The Data Integrity and Normalization topic introduces students to methods of maintaining accurate, consistent, and reliable data in databases. It covers key areas such as integrity constraints, types of data integrity, anomalies, and normalization techniques including first, second, and third normal forms. Understanding data integrity and normalization equips students with essential skills to design efficient databases, minimize redundancy, and ensure reliable data storage. At PLS Academy, this topic is taught in a simple, exam-oriented manner, emphasizing MCQs, past paper trends, and practical examples, helping students excel in FSC Computer Science exams and university entry tests like NUST, FAST, and other computing programs.
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