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Time series data sets which represent different types of values measured by sensors (for example, temperature or weight). A data record consists of a tag and multiple datapoints, each comprised of a timestamp and a measurement.
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The material account into which materials moved. It designates the start of a Feed Chain.
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ThinkIQ Product offering that uses advanced AI and ML to enable a material-centric view of operations.
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ThinkIQ Product offering which takes your data — standardized and contextualized — and can aggregate and correlate it to your most important metrics.
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The ThinkIQ Vision product offering generates big data where none exists, leveraging cameras and machine vision.
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ThinkIQ product offering level that moves companies past raw data to being able to explore, compare, and contextualize data from disparate systems all on one screen.
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Data values that vary over time; often sensor or calculated data. Time series data is stored in the ThinkIQ Time Series Database. Each value in time is stored as a triple consisting of Value, Time and Status (a.k.a Quality).
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Motivated by legacy processs historians and inspired by emerging stores for data center data, the ThinkIQ Time Series Database is a hyper-scale store specificically designed for Time Series Data.
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An application that charts time series data in graphs and charts.
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A type is used to define the characteristics and behavior of the data for specific objects. Types allow a user to define characteristics and behavior of an object once, then reuse the type on all instances of the same object. See also Introduction to Modeling
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