Data Literacy

Course Description

In this 80-hour practice-based course trainees learn about data, data file formats, and relational and non-relational databases. Emphasis is placed on Relational Database Management Systems (RDBMSs), which are used in virtually all industries and organizations to store data about employees, products, services, inventory, financial transactions, etc. Trainees also learn the fundamentals of data mining, statistical methods, data analysis, and data visualization. They also learn about data governance, quality, and controls. Upon completing this course, trainees understand how data is acquired, stored, manipulated, analysed, and used to make better business decisions.


The prerequisite for this training program is Computational Literacy. To be successful in this course, trainees should be comfortable with basic math and algebra operations, number systems, and data functions such as average and sum.

Learning Outcomes

Trainees will be able to:

  • Use units of data size to determine data storage requirements.
  • Explain the basic principles of relational (SQL) and non-relational (No-SQL) databases.
  • Name the most widely used SQL and No-SQL databases.
  • Compare the most common flavors of SQL databases.
  • Define referential integrity, ACID, and cascade operations.
  • Explain the role of columns and rows in tables.
  • Formulate basic SQL queries using the SELECT statement.
  • Filter the results of queries.
  • Limit the number of results.
  • Use built-in functions to aggregate data.
  • Explain fundamental concepts of data mining.
  • Use basic statistical methods.
  • Distinguish between various data visualization methods.
  • Use Python to visualize data.
  • Perform data analytics with Python
  • Explain basic principles of data governance.
  • Control the quality of data.

Equipment Requirements

Computer, laptop or tablet with Internet access, web browser, and email.

Course Structure and Length

The course is self-paced, and trainees practice each skill or concept as they go.  Automatic feedback is built into the course for both practices and quizzes.

The course is divided into four Units, and each Unit is composed of five Sections.  Each Section consists of 7 instructional/practice levels, a quiz, and a master (proficiency) level.  Trainees can return to any level or quiz for review.

This table illustrates the course structure as units, sections, and levels.

Trainees will need approximately 80 hours to complete the course. Since the course is self-paced, the amount of time required to complete the course will vary from trainee to trainee. Trainees are responsible for learning both the tutorial content and the skills acquired through practice.