Semi-Structured Data
Semi-structured data is a type of data that does not adhere to a rigid schema like structured data (e.g., relational databases) but has some organizational properties, such as tags or markers, that make it more flexible than unstructured data. It often includes formats like JSON, XML, and YAML, which allow for nested or hierarchical data representation without requiring predefined tables. This makes it suitable for scenarios where data variability is high or when integrating diverse data sources.
Developers should learn about semi-structured data when working with modern web APIs, NoSQL databases, configuration files, or data interchange between systems, as it enables handling complex, evolving data models efficiently. It is particularly useful in big data applications, IoT systems, and microservices architectures where data schemas may change frequently or need to integrate heterogeneous sources. Understanding this concept helps in choosing appropriate storage solutions and serialization formats for scalable and adaptable applications.