Having a Big Bang is one of the most common causes of data science project failures. And you probably have done it, at least a couple of times. In this episode, we will show you why it is often better to aim for sub-optimal solutions at the start of a project, and how you can avoid the Big Bang problem by following an ancient Japanese philosophy.
By the way, we are rebroadcasting this episode because it is one of our favourite early episodes. And the content can be very valuable to our new listeners.
Meanwhile, if you are not a data scientist yet, but want to become one, you should really attend our webinar. We will demystify the transition into data science. We will show you the most effective way to build your skills. And we will advise you on the four possible options you can take to go from where you are to landing a data science job in as little as 9 months.
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