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What is the first step in deriving relations for a logical data model?
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?
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?
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?
What is checked during Step 2.3 related to user transactions?
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What happens in Step 2.5 of the logical data model process?
What happens in Step 2.5 of the logical data model process?
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What is the optional step of merging distributed user views in the logical data model called?
What is the optional step of merging distributed user views in the logical data model called?
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What should be checked regarding future growth in Step 2?
What should be checked regarding future growth in Step 2?
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Why is Step 2.6 not necessary for certain database designs?
Why is Step 2.6 not necessary for certain database designs?
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What is the role of a foreign key in a relational database?
What is the role of a foreign key in a relational database?
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How do you determine which entity is the parent and which is the child in a relationship?
How do you determine which entity is the parent and which is the child in a relationship?
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Describe a strong entity type in the context of a conceptual data model.
Describe a strong entity type in the context of a conceptual data model.
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What distinguishes a weak entity type from a strong entity type?
What distinguishes a weak entity type from a strong entity type?
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What is a one-to-many (1:*) binary relationship type?
What is a one-to-many (1:*) binary relationship type?
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Explain the concept of a multi-valued attribute.
Explain the concept of a multi-valued attribute.
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What is a superclass/subclass relationship in a data model?
What is a superclass/subclass relationship in a data model?
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How are composite attributes handled in strong entity types?
How are composite attributes handled in strong entity types?
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What does it mean for a Client entity to have partial participation in a 1:1 relationship?
What does it mean for a Client entity to have partial participation in a 1:1 relationship?
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Why is the foreign key in the Preference relation also considered its primary key?
Why is the foreign key in the Preference relation also considered its primary key?
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In a 1:1 relationship with optional participation on both sides, how is the designation of parent and child entities determined?
In a 1:1 relationship with optional participation on both sides, how is the designation of parent and child entities determined?
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What should be done after new primary keys or candidate keys are formed in the design process?
What should be done after new primary keys or candidate keys are formed in the design process?
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In the 1:1 Staff Uses Car relationship context, when is the designation of parent and child entities arbitrary?
In the 1:1 Staff Uses Car relationship context, when is the designation of parent and child entities arbitrary?
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Why might cars be more frequently used by staff in the 1:1 Staff Uses Car relationship?
Why might cars be more frequently used by staff in the 1:1 Staff Uses Car relationship?
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What role does the data dictionary play after forming relationships in database design?
What role does the data dictionary play after forming relationships in database design?
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In scenarios with a 1:1 relationship and partial participation, how should the database handle clients without specified preferences?
In scenarios with a 1:1 relationship and partial participation, how should the database handle clients without specified preferences?
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What is the purpose of establishing referential integrity constraints in a database?
What is the purpose of establishing referential integrity constraints in a database?
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What term is used to describe a diagram that shows all merged local logical data models?
What term is used to describe a diagram that shows all merged local logical data models?
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Why is it important to resolve conflicts with users during the database design process?
Why is it important to resolve conflicts with users during the database design process?
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What should be updated to reflect changes made in the global data model?
What should be updated to reflect changes made in the global data model?
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What distinguishes a global ER diagram from a global relation diagram?
What distinguishes a global ER diagram from a global relation diagram?
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What could cause considerable confusion later in the database lifecycle?
What could cause considerable confusion later in the database lifecycle?
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What is the significance of primary keys in a global relation diagram?
What is the significance of primary keys in a global relation diagram?
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What action should be taken if changes occur during database implementation?
What action should be taken if changes occur during database implementation?
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What is the significance of merging relationships and foreign keys in local data models?
What is the significance of merging relationships and foreign keys in local data models?
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Describe the process of merging foreign keys with the same name and purpose.
Describe the process of merging foreign keys with the same name and purpose.
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Explain the difference between the Registers relationship in the StaffClient and Branch user views.
Explain the difference between the Registers relationship in the StaffClient and Branch user views.
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What role do multiplicity constraints play in merging relationships?
What role do multiplicity constraints play in merging relationships?
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Why is it important to resolve conflicts before merging relationships?
Why is it important to resolve conflicts before merging relationships?
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What happens to the Registers relationship from the StaffClient user views during merging?
What happens to the Registers relationship from the StaffClient user views during merging?
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How can relationships/foreign keys with different names but the same purpose be merged?
How can relationships/foreign keys with different names but the same purpose be merged?
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What is the outcome of ignoring conflicting relationships in user views?
What is the outcome of ignoring conflicting relationships in user views?
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What is the primary goal of validating the global logical data model?
What is the primary goal of validating the global logical data model?
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In the validation process, what areas should be checked?
In the validation process, what areas should be checked?
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Why is it necessary to review the global logical data model with users?
Why is it necessary to review the global logical data model with users?
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What distinction disappears after merging local data models into the global data model?
What distinction disappears after merging local data models into the global data model?
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What is assessed to check for future growth in the logical data model?
What is assessed to check for future growth in the logical data model?
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What does the conclusion of logical database design involve?
What does the conclusion of logical database design involve?
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How does normalization contribute to the validation process of the global logical data model?
How does normalization contribute to the validation process of the global logical data model?
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What document should accompany the global logical data model during the review with users?
What document should accompany the global logical data model during the review with users?
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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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Description
This quiz focuses on Step 2 of the database design methodology, which involves translating a conceptual data model into a logical one. Key activities include deriving relations, normalizing data, validating transactions, and ensuring integrity constraints. Dive into the details of creating accurate logical representations for enterprise data needs.