data validation - definizione. Che cos'è data validation
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Cosa (chi) è data validation - definizione


Data validation         
TECHNICAL PROCESS
Data Checking; Validation rule; Validation routine; Input validation; Validation scheme; Presence check; Data Validation; Cross-reference validation; Validation of data
In computer science, data validation is the process of ensuring data has undergone data cleansing to ensure they have data quality, that is, that they are both correct and useful. It uses routines, often called "validation rules", "validation constraints", or "check routines", that check for correctness, meaningfulness, and security of data that are input to the system.
Data validation and reconciliation         
  • Normally distributed measurements without bias.
  • Normally distributed measurements with bias.
Random and systematic errors
  • Sensor redundancy arising from multiple sensors of the same quantity at the same time at the same place.
  • Topological redundancy arising from model information, using the mass conservation constraint a=b+c\,\!, for example one can calculate c\,\!, when a\,\! and b\,\! are known.
Sensor and topological redundancy
  • Calculable system, from d\,\! one can compute c\,\!, and knowing a\,\! yields b\,\!.
  • non-calculable system, knowing c\,\! does not give information about a\,\! and b\,\!.
Calculable and non-calculable systems
TECHNOLOGY TO CORRECT MEASUREMENTS IN INDUSTRIAL PROCESSES
User:Robcha/Data Validation and Reconciliation; Data Validation and Reconciliation; Data reconciliation; Industrial process data validation and reconciliation
Industrial process data validation and reconciliation, or more briefly, process data reconciliation (PDR), is a technology that uses process information and mathematical methods in order to automatically ensure data validation and reconciliation by correcting measurements in industrial processes. The use of PDR allows for extracting accurate and reliable information about the state of industry processes from raw measurement data and produces a single consistent set of data representing the most likely process operation.
Training, validation, and test data sets         
THREE DATASETS USED IN MACHINE LEARNING
Training set; Validation set; Dataset (machine learning); Training data set; Training data; Test set; Training, test and validation sets; Training, test, and validation sets; Out-of-sample; Trainable parameter; Trained parameter; Train parameter; Model training; Training, validation, and test sets; Holdout data set; Training, validation, and test datasets; Training, validation, and test data; Training dataset
In machine learning, a common task is the study and construction of algorithms that can learn from and make predictions on data. Such algorithms function by making data-driven predictions or decisions, through building a mathematical model from input data.