Publisher's Synopsis
Data storage in IoT is not merely about capacity; it also involves considerations of speed, accessibility, and security. IoT data's dynamic nature often requires agile and scalable storage systems, allowing for real-time data processing and analysis. Additionally, as IoT devices proliferate, the security of stored data becomes paramount. With increasing concerns over data breaches and unauthorised access, professionals must be well-versed in best practices for securing sensitive information against potential threats.
Furthermore, data management in IoT goes beyond storage solutions; it encompasses the entire data lifecycle, from collection and analysis to archiving and deletion. Effective data management strategies must include robust data governance frameworks that ensure compliance with regulations while maintaining ethical standards. As students and professionals delve deeper into this field, they will encounter various methodologies and tools designed to streamline data management processes, which are crucial for maximising the value derived from IoT data.
