This paper introduces a relational model for large shared data banks, emphasizing data independence and consistency. E. F. Codd proposes a model based on n-ary relations, normal forms, and a universal data sublanguage. The relational model is superior to graph or network models as it avoids superimposing additional structure for machine representation, enabling a high-level data language that maximizes independence between programs and data representation. It also provides a sound basis for treating derivability, redundancy, and consistency of relations. The paper discusses data dependencies in existing systems, including ordering, indexing, and access path dependencies. These dependencies can lead to inconsistencies and require changes in data representation. The relational model addresses these issues by allowing domain-unordered relationships, where domains are uniquely identifiable without using position. This approach simplifies data handling and reduces dependency on specific data structures. Normalization is introduced as a method to eliminate nonsimple domains, simplifying data storage and communication. The paper also discusses linguistic aspects, proposing a universal data sublanguage based on predicate calculus. This language allows for the declaration of relations and their domains, and supports retrieval, insertion, deletion, and updates of data. The paper further explores operations on relations, including permutation, projection, join, and composition. These operations are crucial for deriving relations from other relations and ensuring data consistency. The paper highlights the importance of normalization in reducing redundancy and ensuring data integrity. It also discusses the challenges of maintaining data independence and the need for efficient storage and retrieval mechanisms in large data banks. The relational model is shown to be more flexible and efficient than existing data models, providing a foundation for future data systems.This paper introduces a relational model for large shared data banks, emphasizing data independence and consistency. E. F. Codd proposes a model based on n-ary relations, normal forms, and a universal data sublanguage. The relational model is superior to graph or network models as it avoids superimposing additional structure for machine representation, enabling a high-level data language that maximizes independence between programs and data representation. It also provides a sound basis for treating derivability, redundancy, and consistency of relations. The paper discusses data dependencies in existing systems, including ordering, indexing, and access path dependencies. These dependencies can lead to inconsistencies and require changes in data representation. The relational model addresses these issues by allowing domain-unordered relationships, where domains are uniquely identifiable without using position. This approach simplifies data handling and reduces dependency on specific data structures. Normalization is introduced as a method to eliminate nonsimple domains, simplifying data storage and communication. The paper also discusses linguistic aspects, proposing a universal data sublanguage based on predicate calculus. This language allows for the declaration of relations and their domains, and supports retrieval, insertion, deletion, and updates of data. The paper further explores operations on relations, including permutation, projection, join, and composition. These operations are crucial for deriving relations from other relations and ensuring data consistency. The paper highlights the importance of normalization in reducing redundancy and ensuring data integrity. It also discusses the challenges of maintaining data independence and the need for efficient storage and retrieval mechanisms in large data banks. The relational model is shown to be more flexible and efficient than existing data models, providing a foundation for future data systems.