According to TechTarget, “data archiving is the process of moving data that is no longer actively used to a separate storage device for long-term retention. Archive data consists of older data that remains important to the organization or must be retained for future reference or regulatory compliance reasons. Data archives are indexed and have search capabilities, so files can be located and retrieved.”
Reasons for archiving data include:
- Lower costs
- Improve performance
- Reduce backup time
- Achieve compliance
Click Procurement Examples for system shall statements.
Here’s some sample text to consider for your acquisition document:
The System must provide the ability for staff to specify archive and purging rules according to retention policies.
The System shall archive all data; including data used in the production system, audit data, inbound and outbound correspondence, attachments, notes, reports, and log files; in compliance with applicable data retention policies.
The System shall support note data retention and lifecycle including archival and purge criteria in compliance with applicable policies.
The System shall archive information in compliance with Federal and state retention policies.
The System shall maintain system data integrity when archiving information.
The System shall provide the ability for Staff to access archived data as part of normal system processing.
The System shall distinguish archived records and their archived status, and not allow such records to be updated.
The System shall monitor the archive process and report the success or failure of the archive.
The System shall allow staff to include or exclude archive databases when conducting searches.
The System shall provide the ability to create archive reports.
The System shall prevent an audit trail from being deleted except in compliance with defined record retention, purge, and archival criteria.
The System shall provide the ability for Staff to configure the archival period and criteria for the audit trail.
The System must archive data according to business rules and allow authorized users to reinstate and interact with archived data.
The Offeror must describe their data archiving functionality and whether archived data remains in the system in separate tables, remains in the productions tables but is flagged as “archived” so as to be ignored by regular operations, archived off to a separate system maintained by the Awarded Vendor, deleted entirely, or whether the vendor archives off to a separate system they expect to be developed and maintained by the Organization.
The Offeror must describe how their solution will un-archive data from the existing legacy archive and the time to access archived data.
The System must identify archived records and not allow archived records to be updated.
The System must monitor the archive process and log the outcome including any errors.
The System must perform routine, at least quarterly, reviews of archived data to verify no loss of archived files and verify the ability to retrieve archived files.
What is the difference between data archiving and data backup?
Data archiving is the process of moving inactive data out of current production systems and into a separate storage device, until the end of a defined retention period, at which point the data is purged. Data backups are copies of production data that are stored either locally or at an offsite location. Backups are used to restore production data if it becomes corrupted or destroyed.
What is the difference between data archiving and data warehouse?
Data archiving is the process of moving inactive data out of current production systems and into a separate storage device, until the end of a defined retention period, at which point the data is purged. A data warehouse is a huge collection of data typically used to create reports, perform data analysis, and to support management decision-making.
What is the difference between data archiving and data purging?
Data archiving is the process of moving inactive data out of current production systems and into a separate storage device, until the end of a defined retention period, at which point the data is purged. Regulations exist that require many organizations to keep vast amounts of historical data for compliance with data retention policies. Data purging is the process of removing data that has reached the end of its defined retention period.