Archiving strategy and data cleansing

Keeping the pitfall of everything

Part of the AVG is that you know where your data is, how long and how you store it and when it will be destroyed. After all, personal data may only be stored if they are necessary for processing. Retention periods are laid down in various laws and regulations, which for international organisations can vary greatly from country to country. Apart from the aforementioned retention period, there is also the right of the data subject to have data deleted if it is processed unlawfully. An archiving strategy is therefore necessary.

Destruction for advanced users

Archiving is often an underexposed theme in the company vision. It is often ‘a profession’ that is practiced in an atmosphere of dustiness and secrecy in dark locations in the belly of an office building and/or on hard disks in data centres. With the arrival of the AVG, organisations have to ask themselves questions and – after decades of neglect – now give this theme serious attention. CRANIUM supports in drawing up a strategy for archiving, including the actual cleaning up of data that has passed its sell-by date. This goes further than just cleaning up personal data: CRANIUM also looks at the metadata and other related business critical data that is used and reused across different departments. Finally, CRANIUM supports the actual destruction in the systems and/or the anonymisation of data if it cannot be deleted for various reasons.

Related solutions

CRANIUM can fully support you in drawing up and implementing your archiving strategy and implementation for cleaning. We have knowledge of the retention periods of more than 50 countries worldwide and we employ archivists. Where necessary, we can also draw up and/or update your data retention procedure, including an archive policy. With the knowledge you gain in the cleaning process you can then also tackle your other outdated data. Cleaning up means knowing what you have, what you want to keep and where to find it. To that extent, the clean-up process can also form the basis for a data strategy, data governance and even data quality.

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