What is the 80/20 rule when working on a big data project?

Could you please clarify the significance of the 80/20 rule when embarking on a large-scale data project? I'm intrigued to know how this principle, often referred to as the Pareto principle, can be applied in the context of managing and analyzing vast amounts of data. Specifically, how does it guide prioritization, resource allocation, or perhaps, even the selection of the most impactful data sets? I'm eager to learn how professionals in the field leverage this concept to streamline their processes and ensure the most effective use of their time and resources.