No, we don’t hate Spark! We like it a lot – regular blog readers know that we integrated Apache Spark’s MlLib library into our SCALAR product last Fall. If you missed this news, here’s the PRESS RELEASE and BLOG POST.
What the Spark is the name of a meetup event in the Bay Area on February 26, where our principal architect, Mohammed Guller will be presenting. He will talk about the numerous benefits of Spark and why it is fast replacing Hadoop MapReduce for batch and stream processing jobs. If we’re piqued your interest, please SIGN UP for this meetup.
Glassbeam integrated MlLib with it’s proprietary, patent-pending technologies to provide end-customers with very powerful predictive analytics on product operational data. We’re already seeing great success for this capability in one of the hottest industry trends today: predictive maintenance. That is, the ability for product manufacturers (and specifically their support and services groups) to predict and preempt product issues that are likely to happen in the field. Glassbeam has a very handy ‘Rules and Alerts’ module to model and detect product anomalies; not this capability is greatly bolstered by machine learning capabilities.
Predictive Maintenance, in turn, realizes numerous benefits for any company. It helps product manufacturers avoid costly and embarrassing product failures, helps support teams become significantly more productive, and even helps services organizations identify new revenue streams based on value-added services to end-customers. As a result, we’re seeing machine data analytics become a key imperative for organizations of all size – especially where complex products generate voluminous machine data that can be mined to glean valuable insights.