Data professional: Any individual who works with data and/or has data skills
Data science: The discipline of making data useful
Data stewardship: The practices of an organization that ensure that data is accessible, usable, and safe
Edge computing: A way of distributing computational tasks over a bunch of nearby processors (i.e., computers) that is good for speed and resiliency and does not depend on a single source of computational power
Jupyter Notebook: An open-source web application used to create and share documents that contain live code, equations, visualizations, and narrative text
Machine learning: The use and development of algorithms and statistical models to teach computer systems to analyze patterns in data
Metrics: Methods and criteria used to evaluate data
Python: A general-purpose programming language