Tractian is the Industrial Copilot for maintenance and reliability, combining hardware and software solutions to monitor asset performance, manage industrial operations, and implement predictive maintenance strategies. Its AI-driven platform empowers businesses to prevent unplanned equipment downtime and boost production output. The company is headquartered in Atlanta, GA, and extends its presence globally with offices in Mexico City and Sao Paulo. Learn more at tractian.com.
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Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.
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Concentio
The analysis of data from diverse IoT sources, such as sensors and devices, facilitates predictive and prescriptive insights that empower users to address potential anomalies in real time. Concentio® IoT Doctor effectively processes data from various IoT endpoints, notifying users of any faulty incoming data to ensure that issues are resolved before the data is utilized for further analytical purposes. Additionally, the Concentio® Production Line Fault Prediction tool leverages AI to conduct predictive assessments of production line components by analyzing IoT data, videos, and images. Meanwhile, Concentio® Optimal Asset Management scrutinizes incoming information from a network of utility service assets, allowing users to schedule timely maintenance and ultimately reduce capital expenditures by informing strategic asset replacement decisions. This comprehensive approach not only enhances operational efficiency but also significantly contributes to improved asset longevity and performance.
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SensorCloud
SensorCloud stands out as an innovative platform for storing, visualizing, and remotely managing sensor data, utilizing robust cloud computing technologies to ensure exceptional scalability, quick data visualization, and customizable analytical capabilities. Among its key features are FastGraph, MathEngine®, LiveConnect, and the OpenData API, all designed to enhance user experience. The platform enables users to effortlessly construct dashboards for data visualization, ranging from straightforward Timeseries Graph widgets to more complex configurations featuring Radial Gauges, Text Charts, Linear Gauges, FFTs, and Statistics. Given that SensorCloud accommodates unlimited data uploads and LORD's sensors operate at very high sampling rates, the ability to swiftly visualize extensive datasets is crucial. Our search for an existing application that could manage substantial data volumes was unfruitful; thus, we developed a proprietary algorithm tailored to meet our unique needs and challenges in handling large-scale sensor data. Ultimately, this dedication to innovation ensures that SensorCloud remains a leader in the realm of sensor data management.
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