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Traditional data science is too complicated for the average non-tech team member. Traditional ML is limited to large companies like Google and Apple that can afford a team of machine learning engineers. The process is in a technical coding language, such as Python or SQL. You have to guess which algorithm to assign to the data, which leaves room for wasted time or error. The user can’t visualize a data output and has to create their own charts and graphs to communicate their findings. No-code data science allows you to do just that and puts machine learning and insights from data out of the hands of an engineer.