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For advanced analytics and true sensemaking, much of this might be true. You need a human to really deeply understand data and find what it really means. However, let's apply the pareto principle. 80% of the needs are served by 20% of the effort. I think for most (let's say 80%) of what most (about 80%) of companies really need, a computer can get at least most of the way there, with much less time and effort than a human. For example, sure, you need a human to really understand your web analytics. However, to understand it at a basic level, pull out clusters of interesting patterns, and discover anomalies and outliers that you wouldn't have gone looking for otherwise, the computer can get the average intelligent person (not an analyst) most of the way there, and certainly can provide a great deal of value for generally much less cost than a human analyst on salary. Plus, this frees analysts up for work that truly needs their expertise. As many data folks will tell you, it'd be great if everything they did was using their full skill set to the fullest; but often they spend half their day pulling reports that a computer truly could have done for the requester without any intervention, if designed correctly (not easy, mind). So, it's not about computers replacing humans entirely. It's about reducing waste, finding ways to cover common cases and repeated work easily, and freeing up human minds for what they're really good at and needed for. |