From the course: Twelve Myths about Data Science

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Data quality is not as important as quantity

Data quality is not as important as quantity

From the course: Twelve Myths about Data Science

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Data quality is not as important as quantity

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- Now I'd like to dive into a pretty common belief floating around in the data universe, the idea that the more data you have, the better off you are. People often think that a mountain of data beats a hill of high-quality information any day of the week. But let's be real, is that actually true? Today, we're going to bust this myth wide open and see really what's up when it comes to the quantity versus quality debate in data. You've probably heard it a million times, data is the new oil. And, yes, I think it's fair to say that data is the most valuable asset of nearly every company out there. But, like oil, it needs to be refined before it can become useful. The truth is data isn't just about quantity. The real magic happens when the data you're working with is both extensive and high quality. Think about it, what good is a heap of data if it's riddled with errors, outdated, or just plain irrelevant information? That's where the saying garbage in garbage outcomes from. Let's say that…

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