Data Entities and Relationships

A visual representation of data elements and their relationships in a database.

ERD showing data structure and relationships, part of solution design.

Detailed ERD showing database implementation, including non-functional requirements like performance and security.

Structured collection of information, easily stored and retrieved.

Data element describing/detailing the entity.

A person, object, concept, or event in a database.

Connection between entities (e.g., "enroll").

Format of data storage (e.g., integer, character, string).

Data that accurately reflects entities and relationships in a system.

Deep understanding of how a business operates and flows of data.

Gathering data requirements from stakeholders (business owners, etc.).

Checking existing documents (requirements, diagrams) to find important data.

Organizing a database to reduce data redundancy and improve efficiency.

Repeating the same data in multiple places.

A visual representation of database entities and their relationships.

Comparing database and diagram results to ensure accuracy.

Ensuring that normalized tables accurately reflect relationships in the Entity-Relationship Diagram (ERD).

Eliminating redundancy and improving data integrity in a database.

Fields in a table that link to primary keys in another table, establishing relationships between entities.

A visual representation of the entities and relationships in a database.

Resolving conflicts or inconsistencies that arise during the normalization process.

Smaller, independent tables resulting from the normalization process, reducing redundancy.

Storing the same data multiple times in a database.

Checking attribute alignment with the ERD and ensuring the accuracy of data relationships.

The Student Table contains attributes like Student#, Student Name, and DateOfBirth. Student# is the key attribute.

Contains course details like Course#, Course Name, and Duration. Course# is a unique identifier of a course.

Links student results to specific courses, including student ID, course ID, marks achieved, and grades.

Stores the exam date for each course which helps with scheduling and other administrative aspects.

Student Name and DateOfBirth are dependent on Student# in the STUDENT table. This means one student has only one name and birthday.

Splitting tables like Student_Course_Result into separate tables like STUDENT, COURSE, RESULT, EXAM_DATE removes redundant data and improves database structure.

The Student# is the key attribute in the STUDENT table, uniquely identifying each student.

The initial step in resolving any issue, involving understanding and defining the specific problem or challenge.

Collecting relevant data and information related to the issue, such as system logs, user feedback, or performance metrics.

Examining the source of the issue to determine the underlying cause. This might involve code, database design, or network configuration.

Suggesting potential solutions based on the root cause analysis, including code changes, database optimization, or security enhancements.

Assessing the impact and trade-offs of proposed solutions, considering factors like cost, time, and compatibility.

Putting the chosen solution into action and then thoroughly testing it to ensure it works as intended.

Keeping a close watch on the system after implementing the solution, tracking performance metrics and addressing any new issues that arise.

Continuously adjusting the solution or making further improvements based on monitoring results and feedback.

The process of creating a detailed record of the data model's structure, relationships, and constraints.

A detailed explanation of each entity within the data model, including its purpose, attributes, and any constraints.

A list of each attribute present in an entity, along with their names, data types, lengths, and constraints.

A clear explanation of the relationships between entities, including their types (one-to-one, one-to-many, etc.) and any applicable constraints.

Documentation serves as a vital reference for developers, database administrators, and other stakeholders. It helps them understand the structure and relationships within the data model.

Entity descriptions explain the purpose and significance of each entity within the data model, helping stakeholders understand their roles in the system.

Attribute definitions help ensure data consistency and accuracy by clearly defining the characteristics of each attribute.