Concept
Behavioral data refers to the information collected about individuals' actions, interactions, and engagements, often used to understand patterns, preferences, and decision-making processes. This data is pivotal in fields like marketing, psychology, and user experience design, enabling the prediction of future behaviors and the customization of services or products.
Concept
Normalization is a process in database design that organizes data to reduce redundancy and improve data integrity by dividing large tables into smaller, related tables. It involves applying a series of rules or normal forms to ensure that the database is efficient, consistent, and scalable.
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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.
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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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A primary key is a unique identifier for a record in a database table, ensuring that each entry is distinct and easily retrievable. It is essential for maintaining data integrity and establishing relationships between tables in a relational database management system.
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Partial dependency refers to a situation in a database where a non-prime attribute is functionally dependent on part of a candidate key, rather than the whole key. This often leads to redundancy and anomalies, and is typically resolved by normalizing the database to Third Normal Form (3NF).
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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.
Concept
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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Normalization Process is a systematic approach to organizing data in a database to reduce redundancy and improve data integrity. It involves decomposing tables into smaller, more manageable pieces while ensuring that relationships between data entities are preserved.
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Normal forms are structured representations of data that aim to reduce redundancy and dependency in relational databases, ensuring data integrity and efficiency. They are achieved through a series of increasingly strict rules or 'normalizations', each building on the last, to organize data into relational tables that minimize duplication and potential anomalies.
Concept
Database anomalies are inconsistencies and issues that arise when performing operations on a database that is not properly normalized, leading to problems such as redundancy, dependency, and integrity violations. These anomalies can manifest as insertion, update, or deletion anomalies, each disrupting data accuracy and consistency within a database system.
Concept
Normal form is a standardized way of organizing data in a database to reduce redundancy and improve data integrity. It involves a series of guidelines, known as Normal forms, that databases must adhere to in order to ensure efficient data structure and retrieval.
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