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Collecting and analyzing data lies at the basis of the scientific method: findings about nature usher new ideas, and experimental results support or refute theories. All this is not very prevalent in computer science, possibly due to the fact that computer systems are man made, and not perceived as a natural phenomenon. But computer systems and their interactions with their users are actually complex enough to require objective observations and measurements. We'll survey several examples related to parallel and other systems, in which we attempt to further our understanding of architectural choices, system evaluation, and user behavior. In all the cases, the emphasis is not on heroic data collection efforts, but rather on afresh look at existing data, and uncovering surprising, interesting, and useful information. Using such empirical information is necessary in order to ensure that systems and evaluations are relevant to the real world.