Chapter 2 Flashcards

(31 cards)

1
Q

Discuss data modeling and why data models are important

A

Data modeling is the first step in designing a database, creating a specific data model for a defined problem domain. A data model is a simplified graphical representation of complex real-world data structures, helping understand complexities. It serves as a blueprint combining narrative and diagrams, guiding database construction to meet user needs. Data models facilitate communication among designers, programmers, and users, offering a comprehensive view like blueprints for a house. Without them, conflicting data schemes and design issues arise.

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2
Q

What is a problem domain in data modeling?

A

A problem domain is a clearly defined area within the real-world environment with specific scope and boundaries addressed systematically by the data model.

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3
Q

Why is data modeling considered an iterative process?

A

Data modeling starts with a simple understanding of the problem domain and increases in detail progressively as understanding improves, refining the model over time.

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4
Q

How do data models help different stakeholders in an organization?

A

Data models facilitate interaction among designers, programmers, and end users by providing a common understanding of data, accommodating different views such as enterprise-wide or department-specific.

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5
Q

Describe the analogy comparing data models to the ‘view of the whole elephant’.

A

Just as blind people touch parts of an elephant and see only partial views, different users see partial data views. A data model provides an overall ‘blueprint’ to unify these perspectives for consistent database design.

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6
Q

What are the basic data-modeling building blocks?

A

Entities, Attributes, Relationships, and Constraints.

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7
Q

What is an entity in data modeling?

A

An entity is a person, place, thing, concept, or event about which data is collected; each entity occurrence is unique.

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8
Q

Give examples of entities.

A

Examples include CUSTOMER, flight routes, or any distinguishable real-world object or abstraction.

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9
Q

What is an attribute?

A

An attribute is a characteristic or property of an entity, like customer last name or phone number.

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10
Q

What is a relationship in data modeling?

A

A relationship describes an association among entities, such as between customers and agents.

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11
Q

What are the types of relationships?

A

One-to-many (1:M), Many-to-many (M:N), and One-to-one (1:1).

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12
Q

What is a constraint in data modeling?

A

A constraint is a restriction on data to ensure integrity, such as a GPA being between 0.00 and 4.00.

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13
Q

What are business rules in database design?

A

Business rules are brief, precise, and unambiguous descriptions of policies or procedures that govern an organization’s operations and influence database design.

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14
Q

How do business rules influence database design?

A

They define entities, attributes, relationships, and constraints in the data model, ensuring the model reflects the organization’s operations accurately.

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15
Q

What are main sources for business rules?

A

Company managers, policy makers, department managers, written documentation, and direct interviews with end users.

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16
Q

Why is identifying business rules essential?

A

They standardize the company’s data view, aid communication, clarify data roles, and help develop accurate relationship rules and constraints.

17
Q

How are business rules translated into data models?

A

By identifying nouns as entities and verbs as relationships, and by determining relationship cardinality through questions about instance associations.

18
Q

Outline the evolution of major data models.

A

Hierarchical (1960s), Network, Relational (1970s), Entity Relationship Model (ERM), and Object-Oriented Data Model (OODM).

19
Q

What characterizes the Hierarchical Model?

A

An upside-down tree structure representing one-to-many relationships, with each child having only one parent.

20
Q

How does the Network Model differ from the Hierarchical Model?

A

Allows records to have multiple parents, supports schema, DML, and DDL, but lacks ad hoc queries and data independence.

21
Q

What was the significance of the Relational Model?

A

Introduced the table (relation) concept, focusing on logical data representation, supporting structural and data independence, and implemented via RDBMS and SQL.

22
Q

What is the Entity Relationship Model (ERM)?

A

A data modeling standard using entities, attributes, and relationships represented graphically as ER diagrams.

23
Q

What is the Object-Oriented Data Model (OODM)?

A

A model combining data and relationships within objects, including operations and inheritance, usually depicted with UML diagrams.

24
Q

What are emerging alternative data models?

A

XML Databases, Big Data approaches, and NoSQL databases.

25
Why did XML databases emerge?
To manage large amounts of unstructured data in native XML format due to widespread use of XML for data exchange.
26
What challenges does Big Data address?
Rapid data growth, performance, scalability, and low-cost management of huge volumes of sensor and web-generated data.
27
What are NoSQL databases?
Databases designed for handling very large volumes, varied data types, and high-velocity operations beyond relational model capabilities.
28
How can data models be classified by abstraction levels?
External Model (user view), Conceptual Model (global organizational view), Internal Model (DBMS-specific representation), and Physical Model.
29
What is the External Model in data modeling?
The end users’ view, showing relevant data subsets for specific business units, helping ensure security and simplifying application development.
30
What is the Conceptual Model?
A global view integrating all external views into one, independent of software and hardware, usually represented by ER diagrams.
31
What is the Internal Model?
The representation of the database tailored to the selected DBMS, mapping the conceptual model to DBMS-specific details.