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    Data quality dimensions: Timeliness

    In this latest post, we look at one of the DAMA six dimensions of data quality – timeliness


    The degree to which data represent reality from the required point in time.


    Time difference

    Often this measure is used to assess the effectiveness of a process. Consider a social housing example, we may have a time constraint of 7 days to turn around a void property and make it available for a new applicant. If this data is not recorded accurately in time, it could mean that a person is not adequately housed.

    Timeliness is also an aspect for consideration when considering data protection i.e. how long should we keep data for. For example, if there is no legal basis for holding data after say 12 months, then the data should be removed in accordance with your data retention policy guideliness.

    Infoboss can help enormously here by allowing you to create timeliness checking rules in your data and then automatically executing them to alert data owners when an exception occurs. For example, one infoboss client used the software to ensure that a new customer had all critical data needed for the customer lifetime entered correctly within 7 days of receiving instruction as a new client. The rules established where able to check that national insurance number, name, address, phone, email, gender, date of birth where all captured over the course of 7 days. If not, the data owner received an alert and the record was tracked until resolved. The difference for this client was significant, they discovered there were thousands of customers where they had not captured all of the information correctly. By introducing the timeliness check they were able to prevent any new clients being setup with incorrect data. We call it switching off the dirty-data tap!

    Look out for our other posts on the six data quality dimensions.

    To discover more about how infoboss can help support your data quality and data protection initiatives, please get in touch.