The document discusses the relational data model and databases. It describes advantages of databases such as data consistency, security, faster application development, and backup/recovery capabilities. It also outlines the evolution of database systems from flat files to relational, object-oriented, and data warehousing approaches. Key concepts covered include data models, schemas, and database states.

1. Lecture 02
The Relational Data Model

2. Advantages of Database

3. Advantages of Database
• Data Consistency
• Better Data Security
• Faster Application Development
• Economy of Scale
• Better Concurrency Control
• Better Backup and Recovery Facility

4. The Range of
Database Applications
• Personal Database – standalone desktop database
• Workgroup Database – local area network (<25 users)
• Department Database – local area network (25-100 users)
• Enterprise Database – wide-area network (hundreds or thousands of
users)

5. Evolution of DB Systems
• Flat files - 1960s - 1980s
• Hierarchical – 1970s - 1990s
• Network – 1970s - 1990s
• Relational – 1980s - present
• Object-oriented – 1990s - present
• Object-relational – 1990s - present
• Data warehousing – 1980s - present
• Web-enabled – 1990s - present

6. Models, Schemas and States
• A data model defines the constructs
available for defining a schema
– defines possible schemas
• A schema defines the constructs
available for storing the data
– defines database structure
– limits the possible database states
• A database state (or instance) is all
the data at some point in time
 the database content

7. Models, Schemas and States
• data model
– fixed by the DBMS
– Defined by DB designer
• schema
– defined by the DB designer
– generally fixed once defined *
• database state
– changes over time due to user updates
* schema modifications are possible once the database
is populated, but this generally causes difficulties

8. RELATION SCHEMAS
AND
RELATION INSTANCES

9. Relation Schemas
• A relation is defined by
a name and
a set of attributes
• Each attribute has a name and a domain
– a domain is a set of possible values
– all domains are sets of atomic values
– RDM does not recommend complex data types
– domains may contain a special null value

11. Definition: Relation Schema
• Relation Schema
R(A1, A2, … , An)
– R is the relation name
– A1 … An are the attribute names
• Domains are denoted by
dom(Ai)
• degree = the number of attributes

12. Characteristics of Relations
• A relation is a set
– tuples are unordered
– no duplicate tuples
• Attribute values within tuples are ordered
– values are matched to attributes by position

13. Characteristics of Relations
• Values in tuples are atomic
• Each Column has distinct name
• The values of the attribute come from the same domain
• The order of the column is immaterial
• Each row/tuple/record is distinct

14. SQL: Relation States
• A relation is viewed as a table
• The attributes define the columns of the table
• Each row in the table holds related
values for each attribute
– a row often represents a conceptual entity (object)
• Values in each column must come
from the domain of the attribute

15. Example Schema