In an era of exponentially accelerating data production and consumption, managing inactive data, securing and duplicating your data in non-production environments is a particularly time-consuming task.
Data Lifecycle
Get high quality data and rationalise its useFunctionalities
Campaign
Manage your documentation and campaigns
Data Quality
Guarantee high quality data suitable for use in operations, decision making and planning
Data Archiving
Archive your inactive data and destroy those that need to be destroyed
Data Purging
Archive your inactive data and destroy those that need to be destroyed
Data Anonymization
Anonymise your sensitive data
Data Refresh
Update your data to keep it meaningful and reliable
Data Reversibility
Transfer and recover data from one environment (Cloud…) to another by guaranteeing their integrity while meeting regulatory requirements
Data Comparison
Detect gaps in structure and content between your environments
Bénéfices
- Reduce time spent on functional and technical specification through retro-documentation
- Data quality (automated data profiling and quality campaigns)
- Minimize implementation and maintenance costs of the archiving and anonymization system
- Automatically take into account any changes in the data model
- Guarantee the integrity of the data in your different environments
- Optimize and secure the creation of your non-production databases
Cas d’usage
- Implement a data quality project
- Build datasets for your digitisation and lifecycle management projects to archive, destroy, anonymise, manage reversibility, merge, compare, decommission, etc
- Implementation of a dynamic & recurrent archiving system (RGPD)
- Creation of non-production environments
- Datamart creation and feeding project (Data warehouse)
- Retirement of the database
Discover other functionalities of the Systnaps solution :
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