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Media Coverage: Applying Machine Learning on Operational Data

May 8, 2021

dotData’s Sachin Andhare was recently published in industry publication SmartIndustry on the subject of applying machine learning to operational data. As sensors everywhere generate time-series data, manufacturing is becoming driven by advanced analytics and artificial intelligence to improve production, streamline processes, and make better decisions. AI allows manufacturing companies to drive innovation. Augmented data discovery, predictive analytics, and machine learning-based modeling are required to drive AI innovation and adoption in manufacturing.

While AI can bring dramatic benefits to manufacturing, implementing it is challenging because of the necessary steps and data science skills needed. Industrial data management requires a scalable environment with high-performance analytics is needed. Using AI automation, manufacturers can reduce the cost to implement AI and speed up the painfully slow AI deployment.

The ideal AI-automation solution for the industrial manufacturing industry should automatically use an AI-based engine to discover and build ML-ready feature tables from operational data. Augmented-data discovery, AI automation, and real-time analytics will help manufacturers move faster, iterate rapidly, and be more agile and accurate in their decision-making.

Head over to SmartIndustry to read the article and learn more about how sensor technologies are creating a new flood of data that will empower Industry 4.0, powered by AI Automation and Data Analysis. Read the whole article at SmartIndustry today .