64th ISI World Statistics Congress - Ottawa, Canada

64th ISI World Statistics Congress - Ottawa, Canada

Avoiding imposter syndrome post data-revolution: A public servant’s guide to increasing data literacy

Conference

64th ISI World Statistics Congress - Ottawa, Canada

Format: IPS Abstract

Keywords: data-literacy

Abstract

In an age where data-driven decision making has become crucial, public servants are often faced with the challenge of being able to navigate complex and evolving data landscapes without formal training. This presentation explores Statistics Canada's Data Literacy Training Initiative (DLTI) - a transformative response to these issues aimed at increasing data literacy among Canadian government employees. The DLTI underlines the importance of accessible, plain language training products created to enhance one’s skills and abilities, and to interact confidently with data. Simultaneously, our mission is to disprove the common belief that data science is too technically advanced, complicated or intimidating to learn in an informal setting.
This presentation will demonstrate how the DLTI cultivates a more inclusive and empowering data environment, reducing feelings of imposter syndrome as data grows more integral to public service work. We will illustrate how the initiative's resources have helped instill a stronger understanding and command of data among public servants, thus aiding the post-data-revolution transition.
Through this discussion, we underscore the importance of increased data literacy, demonstrating how comprehensive yet straightforward training can make data accessible to all, ultimately empowering public servants to engage more effectively in their roles, enhance decision-making, and provide better public service.