What is Reinforcement Learning (RL)? Definition, Algorithms, Examples
There is an ever-increasing number of people, devices and sensors that generate, communicate and share data via the global internet. Analysing this data can help organizations to develop new products, improve their efficiency and effectiveness, as well as to make better decisions. However, there are increasing concerns over the trustworthiness of this data as well as security and compliance challenges over the way that it is used. This report describes the challenges of using Big Data in ways that are secure, compliant and ethical and how a data centric approach to security is essential to meeting these challenges. Societal concerns over how data is being acquired and used are leading to increasingly tough regulations governing how organizations can acquire, store and use data. In addition to existing regulations such as HIPAA, recent examples are the EU GDPR (General Data Protection Regulation) and the CCPA (California Consumer Privacy Act of 2018). GDPR imposes a much tougher regulatory framework that affects organizations worldwide that hold or process personal data relating to residents in the European Union. In order to meet the obligations imposed by these laws, it is essential that organizations implement good data governance as well as data centric security controls over how they acquire, store, process, and analyse data.