Sensor data quality plays a vital role in industrial IoT applications as they are rendered useless if the data quality is bad. Artificial Neural network-based sensor data validation algorithms identify outliers, missing data, constant value, stuck at zero, and filter bad data from useful data. This helps to increase data science productivity and accuracy of anomaly detection and diagnostics models significantly.