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Powered by sensors, connectivity and smart machines, the Internet of Things (IoT) is reshaping the manufacturing and industrial processes, effectively changing the paradigm from ‘repair and replace’ to more of ‘predict and prevent’. By capturing and utilizing data streaming from sensors and connected devices, businesses can now gain visibility into the condition of their valuable assets and specific components in real time. Utilizing IoT and sensor data from connected equipments, organizations can effectively predict when and how an asset might fail, detect variances, understand warning signals, and quickly identify any patterns that might indicate a potential breakdown. Data-centric organizations are using advanced analytics and machine learning to detect anomalies or patterns that are indicative of failure and intervene as soon as initial signs of failure are detected to perform the right maintenance activities.

Download this paper to learn more about how today's enterprises can effectively ingest, process and analyze petabytes of data generated from IoT in order to effectively drive predictive maintenance. Learn more about IoT customer use cases across different verticals, that highlights how some of the leading organizations are utilizing Cloudera and the power of IoT and advanced analytics to drive predictive maintenance.

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