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    Graham Immerman
    Graham Immerman Industry 4.0 / April 18, 2018

    Good data vs bad data

    Having lots of data is great - but having quality, actionable data is better.

    The Harvard Business Review said, "Machine learning has incredible power and you need to learn to tap that power. Poor data quality can cause that power to be delayed, denied, or misused, fully justifying every ounce of the effort."

    You can use machine learning for data quality. By giving you real time insight into your machines, MachineMetrics can help you act on data quickly without losing valuable time. As their title says, "If your data is bad, your machine learning tools are useless."

    Recommended ReadIf Your Data Is Bad, Your Machine Learning Tools Are UselessSource: http://hbr.org

      Poor data quality is enemy number one to the widespread, profitable use of machine learning. While the caustic observation, “garbage-in, garbage-out” has plagued analytics and decision-making for generations, it carries a special warning for machine learning. The quality demands of machine learning are steep, and bad data can rear its ugly head twice — first in the historical data used to train the predictive model and second in the new data used by that model to make future decisions. Read More

    START DRIVING DECISIONS WITH MACHINE DATA.

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