Data literacy training
Course Description
What is data literacy?
Data literacy is the ability to derive meaningful information from data. It focuses on the competencies involved in working with data including the knowledge and skills to read, analyze, interpret, visualize and communicate data as well as understand the use of data in decision-making.
Data literacy also means having the knowledge and skills to be a good data steward including the ability to assess the quality of data, protect and secure data, and their responsible and ethical use.
Learning Outcomes
The data literacy learning catalogue is organized by the steps on the data journey from data collection to storytelling. The journey addresses the following data competencies:
Data analysis | Data awareness | Data cleaning | Data discovery | Data ethics | Data exploration | Data gathering | Data interpretation | Data management and organization | Data modeling | Data stewardship | Data tools | Data visualization | Evaluating data quality | Evaluating decisions based on data | Evidence based decision-making | Metadata creation and use | Storytelling
Course Content
-
Module 1: The Data Journey: Foundational concepts
These introductory videos provide foundational concepts about Data, includingThe Data Journey: What you need to know for successful navigation
-
Module 2: Define – Find – Gather
The first step is to get data, whether this is using a pre-established database or establishing what variables are needed and creating and implementing a collection method.
-
Module 3: Explore – Clean – Describe
Data should be explored to understand the format and variables and also checked for errors and missing values. It may be necessary to clean the data before using it for analysis which includes doing such things like correcting formatting, removing or correcting erroneous data, or something as simple as taking out extra space. It important to document what you found and what you did to clean the data.
-
Module 4: Analyze – Model
The purpose of doing analysis and modeling is to use statistical techniques to turn the data into information to provide meaningful insights. Analysis and modelling is used to describe a phenomenon, draw conclusions about a population or make predictions about future events.
-
Module 5: Tell the story
The statistical information that comes from analysis and modeling is easier to digest if it is presented in some sort of story. It could be a research paper, an infographic, an article for the media, or some combination of these and other data presentation methods.
-
Module 6: Foundation: Stewardship – Metadata – Standards – Quality
In order to successfully follow the steps of the data journey, it is essential to build your work on a solid foundation of stewardship, metadata, standards and quality.
Pre-requisites
- Ability to work with spreadsheets and basic understanding of graphs and charts
Course Provider
- This course is provided by Statistics Canada (https://www.statcan.gc.ca/en/wtc/data-literacy) and curated through eCISTAR.
Target audiences
- This training is aimed at those who are new to data or those who have some experience with data but may need a refresher or want to expand their knowledge.
FAQs
Related Courses
