Exam2

  1. Entity: An object or thing in the real world that is distinguishable from other objects. In a database, it is typically represented as a table, where each row represents a specific instance of that entity.

  2. Relationship: The association between two or more entities in a database. It defines how the entities are related to one another (e.g., one-to-many, many-to-many).

  3. One-to-many: A type of relationship between two entities where one instance of the first entity can be associated with multiple instances of the second entity, but each instance of the second entity is associated with only one instance of the first entity.

  4. Many-to-many: A type of relationship where multiple instances of one entity can be associated with multiple instances of another entity. This typically requires a junction table to represent the relationship in a relational database.

  5. ER Modeling (Entity-Relationship Modeling): A conceptual framework for designing databases, which uses entities, relationships, and attributes to represent real-world data and its relationships.

  6. ER Diagram (Entity-Relationship Diagram): A graphical representation of the entities, relationships, and their attributes in an ER model, commonly used in database design.

  7. Data Redundancy: The unnecessary repetition of data within a database. This can lead to inconsistencies, increased storage requirements, and maintenance challenges.

  8. Single-valued vs Multi-valued:

    • Single-valued: An attribute that can hold only one value per record (e.g., a person’s date of birth).

    • Multi-valued: An attribute that can hold multiple values per record (e.g., a person having multiple phone numbers).

  9. Top-down vs Bottom-up:

    • Top-down: A design approach where you start with a high-level overview of the system and progressively break it down into smaller components.

    • Bottom-up: A design approach where you begin by focusing on specific details or components and work up to the full system.

  10. First Normal Form (1NF): A database is in 1NF if all columns contain atomic (indivisible) values, there are no repeating groups or arrays, and each column contains values of a single type.

  11. Flattening: The process of converting a multi-dimensional structure (such as a relational database or object) into a flat, two-dimensional format (e.g., a table).

  12. Data Anomaly: An inconsistency or problem in the database that can arise due to poor design, such as incorrect or redundant data.

  13. Insertion Anomaly: A problem that occurs when certain data cannot be inserted into a database without the presence of other data (due to normalization issues).

  14. Deletion Anomaly: A problem that arises when the deletion of data causes unintended loss of other related data.

  15. Update Anomaly: A problem that occurs when data is duplicated in a database, and updating one instance requires multiple changes, increasing the risk of inconsistencies.

  16. Primary Key: A unique identifier for each record in a database table. It must contain unique values and cannot be null.

  17. Candidate Key: A set of attributes that can uniquely identify each record in a table. Any candidate key can be chosen as the primary key.

  18. Composite Key: A key composed of two or more attributes that together uniquely identify a record in a table.

  19. Foreign Key: An attribute in a table that refers to the primary key of another table. It establishes a relationship between the two tables.

  20. Lossless Join Property: A property of a decomposition where, after splitting a table into multiple tables, no information is lost, and the original table can be reconstructed from the decomposed tables.

  21. Functional Dependence: A relationship between two attributes where the value of one attribute (the determinant) determines the value of another attribute.

  22. Determinant: An attribute or set of attributes that uniquely determines the value of another attribute. In a functional dependency, the determinant is the left-hand side.

  23. Partial Dependence: A type of functional dependence where an attribute depends on part of a composite primary key but not on the whole key. This occurs in 1NF but needs to be eliminated in 2NF.

  24. Second Normal Form (2NF): A table is in 2NF if it is in 1NF and all non-key attributes are fully functionally dependent on the entire primary key (i.e., there are no partial dependencies).

  25. Transitive Dependence: A functional dependency where one non-key attribute depends on another non-key attribute, which depends on the primary key. This violates 3NF.

  26. Third Normal Form (3NF): A table is in 3NF if it is in 2NF and all attributes are directly dependent on the primary key, with no transitive dependencies.

  27. Atomic: A term used to describe data that cannot be divided into smaller units. An atomic attribute holds a single, indivisible value.

  28. Parse: To analyze and break down data or syntax into smaller components, typically for further processing or understanding (e.g., parsing a query).

  29. Decomposition: The process of breaking down a database table into smaller tables to remove redundancy and improve the database’s design, typically done during normalization.