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INFO MANAGEMENT WK 4
Relational Database Model
| Question | Answer |
|---|---|
| is a collection of information that organizes data in predefined relationships where data is stored in one or more table of columns and rows | Relational Database |
| The main structure that stores data in rows and columns. Each table usually represents one type of entity (e.g., Students, Books, Employees). | Tables (Relations) |
| A unique identifier for each record in a table. | Primary Key |
| A field that links one table to another. It establishes a relationship between tables. | Foreign Key |
| Define how data in one table relates to another (1:1, 1:M, M:M). | Relationships |
| The process of organizing data to reduce redundancy and improve data integrity. Ensures each piece of data is stored only once. | Normalization |
| The standard language used to manage and manipulate relational databases | SQL (Structured Query Language) |
| SELECT INSERT UPDATE DELETE CREATE TABLE | retrieve data Add new data modify data remove data create a new table |
| Developed the relational model organizes data into relations (tables) and also Based on mathematical set theory and predicate logic. | Edgar F. Codd (1970) |
| Represent a single record or data item. | Tuples (Rows) |
| Represent the properties or characteristics of the entity | Attributes (Columns) |
| Define the allowable values for an attribute (e.g., Year can only be 1–4). | Domains |
| Maintain uniqueness and relationships. | Keys |
| Unique identifier for a record. | Primary Key |
| Establishes a link to another table. | Foreign Key |
| Potential key that can serve as a Primary Key. | Candidate Key |
| A key made up of two or more fields. | Composite Key |
| is the structured process of defining how data is stored, organized, and accessed efficiently in a database system. It involves translating real-world requirements into a well-structured database schema | Database Design |
| properly designed databases ensure data is stored efficiently and retrieved quickly | Efficiency |
| good design makes it easier to scale as data or application requirements grow | Scalability |
| ensures data remains accurate and consistent. | Data Integrity |
| simplifies tasks like updates, backups, reduces risk of errors and downtime. | Maintenance |
| gathering what data needs to be stored, how it will be used. | Requirements Analysis |
| e.g., creating ER diagrams: entities, relationships. | Conceptual Design |
| converting ER diagram into tables/relations, normalization, constraints. | Logical Design |
| storage engines, indexing, partitioning, performance tuning. | Physical Design |
| ensure correctness, performance, functionality | Testing & Evaluation |
| moving to production, training users. | Deployment |
| monitor performance, backups, updates. | Maintenance & Monitoring |
| organizing data to reduce redundancy and improve integrity. | Normalization |
| each column has atomic indivisible values. | 1NF |
| all non-key attributes are fully functionally dependent on the primary key. | 2NF |
| no transitive dependency (attributes depend only on primary key) | 3NF |
| stricter version where every determinant is a candidate key | Boyce Codd NF |