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“Data Types” as a book category gathers works that explain how information is represented, structured, validated, and manipulated across computing and data systems. It spans introductions to primitive and composite types; explorations of type systems (static vs. dynamic, nominal vs. structural), generics, algebraic and dependent types; and their roles in programming languages, databases, and data modeling. Titles range from practical guides for using types in languages like Python, Java, and SQL and in schema formats such as JSON Schema, Avro, and Protocol Buffers to advanced texts on type theory, formal semantics, and program verification. Common themes include correctness and safety, memory layout and performance, serialization and interoperability, schema evolution and nullability, and data quality. The category also covers design patterns for data models and APIs, typing in analytics pipelines, and constraints in distributed systems. Aimed at students, engineers, and researchers, these books show how disciplined use of data types underpins reliable software and robust datasets.

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