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A power source is something that gives energy to make things work, like batteries in toys or the sun for plants. Without a power source, machines and living things can't do what they are supposed to do.
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Concept
First Normal Form (1NF) is a property of a relational database table that requires each column to contain atomic values and each entry in a column to be of the same data type. Achieving 1NF helps eliminate duplicate data and ensures that the database structure is efficient and logically organized.
Concept
Second Normal Form (2NF) is a stage in the normalization process of a relational database where a table is in First Normal Form and all non-key attributes are fully functionally dependent on the primary key. This ensures that there are no partial dependencies of any column on the primary key, thereby reducing redundancy and improving data integrity.
Concept
Third Normal Form (3NF) is a database normalization stage that ensures no transitive dependencies exist, meaning non-key attributes are not dependent on other non-key attributes. This form enhances data integrity and reduces redundancy by ensuring that each non-key attribute is only dependent on the primary key.
Concept
Boyce-Codd Normal Form (BCNF) is a database normalization form used to eliminate redundancy and ensure data integrity by requiring that every determinant in a relation is a candidate key. It is a stricter version of the Third Normal Form (3NF), addressing anomalies that 3NF may not handle by ensuring that no non-trivial functional dependencies exist unless they are on superkeys.
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Functional dependency is a constraint between two sets of attributes in a relational database, where one set uniquely determines another. It is fundamental to database normalization, ensuring data integrity and reducing redundancy by organizing data efficiently.
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Data redundancy occurs when the same piece of data is stored in multiple places within a database or data storage system, which can lead to inconsistencies and increased storage costs. While sometimes intentional for backup and performance reasons, excessive redundancy can complicate data management and compromise data integrity.
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Data integrity refers to the accuracy, consistency, and reliability of data throughout its lifecycle, ensuring that it remains unaltered and trustworthy for decision-making and analysis. It is crucial for maintaining the credibility of databases and information systems, and involves various practices and technologies to prevent unauthorized access or corruption.
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Decomposition is the process of breaking down complex systems or problems into smaller, more manageable parts to simplify analysis, understanding, or problem-solving. It is a fundamental approach used across various fields, including biology, computer science, and mathematics, to enhance clarity and efficiency in addressing intricate challenges.
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A relational database is a structured collection of data that uses a schema to define relationships between tables, enabling efficient data retrieval and manipulation through SQL queries. It ensures data integrity and reduces redundancy by organizing data into tables where each row is a unique record identified by a primary key.
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Anomalies are deviations from the norm, often indicating errors, rare events, or novel insights in data analysis. Understanding anomalies is crucial for fields like fraud detection, quality control, and predictive maintenance, where identifying these outliers can lead to significant operational improvements or risk mitigation.
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Third Normal Form (3NF) is a database normalization stage that ensures all the attributes in a table are functionally dependent only on the primary key, eliminating transitive dependency. Achieving 3NF optimizes database design by reducing redundancy and improving data integrity.
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