Engineering data preparation is the systematic process of cleansing, structuring, enriching, and tagging raw test and sensor data so engineers can find, trust, and use it quickly for analytics and AI. Done well, it turns chaotic files and logs into a reusable asset that cuts time-to-insight from days to seconds and unlocks predictive models.
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Topics: Test, Big Data, Analytics, Viviota, SAP, Sensors, automotive industry, Real-time computing, COTA, U.S. Grand Prix, Autonomous Vehicles, Sensor Data, Machine Learning, aerospace, Analog Data, ADAS, Hybrid Cars, NIWeek, ESS, ANC, Sensor Data Management, data cleansing, simulation, webinar, Smart Factories, Manufacturing, Intelligent Data handling, Software, LabVIEW, Build Back Better Act, Digital transformation
