Data Integrity

Data integrity: The accuracy, completeness, consistency, and trustworthiness of data throughout its life cycle.

Accuracy: The degree to which the data conforms to the actual entity being measured or described.

Completeness: The degree to which the data contains all desired components or measures.

Consistency: The degree to which data is repeatable from different points of entry or collection.

Data constrains: The criteria that determine whether a piece of a data is clean and valid.

Validity: The degree to which the data conforms to constraints when it is input, collected, or created.

Cross-field validation: A process that ensures certain conditions for multiple data fields are satisfied.

Dealing with Insufficient Data

Data range: Numerical values that fall between predefined maximum and minimum values.

Estimated response rate: The average number of people who typically complete a survey.

Data manipulation: The process of changing data to make it more organized and easier to read.

Data replication: The process of storing data in multiple locations.

Data transfer: The process of copying data from a storage device to computer memory or from one computer to another.

Random sampling: A way of selecting a sample from a population so that every possible type of the sample has an equal chance of being chosen.