Data Models

Question 1

What is Data modeling

Answer 1

the process of creating a specific
data model for a determined problem domain.

A representation, usually graphic, of a
complex “real-world” data structure.

Question 2

4 importance of Data modelling and explain.

Answer 2

• Communication tools: allows interaction between designers, programmers and end users
• enhanced organizational understanding: gain new insights into how different components of a business interconnect
• Diverse views on data: allows different level of business to view data differently based on their roles

-holistic view: gives a blueprint of the model.

Question 3

Attribute

Answer 3

A characteristic of an
entity or object.

(column)

Question 4

relationship

Answer 4

Association between entities

Question 5

types of relationships

Answer 5

One to one ( 1:1)
One to Many (1:M)
Many to Many (M:N)

Question 6

Define business rules?

Answer 6

Brief, precise and unambiguous description of a policy, procedure or principle within a specific organization.

Question 7

What does business rules help with?

Answer 7

It helps establish entities, attributes and constraints for our model.

It allows the designer to understand the scope of the data and procedures of the business to create and appropriate model.

Question 8

in business rules, nouns and verbs can translate into which data model components?

Answer 8

Noun - entity
Verb - relationship

Question 9

What are Network models

Answer 9

Models which represent complex data through a collection of records in 1:M relationships.

• improve database performance
• more effective than Hierarchical models.

Question 10

Who introduced the relational model

Answer 10

E.F. Codd in 1970

Question 11

Desc the relational model

Answer 11

Relation -> Table
Contains tuples (rows) and attributes (cols).

-great idea but huge demand computationally.

Question 12

pros of relational model

Answer 12

Performs the same functions as the Network and
Hierarchical Models, but makes it easier to implement and understnand

• Hides complexity from user.

Question 13

what are the 3 things that a SQL - RDBMS consists of?

Answer 13

• End-user interface
• Collection of tables stored in the database
• SQL engine (handles all the queries)

Question 14

Crows foot notation

Answer 14

graphical representation of entity relationship diagrams (ERDs)

lines, unlike chen which got diamond shape between entities.

Question 15

Explain the Object- Oriented Model.

Answer 15

• Both data and its relationships are contained in single structures (objects)
• objects with similar characteristics are grouped in classes.
• typically depicted in Unified Modeling language (UML) class diagrams

Question 16

explain class hierarchy and inheritance in the OO model.

Answer 16

• classes are organized in a class hierarchy. objects within the class hierarchy can inherit the attributes and methods of those above it.

Question 17

Extended relational data model

Answer 17

Allows many of OO features such as objects. Better suited for business applications.

Question 18

Characteristics of Big Data databases.

Answer 18

Volume: amount of data

Velocity: speed which data grows and is processed

Variety: The different data formats which data is collected in.

Question 19

Relational approach problem with big data challenges.

Answer 19

Doesnt always match the needs of big data.

e.g. Its not always possible to fit unstructured data into tables.

Question 20

Solutions to Big data related problems

Answer 20

• Apache Hadoop
• Hortonworks Data Platform
• Vertica Advanced Analytics Platform
• NoSQL

Question 21

Apache Hadoop

Answer 21

• large-scale data processing,
• unstructured or semi-structured data.
• ideal when cost-effective storage and batch processing are key considerations.

Question 22

Hortonworks Data Platform

Answer 22

• managing big data within the Apache Hadoop ecosystem.
• governance, security, and operations alongside Hadoop.

Question 23

Vertica Advanced Analytics Platform

Answer 23

• Excels in high-performance,
• advanced analytics on massive volumes of data.
• It’s optimal for use cases requiring fast query performance on large, structured data sets.

Question 24

NoSQL:

Answer 24

• scenarios requiring high scalability and flexibility,
• particularly when working with unstructured or rapidly changing data.
• Ideal for web applications, real-time analytics, and handling large volumes of data with varying
  structures.

Question 25

4 Degrees of Data Abstraction

Answer 25

• External
• Conceptual
• Internal
• Physical

Question 26

External model

Answer 26

View from the end user.
(ERD)

Question 27

Advantages of the External model

Answer 27

• easy to identify specific date requited for business
• helps ensure security constraints in the database design.

Question 28

Conceptual Model

Answer 28

represents a global view of the entire database. Integrates all the external views.

Question 29

Advantages of the Conceptual Model

Answer 29

Provides a bird’s eye view of the data.

• it is also independent of both the software and hardware.

Question 30

Internal model

Answer 30

The representation of the database as seen by the DBMS.
- expressed using SQL
- Dependent on software but not on the hardware.

• also has logical independence which means a change in the internal model doesnt affect the conceptual model.

Question 31

Physical view

Answer 31

requires the definition of both the physical storage and the physical access methods to retrieve data.

• software and hardware dependent
• physical independence: changes in the physical model does not affect the internal.