills that form the foundation in the development of advanced business analytics. These include:

  1. Database Management Fundamentals
  • Understanding how data is stored and retrieved in both relational and non-relational data systems

2. Data Preparation for Analysis

  • Defining a business objective and determining the data requirements to support it
  • Performing assessments of data to determine suitability for use and identify data quality issues and apply mitigating strategies
  • Applying data manipulation and transformation techniques to support analysis

3. Data Analysis and Visualization

  • Performing exploratory data analysis to delve into the data, examine and discover important interrelationships between attributes, and identify interesting subsets or patterns
  • Developing data visualization solutions that support: exploratory analysis, insight generation, and decision making

Using a combination of theory and practical exercises and case studies, the learner will develop the data acquisition, preparation, and preliminary analysis skills that are a necessary pre-requisite to applying advanced business analytics to their data.

Evaluation and Grade Distribution

Weekly Self-Study and Practice Activities9%
Assignment 1 (Database Design/Implementation and Programming Fundamentals)14%
Assignment 2 (Data Cleaning/Preparation and Manipulation)17%
Assignment 3 (Analysis and Visualization)10%
Final Exam (during exam period)50%

Required Resources

  • SQL
  • Python (It is recommended that students complete a 4-week Python module in preparation for the course).

Last Updated: 2022-11-29 @ 5:15 pm