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Automatic data integrity protection

Self-Healing

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For many company data, retention periods of ten, thirty or more years apply. Archived data must be reliably protected on its "long journey". With the rapidly increasing volumes of data, the risk of losing data or no longer having it in a correct and legally compliant form is also constantly growing.

 

Data corruption or loss can have enormous economic and legal consequences. So how can organizations ensure the integrity of data over a long period of time?

Causes of data loss & corruption

During the retention period of archived data, its integrity must be ensured in order to minimize business risks and meet various requirements (laws, compliance, internal requirements). The most common causes of data loss and unintentional data modification include data corruption, hardware mirroring limitations, accidental deletion and data migrations.

 

Silent data corruption

Silent data corruption is the random changing of bit states on the storage medium without external influence. This can falsify archive data and make it unreadable. The causes of this "tilting" of individual bits include aging of the media and chemical or electro-magnetic processes.

 

Limitation of hardware mirroring and reorganization of data

In hardware-based archive systems, replicating data at the storage level carries the risk of transferring logical errors to the target system. Hardware-based archive systems sometimes employ RAID configurations that organize multiple physical mass storages. These can cause unintentional data corruption: The more full a storage is, the more frequently data is reorganized. This increases the probability that certain data has already been written - but the associated parity information has not yet been written. If an undesired event occurs at this moment - e.g. a short-term inaccessibility of the write cache - data loss is imminent.

 

Data migrations

During the archiving period, data often has to be migrated several times. This involves transferring data from one system to another. This moving can result in unintentional transfer errors, which can lead to damage or loss of sensitive or critical data. For example, content-related and important meta-information such as retention period, timestamps or IDs can be lost.

Whitepaper: Future-proof protection of business-critical data

During the long retention periods of data and documents, their integrity must be reliably protected. At the same time, the storage industry is experiencing rapid technological progress. Archive solutions without hardware dependency and with open industry standards are in demand.

 

Learn in this whitepaper how a Software-Defined Archiving approach helps you protect the integrity of business data and meet compliance requirements in the long term.

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Self-Healing: Automatic data integrity protection

Until now, proprietary archive systems have often failed to provide complete protection against the corruption or loss of corporate data - whether through silent data corruption or errors in the migration, replication and reorganization of data. Without a secure backup and the ability to detect creeping data corruption or defects, errors are often not noticed until it is already too late - namely, when the data is already corrupted or no longer available. Therefore, an archiving solution must be able to check and guarantee the integrity of the stored data. This capability is essential for an audit-proof archive and can be ensured with the help of a "self-healing" function.

 

What does Self-Healing mean?

The self-healing functionality enables continuous monitoring and assurance of data integrity. The data is archived synchronously on any two storage systems. Each data record is assigned a content-related hash value (checksum), which is stored as an archive object together with all important additional information. The automatic self-healing process then checks the consistency and integrity on all storage paths. Damaged or invalid archive objects are identified using the hash value and automatically repaired - by replacing the damaged data set with the valid one. In this way, logical or technical errors from System-A cannot affect the replicated System-B.

The self-testing feature also allows continuous integrity checks to be performed and potential data corruption to be detected and reported if data replication is not desired.

 

By managing archive objects in a content-based and object-oriented manner, it is possible to ensure that users always have access to valid archive data in the long term. With the help of the self-healing function, silent data corruption, data damage or loss can be prevented and the long-term integrity and availability of important company data can be ensured. Data migrations are also possible without loss of evidential value.

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