CIS 130 Quiz 4

The statement "Metadata is data about data" is true. Metadata provides information about the characteristics, attributes, and properties of data. It helps in understanding and managing data by providing details such as its source, format, structure, and context. Metadata plays a crucial role in organizing, categorizing, and retrieving data, making it easier to locate and use. By describing the content and structure of data, metadata enhances its usability, accuracy, and reliability.

An entity is indeed the basic building block for a data model. In database design, an entity represents a real-world object or concept, such as a person, place, or thing. It is used to define the structure and properties of the data that will be stored in the database. Entities are typically represented as tables in a relational database, with each row representing a specific instance of the entity. Therefore, the statement "An entity is the basic building block for a data model" is true.

When an Entity Relationship Diagram (ERD) becomes too complex, it can be difficult to understand and manage. In such cases, breaking down the ERD into related subject areas can help simplify the representation and make it more manageable. By dividing the ERD into smaller, more focused subject areas, it becomes easier to analyze and comprehend the relationships between entities and attributes. This approach also allows for better organization and documentation of the database design, making it easier to maintain and modify in the future.

ERD stands for Entity-Relationship Diagram, which is a visual representation of the relationships between entities in a database. It is true that ERDs can be quite complex and may involve a large number of entities. This is because databases can have numerous tables or entities, and each entity can have relationships with multiple other entities. Therefore, it is not uncommon for ERDs to be complex and include hundreds or even thousands of entities.

Data models can be either logical or physical. A logical data model represents the information requirements of an organization without considering how the data will be stored or implemented. It focuses on the relationships and attributes of the data entities. On the other hand, a physical data model represents how the data will be stored in a database system, including tables, columns, indexes, and constraints. Therefore, it is correct to say that data models can be either logical or physical.

The correct answer is "Entity Relationship Diagramming". An Entity Relationship Diagram (ERD) is a visual representation of the relationships between entities in a database. It helps to illustrate the structure of a database and the relationships between different entities such as tables, attributes, and their associations. This diagramming technique is widely used in database design and development to ensure data integrity and efficient data management.

Metadata refers to the information in the data dictionary. It provides a description and context for the data, including its structure, format, and meaning. Metadata helps users understand and interpret the data, making it easier to manage and analyze. It acts as a guide or reference for the data, allowing for efficient data storage, retrieval, and manipulation.

In ERD diagrams, a crow's foot is used to represent a one-to-many relationship. This symbol indicates that one entity instance is associated with multiple instances of another entity. Therefore, Mike should draw a crow's foot to identify the end of the one-to-many relationship in his ERD diagram.

The given statement is false because in an entity called STUDENT, it is unlikely to find the attribute of PROFESSOR-ID. The attributes mentioned, such as Last-Name, First-Name, and CLASSROOM, are commonly associated with a student entity. However, the attribute PROFESSOR-ID would typically be associated with a separate entity, such as PROFESSOR, to establish a relationship between the student and the professor. Therefore, the correct answer is false.

An analyst can read an ERD to discover the individual pieces of information in a system and understand how they are organized and related to each other. This includes identifying the different entities and their attributes, as well as the relationships between these entities. By examining the ERD, the analyst can gain insights into the data structure and understand how the information flows within the system. This knowledge is crucial for designing and optimizing the system's functionality and efficiency.

When normalizing data models, if you take attributes that have multiple values for a single instance of an entity and create separate entities for those attributes, you are moving from 0 normal form to 1st normal form (1NF). This is because in 0 normal form, the data is unorganized and may have repeating groups or multiple values in a single attribute. By creating separate entities for these attributes, you are ensuring that each attribute has only a single value for each instance of the entity, which is the requirement for 1NF.

The given statement is false. ERD's are not drawn in several levels as mentioned. ERD's typically consist of one main diagram that represents the entire system or database. There may be additional diagrams or views that provide more detail or focus on specific aspects, but they are not categorized into different levels like context, level 0, and level 1 ERD diagrams.

A classroom number would not likely be an attribute of a student because it is a characteristic of the physical space where students attend classes, rather than a characteristic of the student themselves. Attributes of a student typically include age, student identification number, home phone, and gender, as these are personal details that are directly related to the individual student.

A data model can be used as a logical data model in analysis and as a physical data model in design. This means that a data model can help in understanding and representing the structure and relationships of data in a system during the analysis phase, and also in designing the physical implementation of the data model during the design phase. It is a versatile tool that can be used in both stages of the system development process.

not-available-via-ai

A dependent entity is one that relies on the presence of another entity and is usually on the "many" end of a relationship or has an identifier that is based on another entity's attribute. This means that the dependent entity cannot exist independently and its existence is tied to the existence of another entity.

ERD's (Entity Relationship Diagrams) and DFD's (Data Flow Diagrams) are not two techniques for process modeling. ERD's are used for modeling the relationships between different entities in a database, while DFD's are used for modeling the flow of data within a system. They serve different purposes and are used in different stages of system development. Therefore, the correct answer is False.

A data model is a representation of the structure and relationships of data. It helps to organize and understand data. People, places, and things are all examples of entities that can be represented in a data model. However, actions are not typically represented directly in a data model. Actions are typically represented through relationships or attributes that describe the behavior or interactions between entities. Therefore, actions are not illustrated by a data model.

A zip code is not likely to be an entity on a car insurance ERD because it is not directly related to the car insurance process. The other entities listed (Customer, Policy, Agent, Car) are all directly involved in the car insurance process and have a direct relationship with each other. However, a zip code is more likely to be a attribute or a property of another entity, such as the Customer or Car entity, rather than being its own separate entity on the ERD.

In the process of creating basic ERD's, the last step is to identify relationships. This involves determining how different entities are related to each other and understanding the connections between them. By identifying relationships, we can establish the associations and dependencies between entities, which is crucial for designing an effective database structure. This step helps in organizing and visualizing the data model, enabling efficient data management and retrieval.

The correct answer is "Whether a child entity can exist with or without a related instance in the parent entity." Modality refers to the relationship between entities in a database. It determines whether a child entity can exist independently or if it is dependent on a parent entity. For example, in a customer-order relationship, the modality would determine if an order can exist without a customer (zero or optional modality) or if every order must be associated with a customer (one or mandatory modality).

Independent entities are entities that can exist on their own without the need for any other entity. They do not rely on any other entity for their existence or functioning. They have their own attributes and can perform their own operations without being dependent on any other entity.

ERD's (Entity Relationship Diagrams) and DFD's (Data Flow Diagrams) are indeed two techniques for data modeling. ERD's are used to represent the relationships between entities in a database, while DFD's are used to illustrate the flow of data within a system. Therefore, the given answer that ERD's and DFD's are two techniques for data modeling is correct.

The first step to building an Entity Relationship Diagram is to identify the entities. This is because entities are the fundamental building blocks of an ER diagram and represent real-world objects or concepts. By identifying the entities, we can then proceed to define the relationships between them, identify their attributes, and determine how they interact with other entities, processes, data flows, and data stores.

Logical data models are not most commonly drawn with the Data Flow Diagram (DFD) technique. Instead, DFDs are typically used to represent the flow of data within a system, focusing on processes, inputs, outputs, and data stores. Logical data models, on the other hand, are typically depicted using Entity-Relationship Diagrams (ERDs) or Unified Modeling Language (UML) class diagrams. These models focus on the structure and relationships of data entities, attributes, and constraints. Therefore, the statement that logical data models are most commonly drawn with the DFD technique is false.

A data model is a formal way of representing the data that are used and created by a business system. It provides a structured and organized representation of the data elements, their relationships, and the rules that govern them. This helps in understanding and documenting the data requirements of the system, ensuring data consistency and integrity, and facilitating communication between stakeholders. Data models can be represented using various techniques such as entity-relationship diagrams, UML diagrams, or data flow diagrams.

Data stores are not elements of an Entity Relationship Diagram (ERD). An ERD is a visual representation of the relationships between entities in a database. It includes entities, attributes, relationships, and cardinality. Data stores, on the other hand, represent where data is stored physically, such as databases or files, but they are not considered elements of an ERD.

Creating an entity relationship diagram is an iterative process, meaning that it involves repeated cycles of analysis, design, and refinement. This implies that the diagram is not created in a single step but rather through multiple iterations. Each iteration involves identifying entities, relationships, and attributes, analyzing and refining them, and combining them if necessary. Therefore, the process of creating an entity relationship diagram is not a one-time task but requires ongoing iterations to ensure accuracy and completeness.

An ERD, or Entity-Relationship Diagram, is a visual representation of the relationships between entities (such as tables) in a database. It does not depict how data and information are processed and transformed by a business system. Instead, it focuses on the structure and organization of the data within the system. Therefore, the given statement is false.

Relationships are not drawn with lines showing cardinality and plurality. Instead, lines are used to show the type of relationship between entities in a database diagram, such as one-to-one, one-to-many, or many-to-many. The lines do not represent cardinality or plurality directly. Therefore, the statement is false.

A process model does not illustrate the data used and created by a business system. Rather, a process model represents the flow of activities, tasks, and events within a system. The data used and created by a business system are typically represented by data models or data flow diagrams. Therefore, the given statement is false.

A data dictionary is a repository that stores information about entities, attributes, and relationships in an Entity Relationship Diagram (ERD). It provides a centralized location for documenting and managing metadata related to the database design. The data dictionary helps in maintaining consistency and accuracy in the database by providing a comprehensive view of the data elements and their definitions. It is an essential component of CASE (Computer-Aided Software Engineering) tools, which assist in the design and development of software systems.

The second normal form is being performed when the analyst is evaluating a data model to ensure that all fields in a record depend fully on the entire primary key. This form eliminates partial dependencies, meaning that each non-key attribute in a table is fully dependent on the entire primary key.

The system proposal document may not be a good resource for attributes because it typically focuses on high-level system requirements and goals, rather than specific data attributes. It may provide information about the overall system design and functionality, but may not provide detailed information about the specific attributes that need to be included in the ERD. Therefore, other sources such as the CASE tool, data flows from DFD's, requirements documents, and interviews with users may be more reliable and useful in identifying and defining attributes for the ERD.

An ERD diagram is a visual representation of the relationships between entities in a database. The three major parts of an ERD diagram are relationship, data flow, and entity. Relationships define how entities are connected or associated with each other. Data flow shows the flow of information between entities. Entities represent the objects or concepts in the database. Therefore, the correct answer is relationship, data flow, and entity.