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To answer that question, I suggest we take a look at the evolution of machine learning.  Machine learning is a process of building models, applying models, and testing the model for accuracy and adjusting.  Although Alan Turing built machines that could execute the process before 1950, it has taken many years to become mainstream.

What probably gives a better indicator of the future of machine learning would be the growth of advanced analytics.  Businesses and sports organizations have been using advanced analytics for years.  This was a manual process and limited to scenarios where there was enough data to analyze.  Financial institutions and communications companies were early adopters due to the amount of data they had from calls and transactions.

The digital evolution has opened the doors for many businesses to leverage advanced analytics.  This explosion of data has also added a requirement to analyze images, voice & video in addition to the structured and semi-structured data used for years.  Unstructured data combined with the massive amounts of information generated by sensors and the internet has made machine learning a requirement.

We need machine learning today  for the same reason Turing needed a machine to try all of the combinations to break the code in 24 hours.  Data scientists can build perfect models, but by the time they build it the data will have changed.

The same digital evolution that is transforming businesses will mandate that machines conduct the analysis.   The only way the machine learning will go away is if we go back to the barter system.

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We've covered machine learning and advanced analytics topics extensively over the years. Read the rest of our blogs on the topic, and check out our SAP Analytics YouTube channel for videos on SAP solutions for machine learning, including more on SAP Predictive Analytics, SAP Analytics Cloud, and SAP Leonardo.