Demystifying machine learning

Date of publication: November 11, 2018

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Abstract:

Research departments are under pressure. They are expected to deliver faster, cheaper and more impactful insights than ever before. Instead of doing more and faster research, insight departments are also able to revisit existing data sources. Often, companies have plenty of valuable data sources at their disposable, without being aware of their full potential. Moreover, relevant databases are often publicly available via APIs or sold via data brokers. Yet, the biggest hurdle lies in making sense of this abundance of data. Companies are struggling to connect different sources due to different structures, missing values and other complexities. In the last years enormous advancements have been made in machine learning and data science. Although demystifying is needed in order to better understand this discipline in context. With a creative and pragmatic mind-set, the problem can be solved by borrowing techniques from this field of data science. We show a case – in the beverage industry – where we exploited existing data sources to uncover a hidden layer of insights.

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