From the course: A Day In The Life of a Data Scientist

Knowing when to use which tools

From the course: A Day In The Life of a Data Scientist

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Knowing when to use which tools

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- We have a lot of tools now to be able to analyze data automatically for us, or think of a calculator, you don't need to now how to do multiplication on your own anymore, because the calculator can do it for you. But as a data scientist or a data analyst, and someone who works with data all the time, what's more important than maybe knowing every statistical formula, because you can Google it and you can use a calculator to do a formula for you, it's more important to know when you should use what tool. So, if you think about statistics, for example, there's a whole different arms of statistics. There's different areas, different computations that you can run, different models that you can apply. The most important thing, and I think something that's really... There's a need for, even within the data science industry right now, is people who understand what they want to pull from the data, and what tool they can use to do that. Because the tool will do all the computations for you, but you need to know how to apply it. You need to know how to make the technology work for what you want it to do. You need to be technical and be able to do the code and everything, but you also just need to be able to understand that if I put this number into this formula, this is what it means. This is what it means when I apply this model to this data set, and how can I communicate that to other people? So if you have a test, it's like having the answer key. The only thing you need to figure out is what questions do you want to ask? But you have all the data right there. You've got all the answers in front of you. And what I really love about data science and data analytics is that, the numbers don't lie. The numbers tell you the answers. And if you can just figure out questions, there are so many things that you can get new perspectives on, get new insights to. You just have to figure out how to use the data to work for you.

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