Data governance refers to the policies and practices used to manage and protect data throughout its lifecycle. It ensures data quality, compliance, and security within an organization.
Data integration for IoT applications poses significant challenges due to various factors such as volume, data heterogeneity, security, and real-time processing requirements. Integration of diverse data sources, handling large data volumes, ensuring data privacy and security, and addressing real-time processing needs are some of the key challenges in data integration for IoT applications.
In order to handle GDPR compliance and data protection in backend systems, there are several key measures and strategies that need to be implemented. These include implementing proper data encryption, implementing access controls and user authentication, conducting regular data privacy impact assessments, and ensuring transparent and informed consent from users. Additionally, it is important to establish clear data retention and deletion policies, maintain proper data governance, and have a robust incident response plan in place to address any potential data breaches.
