Database Design Methodology Chapter 2

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Questions and Answers

What is the first step in deriving relations for a logical data model?

Step 2.1 is to derive relations for the logical data model.

How is the relational schema validated in Step 2?

It is validated using normalization.

What purpose do integrity constraints serve in the logical data model?

Integrity constraints ensure that the logical data model accurately represents important rules and conditions of the data.

What is checked during Step 2.3 related to user transactions?

<p>The relations are validated against user transactions to ensure they support user requirements.</p> Signup and view all the answers

What happens in Step 2.5 of the logical data model process?

<p>In Step 2.5, the logical data model is reviewed with the users for validation.</p> Signup and view all the answers

What is the optional step of merging distributed user views in the logical data model called?

<p>Step 2.6 is the optional step to merge logical data models into a global data model.</p> Signup and view all the answers

What should be checked regarding future growth in Step 2?

<p>Future growth should be assessed to ensure the model can accommodate future data requirements.</p> Signup and view all the answers

Why is Step 2.6 not necessary for certain database designs?

<p>Step 2.6 is omitted if the database only has a single user view or uses a centralized approach.</p> Signup and view all the answers

What is the role of a foreign key in a relational database?

<p>A foreign key acts as a reference to a primary key in another relation, establishing a link between the two entities.</p> Signup and view all the answers

How do you determine which entity is the parent and which is the child in a relationship?

<p>The parent entity is identified as the entity that posts its primary key into the child entity as a foreign key.</p> Signup and view all the answers

Describe a strong entity type in the context of a conceptual data model.

<p>A strong entity type has its own unique primary key and does not rely on any other entity for its identification.</p> Signup and view all the answers

What distinguishes a weak entity type from a strong entity type?

<p>A weak entity type cannot be uniquely identified by its attributes alone and requires a foreign key from a strong entity.</p> Signup and view all the answers

What is a one-to-many (1:*) binary relationship type?

<p>In a one-to-many relationship, a single instance of the parent entity can be associated with multiple instances of the child entity.</p> Signup and view all the answers

Explain the concept of a multi-valued attribute.

<p>A multi-valued attribute can hold multiple values for a single entity, unlike simple attributes which can hold only one.</p> Signup and view all the answers

What is a superclass/subclass relationship in a data model?

<p>A superclass/subclass relationship establishes a hierarchy where the subclass inherits attributes from the superclass while having its unique attributes.</p> Signup and view all the answers

How are composite attributes handled in strong entity types?

<p>Composite attributes are broken down into their constituent simple attributes when creating relations for strong entities.</p> Signup and view all the answers

What does it mean for a Client entity to have partial participation in a 1:1 relationship?

<p>It means that not every client specifies preferences, leading the Client entity to be the parent and the Preference entity to be the child.</p> Signup and view all the answers

Why is the foreign key in the Preference relation also considered its primary key?

<p>Because the foreign key attribute from the Client relation is essential for uniquely identifying records in the Preference relation.</p> Signup and view all the answers

In a 1:1 relationship with optional participation on both sides, how is the designation of parent and child entities determined?

<p>The designation is arbitrary unless additional information clarifies the relationship.</p> Signup and view all the answers

What should be done after new primary keys or candidate keys are formed in the design process?

<p>Any new primary keys or candidate keys should be identified and the data dictionary should be updated accordingly.</p> Signup and view all the answers

In the 1:1 Staff Uses Car relationship context, when is the designation of parent and child entities arbitrary?

<p>The designation is arbitrary when there is no additional information to guide the decision on which entity is parent or child.</p> Signup and view all the answers

Why might cars be more frequently used by staff in the 1:1 Staff Uses Car relationship?

<p>This implies that while many cars are utilized by staff, not all staff members use cars, indicating a one-to-many dynamic within the relationship.</p> Signup and view all the answers

What role does the data dictionary play after forming relationships in database design?

<p>The data dictionary serves as a reference to maintain the accuracy and integrity of the database after identifying new keys.</p> Signup and view all the answers

In scenarios with a 1:1 relationship and partial participation, how should the database handle clients without specified preferences?

<p>The database should allow for clients to exist without corresponding entries in the Preference relation.</p> Signup and view all the answers

What is the purpose of establishing referential integrity constraints in a database?

<p>To ensure that relationships between tables are maintained correctly and to prevent orphaned records.</p> Signup and view all the answers

What term is used to describe a diagram that shows all merged local logical data models?

<p>Global relation diagram.</p> Signup and view all the answers

Why is it important to resolve conflicts with users during the database design process?

<p>To ensure that the database meets user needs and to prevent future issues in data management.</p> Signup and view all the answers

What should be updated to reflect changes made in the global data model?

<p>The documentation.</p> Signup and view all the answers

What distinguishes a global ER diagram from a global relation diagram?

<p>A global ER diagram is based on local ER diagrams, while a global relation diagram focuses on merged relations.</p> Signup and view all the answers

What could cause considerable confusion later in the database lifecycle?

<p>Out-of-date documentation.</p> Signup and view all the answers

What is the significance of primary keys in a global relation diagram?

<p>They uniquely identify records within a table, ensuring data integrity.</p> Signup and view all the answers

What action should be taken if changes occur during database implementation?

<p>Update the documentation simultaneously with the model changes.</p> Signup and view all the answers

What is the significance of merging relationships and foreign keys in local data models?

<p>Merging relationships and foreign keys ensures consistency and integrity across data models, allowing for a unified global model.</p> Signup and view all the answers

Describe the process of merging foreign keys with the same name and purpose.

<p>Foreign keys with the same name and purpose can be directly merged into the global model, simplifying the data structure.</p> Signup and view all the answers

Explain the difference between the Registers relationship in the StaffClient and Branch user views.

<p>In the StaffClient views, the Registers relationship models a staff member registering a client, while in the Branch views, it involves registering a client at a specific branch.</p> Signup and view all the answers

What role do multiplicity constraints play in merging relationships?

<p>Multiplicity constraints help identify conflicts in relationships, ensuring that merged elements accurately reflect the intended data interactions.</p> Signup and view all the answers

Why is it important to resolve conflicts before merging relationships?

<p>Resolving conflicts ensures that the merged data accurately represents all user views without any discrepancies or loss of information.</p> Signup and view all the answers

What happens to the Registers relationship from the StaffClient user views during merging?

<p>The Registers relationship from the StaffClient user views is ignored in favor of equivalent relationships from the Branch user views.</p> Signup and view all the answers

How can relationships/foreign keys with different names but the same purpose be merged?

<p>These relationships can be merged by analyzing their functionalities and aligning them under a common naming convention.</p> Signup and view all the answers

What is the outcome of ignoring conflicting relationships in user views?

<p>Ignoring conflicting relationships allows for a more streamlined model, eliminating redundancy and potential errors.</p> Signup and view all the answers

What is the primary goal of validating the global logical data model?

<p>The primary goal is to ensure the relations created support the required transactions and to validate through normalization.</p> Signup and view all the answers

In the validation process, what areas should be checked?

<p>Only the areas of the model that resulted in changes during the merging process should be checked.</p> Signup and view all the answers

Why is it necessary to review the global logical data model with users?

<p>It is necessary to ensure that the model accurately represents the data requirements of the enterprise as perceived by users.</p> Signup and view all the answers

What distinction disappears after merging local data models into the global data model?

<p>The distinction between local logical data models and the global logical data model is no longer necessary.</p> Signup and view all the answers

What is assessed to check for future growth in the logical data model?

<p>The assessment includes determining significant changes likely in the foreseeable future and whether the model can accommodate them.</p> Signup and view all the answers

What does the conclusion of logical database design involve?

<p>It involves evaluating the logical data model's capability to be extended for future developments.</p> Signup and view all the answers

How does normalization contribute to the validation process of the global logical data model?

<p>Normalization ensures that the relations created are structured to reduce redundancy and improve data integrity.</p> Signup and view all the answers

What document should accompany the global logical data model during the review with users?

<p>Documentation describing the model should accompany it during the review.</p> Signup and view all the answers

Flashcards

Derive relations for logical data model

The process of creating a set of relations (relational schema) from a conceptual data model.

Validate relations using normalization

Checking if a relational schema conforms to normalization rules, which ensure data consistency and efficiency.

Validate relations against user transactions

Verifying if the relations can handle the data operations (transactions) defined in the user's requirements.

Check integrity constraints

Examining the database for crucial rules that maintain data integrity (like ensuring all entries have values).

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Review logical data model with user

Getting feedback from users to verify if the logical data model accurately reflects their data needs.

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Merge logical data models into global data model

Combining several logical data models into a unified global data model.

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Check for future growth

Assessing the database's capacity for handling future data growth and changes.

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Logical Data Modeling Process

The process of creating a logical data model for a database, used to represent data structures and relationships.

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Parent Entity

The entity that posts a copy of its primary key into the relation that represents the child entity to act as a foreign key.

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Child Entity

The entity that receives a copy of the primary key from the parent entity as a foreign key.

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Referential Constraint

Identifies the entity the foreign key references and indicates its type.

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Foreign Key Resolution

A process where the foreign key is linked back to the primary key, allowing for data retrieval.

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Composite Key

A key that consists of multiple attributes.

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One-to-Many Relationship

A relationship where a single entity on one side can be linked to multiple entities on the other side.

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Derived Attribute

Attributes derived from other attributes, using calculation or logic.

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Recursive Relationship

A relationship that provides a link between the same type of entity.

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1:1 relationship with partial participation

A database design method where one entity (the parent) contains the 'primary key' that is replicated in another entity (the child) through a 'foreign key' to establish a one-to-one relationship.

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Foreign key in 1:1 relationship with partial participation

The primary key of the parent entity is copied and placed in the child entity to establish the one-to-one relationship.

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1:1 relationship with optional participation on both sides

A situation where both entities in a one-to-one relationship have optional participation, meaning neither entity is required to have a counterpart in the relationship.

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Arbitrary parent-child designation

The decision of which entity to designate as the parent and which as the child is arbitrary in a 1:1 relationship with optional participation on both sides, unless further information is available.

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Identifying new primary keys or candidate keys

The process of identifying and updating the primary keys and candidate keys in a database schema after the foreign key has been established in a relationship.

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Updating data dictionary

A process where primary keys and candidate keys are updated in a data dictionary after the foreign key has been established.

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Global Data Model

The process of combining individual local logical data models into a single, comprehensive model, representing the data for the entire system.

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Global Relation Diagram

A diagram representing the relationships between entities in a data model, including primary and foreign keys.

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Referential Integrity Constraints

Constraints that enforce relationships between tables, ensuring data integrity by preventing inconsistent data.

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Data Model Documentation

The process of documenting the design and changes made to the global data model.

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ER Diagram (Entity-Relationship Diagram)

A diagram that graphically represents the entities and relationships in a data model.

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Relational Model

A database design approach that focuses on organizing data into logical tables with defined relationships.

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Data Integrity

The process of ensuring that data is consistent and accurate across the entire database.

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Logical Database Design

A process of carefully designing a database to meet the specific needs of a particular application.

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Merging Relationships/Foreign Keys

The process of combining relationships and foreign keys from multiple data models into a single, global model.

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Relationships with Same Name and Purpose

These are relationships that have the same name and purpose, even if they come from different data models.

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Relationships with Different Names but Same Purpose

This refers to relationships that have different names but perform the same function.

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Relationships with Different Names and Purposes

These are relationships that have different names and purposes, and therefore, may not be merged.

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Resolving Conflicts

The process of identifying and resolving conflicts between relationships and foreign keys from different data models.

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Registers Relationship

A type of relationship used to represent the action of registering a client, where the relationship models the event of a staff member registering a client.

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Registration Relationship

This is a new type of relationship that represents a member of staff registering a client at a specific branch. It was created to address the complexities of modeling branches in the data model.

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Ignoring the 'Registers' Relationship

The process of ignoring relationships like 'Registers' from the StaffClient user views and instead incorporating the equivalent relationships/foreign keys from the Branch user views into the global model.

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Validate Global Logical Data Model

Ensuring that the relationships within the global logical data model are structured correctly and can accommodate all necessary transactions.

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Review Global Logical Data Model with Users

Reviewing the combined logical data model with users to confirm its accuracy in representing the enterprise's data needs.

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Merging Local Logical Data Models

The process of combining individual local logical data models into a single, comprehensive model for the entire enterprise.

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Local Logical Data Model

A detailed representation of data relationships and requirements for a specific user or department within an organization.

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Global Logical Data Model

A detailed representation of data relationships and requirements for the entire enterprise.

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Validate Local Logical Data Model

Ensuring that the relationships within a local logical data model are structured correctly and can accommodate all necessary transactions.

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Normalization (database design)

The process of organizing data into tables with specific relationships, ensuring data integrity and efficiency.

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Study Notes

Methodology-Logical Database Design

  • This chapter describes Step 2 of the database design methodology, translating the conceptual data model into a logical data model.
  • The goal is to create an accurate representation of the enterprise's data requirements.
  • The process includes: deriving relations, validating relations using normalization, validating against transactions, checking integrity constraints and merging local models into a global one (optional).
  • A local logical data model represents the data needs of one or more user groups.
  • A global logical data model depicts the needs of all.

Building a Logical Data Model

  • Objective: Translate the conceptual data model into a logical data model that is structurally correct and supports required transactions.
  • Activities:
    • Derive relations for the logical data model.
    • Validate the relations using normalization.
    • Validate relations against user transactions.
    • Verify integrity constraints.
    • Review the logical data model with users.
    • Merge local data models into a global model (optional).
    • Check for future growth considerations.

Deriving Relations for the Logical Data Model

  • Relations (tables) are created based on entities, relationships, and attributes from the conceptual model.
  • Relation names and attributes are defined, along with primary and foreign keys.
  • Functional dependencies are used, showing relationships between the attributes in the relations
  • Includes strong entity relationships, weak entity types, one-to-many or one-to-one binary relationships (recursive or not), and complex relationships.
  • Any multi-valued attributes are also defined as separate relations.

Validating Relations Using Normalization

  • Data redundancy in relations is reduced through normalization techniques (e.g., 1NF, 2NF, 3NF).
  • Ensuring no update anomalies.
  • Identifies functional dependencies.

Validating Relations Against User Transactions

  • The relations are tested against user transactions to confirm they support the required operations from the requirements specifications.
  • Manual testing is often performed to check if any issues occur.

Checking Integrity Constraints

  • Data integrity constraints are checked and added to the logical model, including constraints for required data, attribute domains, multiplicity, entity integrity and referential integrity.
  • Ensure the model protects against incorrect or inconsistent data.

Reviewing the Logical Data Model with Users

  • The logical data model is reviewed with users to ensure they find it accurate and complete with regards to the requirements.

Merging Local Data Models into a Global Model

  • This involves integrating multiple local logical models into a single global model if the database system has multiple user views that are managed by the user views approach.

Checking for Future Growth

  • Evaluating the logical data model's ability to adapt to potential future developments is assessed to ensure its extensibility and scalability.

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