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    How Databases work

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    • Introduction to Databases
      • 1.1What is a Database?
      • 1.2Importance of Databases
      • 1.3Types of Databases
    • Database Models
      • 2.1Hierarchical Model
      • 2.2Network Model
      • 2.3Relational Model
      • 2.4Object-oriented Model
    • Relational Databases
      • 3.1Introduction to Relational Databases
      • 3.2Tables, Records, and Fields
      • 3.3Keys and Indexes
    • SQL Basics
      • 4.1Introduction to SQL
      • 4.2Basic SQL Commands
      • 4.3Creating and Modifying Tables
    • Advanced SQL
      • 5.1Joins
      • 5.2Subqueries
      • 5.3Stored Procedures
    • Database Design
      • 6.1Normalization
      • 6.2Entity-Relationship Diagrams
      • 6.3Data Integrity
    • Transaction Management
      • 7.1ACID Properties
      • 7.2Concurrency Control
      • 7.3Recovery Techniques
    • Database Security
      • 8.1Security Threats
      • 8.2Access Control
      • 8.3Encryption and Authentication
    • NoSQL Databases
      • 9.1Introduction to NoSQL
      • 9.2Types of NoSQL Databases
      • 9.3Use Cases for NoSQL
    • Big Data and Databases
      • 10.1Introduction to Big Data
      • 10.2Big Data Technologies
      • 10.3Big Data and Databases
    • Cloud Databases
      • 11.1Introduction to Cloud Databases
      • 11.2Benefits and Challenges
      • 11.3Popular Cloud Database Providers
    • Database Administration
      • 12.1Roles and Responsibilities of a Database Administrator
      • 12.2Database Maintenance
      • 12.3Performance Tuning
    • Future Trends in Databases
      • 13.1In-memory Databases
      • 13.2Autonomous Databases
      • 13.3Blockchain and Databases

    Database Design

    Understanding Data Integrity in Databases

    organized collection of data in computing

    Organized collection of data in computing.

    Data integrity is a fundamental aspect of designing and managing databases. It refers to the accuracy, consistency, and reliability of data stored in a database. Ensuring data integrity means that the data is exactly as it was intended to be and has not been altered or lost in an unauthorized way.

    Importance of Data Integrity

    Data integrity is crucial for various reasons. It ensures the validity and reliability of the data, which is essential for the decision-making process. It also helps to maintain the consistency of the data over its entire lifecycle. Without data integrity, the results of any data analysis may be inaccurate and misleading.

    Types of Data Integrity

    There are three main types of data integrity:

    1. Entity Integrity: This ensures that each row (entity) in a table is unique. It is usually enforced by assigning a unique primary key to each row.

    2. Referential Integrity: This ensures that relationships between tables remain consistent. It is typically enforced by using foreign keys. For example, if a table has a foreign key that references the primary key of another table, then every value of the foreign key must either be null or match an existing value in the other table.

    3. Domain Integrity: This ensures that all data in a column falls within a specific set of values, known as the domain of that column. It is enforced by constraints, such as NOT NULL, UNIQUE, CHECK, and others.

    Constraints in SQL

    SQL provides several constraints to enforce data integrity:

    • NOT NULL: This constraint ensures that a column cannot have a NULL value.

    • UNIQUE: This constraint ensures that all values in a column are different.

    • PRIMARY KEY: A primary key is a combination of NOT NULL and UNIQUE. It uniquely identifies each record in a table.

    • FOREIGN KEY: A foreign key is used to prevent actions that would destroy links between tables.

    • CHECK: This constraint ensures that all values in a column satisfy certain conditions.

    Triggers in SQL

    Triggers are special procedures that are automatically executed in response to certain events on a particular table or view in a database. They can be used to enforce complex business rules or to maintain complex data integrity rules.

    Maintaining Data Integrity

    Maintaining data integrity involves implementing the appropriate constraints and triggers, as well as regularly checking the data for errors and inconsistencies. It also involves creating backups of the data and implementing security measures to prevent unauthorized access or alteration of the data.

    In conclusion, data integrity is a critical aspect of database design and management. By understanding and implementing the principles of entity integrity, referential integrity, and domain integrity, you can ensure that your data remains accurate, consistent, and reliable.

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