In any role where you use data to tell stories or make decisions, issues of data equity are emerging as an essential consideration.
A more equitable approach to data involves asking questions such as: what assumptions or perspectives are built into the data? Who defined the categories and methodology, and why? What is and is not represented in the data, and why? How is equity defined in this context?
These answers can help us develop a better approach to our data work, but implementing new practices into projects and teams can be challenging.
You’ll leave this on-demand recorded session with a foundational understanding of data equity concepts, the latest frameworks available to promote equity in your data projects, and how actionable steps you can take to make your data practices more equitable.