Small Big Data @ PyData NYC 2019

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Data science requires writing software, which means your team is going to be slowed down by bugs, slow code, mysterious errors, and other programming issues.

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You use software to analyze data—it's a means, not an end. But you still need to deal with all the problems software development entails: from bugs to slow code to mysterious errors.

You want to trust the software you write, and to ship it on schedule.

So you need improve you software engineering skills, from testing to packaging to performance. And to help you do that I'm writing new articles every week—subscribe to my newsletter to get them in your inbox: