This Feature Focus article takes a deeper dive into the Zatpark Data Purge tool.
The General Data Protection Regulations (GDPR) and Data Protection legislation require organisations that manage personal data (data controllers) to abide by strict rules making sure client/public information is used fairly and lawfully, is safe and secure and is not held any longer than is necessary.
There is a requirement to remove personal data from your systems once it is no longer necessary to retain it. However, this can be a hugely complex and time-consuming task. Some of the key issues include:
- Finding all the relevant data within your systems
- Ensuring you delete the correct data
- Being able to delete data at scale, allowing you to remove lots of records with the minimum intervention.
Meeting your legal obligations
To help you to ensure that you are meeting your legal obligations and to do this efficiently, Zatpark has created the Data Purge tool. Purge allows the deletion of ticket-related data based on status criteria defined by you. This helps clients meet their Data Protection obligations.
Purge is fully customisable and allows a user to:
- Set conditions by which ticket data is selected for purging making sure only the right information is purged from the system.
- Set the schedule for when the purge process is run for each condition providing a high level of control within a timeframe suited to the individual company.
- Select individual tickets or complete batches for purging allowing individual requirements of a particular company to be met.
- Set a delay period so that tickets marked incorrectly for purging have a period of grace allowing data to be removed from the purge process.
- Select elements of tickets such as attached evidence, contact details, ticket VRM & node logs, images & videos, or notes for purging, enabling all or just elements of a ticket to be deleted minimising storage required.
So, how does Purge work?
The first step is to identify which record types require removal. Using the Node Process Overview will help you to choose those records that have reached the end of the ticket progression. For example, if a ticket has been flagged as Appeal Approved then it has reached the end of the process and may be eligible for Purge.
You will be able to set up several different Purge activities based on different sets of conditions. Each Purge process can include multiple conditions.
Purge can be set up to identify records for removal regularly. Scheduling Purge to run every Tuesday and Friday at 10 am for example, will ‘flag’ those tickets that meet the condition(s) set and stage them ready for ‘confirming for purging’. Example conditions could be ‘void’ tickets and any that have had a condition of ‘Finished’ for more than 2 years. The system identifies any tickets that meet these conditions, marks them ‘ready for purging’ but doesn’t delete them at this stage.
Once the scheduled Purge has been run, one or more tickets may be identified as ‘Ready for purging’. At this stage, individual tickets can be deselected should these need to be retained. For instance, you may choose to retain tickets issued to a repeat parking contravention offender as collective evidence for litigation, etc.
A configurable Purge delay is set (e.g. 7 days), before the flagged records for purge are deleted. You can also specify which elements of a ticket you wish to be purged (such as notes, images, etc.).
Once you have reviewed the tickets that are “Ready for purging”, you can confirm that the data should be purged. Once confirmed, the records will wait in the purge queue and countdown until the purge delay has elapsed before deletion takes place. During the purge delay period, you can abort purge for all or some of the records. Once the purge period reaches zero-days, the records will be removed from the database. Once the purge has been completed, it cannot be reversed.
Zatpark’s Purge Feature is a powerful productivity tool, enabling you to comply with data protection rules while ensuring that your administration team is not tied up with finding and removing personal data from the system, helping you to keep your business costs down.