The term big data is thrown around a lot these days, but one of the main areas where this term truly applies is large industrial units (manufacturing facilities, refineries, vehicle assembly plants etc.). With the advent of digital technologies and advanced sensors, the amount of data being collected every day is astounding. This poses several challenges: these datasets are prone to numerous errors and issues.
Timeliness is a measure of how often data is available when it’s expected. It can be calculated as the time difference of when information should be available and when it is actually available. Informed business decisions depend upon consistent and timely information. Therefore, critical measures of data quality include tests specifying how quickly data must be propagated and compliance with other timeliness constraints such as periodic availability.