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    Considering how stubborn established companies are with their business operations, introducing Machine Learning which will bring a difference in business environments and in how people work, is extremely difficult. Data Science, AI and Machine Learning are different concepts where Machine Learning helps the other two prosper. It is a means of programming an algorithm wherein businesses feed in examples of real data. According to Maxim Scherbak, the author of this article, the new task for ML-driven organizations is preparing data for Machine Learning models. This implies that it will make Business Analysts different rather than making them redundant. For successful implementation of Machine Learning algorithms (which are mostly viewed as black boxes) they need to be backed by thorough testing. Leaving rule based approaches behind, businesses need to learn to trust these algorithms to shine in the era of AI. 

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