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AI-based solution designed to automate personal data discovery and classification
Discover personal data across multiple systems in the cloud or on-premise
Harbor cooperation between DPO, Legal Services, IT and Marketing
Turn data subjects request into an automated workflow with a clear insight into data every step of the way
Collaborate with stakeholders and manage DPIA and LIA in real-time with Assessment Automation
Guide your partners trough vendor management process workflow
Identifying the risk from the point of view of Data Subject
Quickly respond, mitigate damage and maintain compliance
Consolidate your data and prioritize your relationship with customers
Privacy portal allows customers to communicate their requests and preferences at any time
Introducing end-to end automation of personal data removal

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General Data Protection Regulation

Here you can find the official content of the Regulation (EU) 2016/679 (General Data Protection Regulation) in the current version. All Articles of the GDPR are linked with suitable recitals.

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Machine learning

Machine learning is a type of artificial intelligence (AI) that involves teaching computers to learn from data, without being explicitly programmed to perform a specific task.

In machine learning, algorithms are used to analyze and identify patterns in large datasets, and the computer is then able to use these patterns to make predictions or decisions based on new data.

There are three main types of machine learning: supervised learning, unsupervised learning, and reinforcement learning.

In supervised learning, the computer is trained on a labeled dataset, where each data point is tagged with the correct answer. The computer then uses this labeled data to learn how to recognize patterns and make predictions on new, unlabeled data.

In unsupervised learning, the computer is given an unlabeled dataset and must identify patterns and relationships in the data on its own.

This type of learning is often used for tasks such as clustering and anomaly detection.

In reinforcement learning, the computer learns by interacting with an environment and receiving feedback in the form of rewards or punishments.

The computer then adjusts its actions to maximize its rewards over time.

Machine learning has many practical applications, including image and speech recognition, natural language processing, and predictive analytics.

It is used in a variety of industries, from healthcare and finance to transportation and manufacturing.

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