From the course: Big Data in the Age of AI
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Big data as proxy data
From the course: Big Data in the Age of AI
Big data as proxy data
- [Instructor] Now, this may seem a little odd in the context of a course on big data where we're trying to find ways to benefit from the enormous quantities of data that are now available, but I'm actually a huge fan of taking the three Rs that we know so well from the physical world, reduce, reuse and recycle, and applying them in the data world too. Now, there's a couple of reasons for that. Number one is, there are costs to gathering data. Whether you're doing a survey with pencil and paper, whether you're doing in-person interviews or online, please-give-us-your-feedback things, it takes time, it takes money, and really you're drawing on the time that your respondents have, that's a limited resource, and their goodwill, another limited resource. And so there are always costs to gathering data. Second, there are costs of preparing data. There's the common truism that in a data science project, 80% of your time is spent preparing the data for analysis, and the remaining 20 is spent…
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