Dedomena's anonymization tools anonymize personal data in structured and unstructured databases, reversibly or irreversibly, in accordance with the needs of the information processing, ensuring compliance with all applicable data protection regulations such as GDPR and CCPA, amongst others.
Comply with the European GDPR and any other data protection regulations by anonymizing personal data when necessary.
With Dedomena, securely anonymize your data on a day-to-day basis with best-of-breed artificial intelligence
Select the files and data you want to anonymize. Our solution will automatically detect the format, language and optimal configuration for further processing.
Data anonymization plays an important role in maintaining data security and privacy across sectors
Compliance with regulatory requirements regarding GDPR or CCPA, amongst others.
Obtaining data and insights from structured and unstructured databases, and the capacity to perform better advanced analytics on anonymized data.
Legally share private and sensible data both internally and with third parties without compromising confidentiality and security.
If data is stolen through a data breach, it would have no practical value outside of the organisation.
Our approach to anonymization makes data consistent among multiple systems, making anonymized data reliable for analysis, development and testing.
Efficient machine learning algorithms allow shorter implementation time. Once the model is generated , you can use anonymized data on demand.
When is data anonymization crucial for your company?
Effective anonymization of personal data eliminates the risks to individuals' data privacy. Data can be processed more easily and be used for multiple purposes.
Medical records and health data to be shared or analyzed with other centres and doctors.
Behavioural patterns can lead to identification of people behind them, compromising their identity.
Storage, processing and migration of data in cloud environments must be performed in a secure way.
Banking data that is stored in different repositories to be able to extract financial insights and spending patterns of different types of users anonymously.
Location data is very sensitive because human trajectories show habits such as where you live, work and meet people.
Check out some of our explanatory articles or cross-industry
use cases to know more