Data Models, Schemas and Instances

Data Models, Schemas and Instances

Data Model is a collection of concepts that can be used to describe the structure of database. Structure of database means data types, relationships and constraints. In addition, most data model include a set of basic operations for specifying retrievals and modifications on the database. Data Model provides a means to achieve Data Abstraction. Data Abstraction is refers to the hiding of certain details of how the data are stored and maintained. With several levels of abstraction, the user’s view of the database is simplified and this leads to the improved understanding of data.
There are three levels of abstractions:

1. View level: The highest level of abstraction describes only part of the entire database. Many users will not be concerned with the large database. Instead, they need to access only a part of it so that view level abstraction is defined. There are many views for the same database.
2. Logical level: This level describes what data are stored in the whole database.
3. Physical level: The lowest level of abstraction describes how the data are actually stored.

Categories of Data Model


* High-level Conceptual Data models: Provide concepts that are close to the way people perceive data to present the data. Typical example of this type is entity – relationship model which use main concepts like entities, attributes, relationships. An entity represents real-world object such as an employee, a project. An entity has some attributes which represents properties of entity such as employee’s name, address, birthdate. A relationship represents association among entities for example a works on relationships between employee and project.

* Record-based Logical Data models: Provide concepts that can be understood by the user but not too far from the way data is stored in the computer. Three well-known data models of this type are relational data model, network data model and hierarchical data model.

o The Relational model represents data as relations. Here is an example of relational schema for the SUPERMARKET database


EMPS (ENAME, SALARY)
MANAGERS (ENAME)

DEPTS (DNAME, DEPT#)
SUPPLIERS (SNAME, SADDR)

ITEMS (INAME, ITEM#)
ORDERS (O#, DATE)

WORKS_IN (ENAME, DNAME)
MANAGES (ENAME, DNAME)

CARRIES (INAME, DNAME)
PLACED_BY (O#, CNAME)

CUSTOMERS(CNAME,CADDR,BALANCE)
INCLUDES (O#, INAME, QUANTITY)

SUPPLIES (SNAME, INAME, PRICES)

The Network model represents data as record types and also represents a limited type of one to many relationship, called set type. The figure below shows a schema in network model notation


Figure 4: Sample schema in network model

The Hierarchical model represent data as hierarchical tree structures. Each hierarchy represents a number of related records. Here is the schema in hierarchical model notation.



Figure 5: Sample schema in hierarchical model notation

Physical Data models: Provide concepts that describe how data is actually stored in the computer.


Database Instances and Schemas
The description of the database which is designed in the early stage and is not expected to change frequently is called the database schema. Database system have severals schemas.
Since information can be inserted to or deleted from database at anytime, database changes over time. At a particular moment, the collection of information stored in the database is called an instance of the database.

ANSI/SPARC Architecture (Three –level Architecture)
Three – level architecture for database system is proposed to archive the characteristics of the database approach. The goal of this architecture is separate the applications and the physical database so the actual details of how data is organized are hided from the users.



As we can see from above picture, there are three levels of schemas in the database architecture
External level:

* In this highest level, there exists a number of views which of is defined a part of the actual database.
* Each view is provided for a user or a group of users so that it helps in simplified the interaction between the user and system.

Conceptual level: Conceptual Schema in this level describes the logical structure of the whole database.

* The entire database is described using simple logical concepts such as objects, their properties or relationships. Thus the complexity of the implementation detail of the data with be hided from the users.

* Internal level: Internal Schema in this level describes how the data are actually stored, how to access the data.

Data Independence
Data Independence is the ability to modify the schema in one level without affecting the schema in the higher level.
There are two levels of data independence:

* Logical data independence is the ability to make change in the conceptual schema without causing a modify in the user views or application program.
* Physical data independence is the ability to make change in the internal schema without causing a modify in the conceptual schema or application program.

Physical data independence seem to be easier to achieve since the way the data is organized in the memory affect only the performance of the system. Meanwhile, the application program depends much on the logical structure of the data that they are access.

Database Language
Data Definition Language (DDL): This is used to define the conceptual and internal schemas for a database system.

* It is not procedural language, rather a language for describing the types of entities and relationships among them in terms of a particular data model.

* Data Manipulation Language (DML): This is used to manipulate the database, which typically include retrieval, insertion, deletion, and modification of the data.


Database Users
End users
People whose jobs require access to database for querying, updating and generating report.
An end users might by one of the following

* Naïve users who use the existing appication programs to perform their daily tasks
* Sophiticated users are who use their own way to access to the database. This mean they donot use the application program provided in the system. In stead, they might define their own application or describe their need directly in a query languages.
* Specialized users maintain the personal database by using ready –make program packages that provide easy-to-use menu.

Application Programmer
People implement specific application program to access to the stored data. This kind of user need to familiar with the DBMSs to accomplish their task.
Database Administrators
A person or a group of people in the organization who is responsible for authorizing the access to the database, monitoring its use and managing all the resource to support the use of the whole database system

Classification of Database Systems
The database management systems can be classified based on several criteria.

* Based on data model: The most popular data model in today commercial DBMSs is relational data model. Almost wellknown DBMSs like Oracle, MS SQL Server, DB2, MySQL are support this model. Other traditional models can be named hierarchical data model , network data model. In the recent year, we are getting familiar with object-oriented data model but this model has not had widespread use. Some examples of Object-oriented DBMSs are O2, ObjectStore or Jasmine.
* Based on number users we can have single user database system which support one user at a time or multiuser syste,s which support multiple users concurrently
* Based on the ways database is distributed we have centralized or distributed database system

o Centralized database system : Data in this kind of system is stored at a single site.
o Distributed database sytem: Actual database and DBMS software are distributed in various sites connected by a computer network.

Homogeneous distributed Database Systems
# Use the same DBMS software at multiple sites
# Data exchange between various sites can be handle easily
Heterogeneous distributed Database Systems
# Different sites might use differents DBMS softwares
# There is a software to support data exchange between sites

Figure 7: Centralized Database System



Figure 8: Distributed Database System




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