Data Accuracy, Integrity and Bias

Data Accuracy
Data being free from errors relates to data accuracy. These errors can be caused when collecting the data, such as in surveys, through the processing of data and can be caused by simply out-of date data.
An example of data accuracy is someone entering an order form for an item being purchased. The individual enters the data in about his/her personal details and enters the wrong house number. This error can have huge side effects such as this individual not ever getting the item they paid for. Data accuracy can be easily prevented by taking the time to check over your details being filled in, and the website manufacturer can increase data accuracy by making the customer fill in important details such as address, twice.

Data Integrity
Data integrity refers to the reliability and accuracy of the data. This should be ensured by the use of verification and validation checks, and the elimination of redundant data.
An example of data integrity is a buyer of delivered newspaper. If this customer were to move house and not change the address on the subscription, the data has therefore lost its integrity.

Bias
Data bias is a false emphasis or representation of data, leading to inaccurate information. Bias can be introduced when deciding what data to collect, when collecting data or when processing or presenting data.
A great example of bias when presenting data is through comparison of tables. Companies can make their productivity seem higher than other companies through a easy process of changing the Y and X axis to suit there needs.