supplement 01 (a)database-introduction-1 supplement 01a database-introduction-1 hsq - databases...

Supplement 01 (a) Database-Introduction-1

Supplement 01aDatabase-Introduction-1

HSQ - DATABASES & SQL

And Franchise Colleges

By MANSHA NAWAZ


Why Database Systems?• Data is one of the most important resources in ALL

organisations. Without data it is not possible to operate.• Control manufacturing processes?• Process sales of goods?• Diagnose patients’ illnesses?• Forecast sales?• Run the University of Teesside?

• To be useful data must be processed into information. It must be:

• Accurate• Timely• Relevant

• Therefore, you need adequate facilities for storing data and processing information:– Storing (and verifying) data– Manipulating data– Extracting data


File - based approach

ApplicationData Department

Stock Control

Production

Accounts

Part No, Supplier, qtylocation, reorder qty

Stores

Operations

Finance

Part#, qty, Assy#,Machine#, Cert.#:

Supplier, Part#, Part#, Cost, Qty

• From the earliest days computers were used to store files of data. • Separate systems, ie separate files and programs, were developed for each

application, eg stock files, production files, accounts files, etc.• Applications processed the data to provide information.

Problems

Inconsistency

Redundancy

Lack of integration

Lack of control


Database approach

Application

Database

Supplier, Supplier Pt No:, Part No:

Cost, Qty ordered, Qty del., qty, Assy No:,

Machine No:, Cert. No: location, reorder qty

Database Management

SystemDBMS

Stock Control

Production

Accounts

Department

• DBMS is the environment used to manage a database• The database consisting of stored data and processed information for a system

• Data are organised into a single set of underlying TABLES from which the applications draw the data to provide information that are relevant to them.


E-R Model NF

Systems Analysis & Design DFD DataStores, DataFlows and Data Dictionary

DBMS

PHYSICAL VIEW OF DATATABLES

LOGICAL VIEW OF DATAFORMS

DATA MODEL

TABLE SET

Database connectivity via websites

www .net technologyMacromedia Dreamweaver

MS Visual Studio

Database connectivity via desktop DBMS such as

MS Access

Database connectivity via programming

languages such as MS Visual Basic

Area of Interest

Database Development


Client/Server Architecture

User Workstation

User Workstation

OperatorWorkstation

DepartmentFile-Servers

Corporate Servers

• Server provides services for the Clients which are responsible for interacting with the users (Input/Output)

• Server is responsible for performing a service (e.g. transaction) and guaranteeing the integrity of the data

• Well suited for distributed systems handling large amounts of data


System Development Overview• Systems development undertaken by using Case Tools

– used early in development life cycle – Provide requirements and design in terms of Systems Model and Data Model

• Case Tools for Systems Modelling:– Dataflow Diagrams (DFD)– Data Dictionary (DD)

• Case Tools for Data Modelling:– Normalisation (NF) – A rules based technique undertaken to produce the data model for a system– Entity Relationship Model (ER) – A diagrammatic based technique undertaken to produce the data model for a system – DFD & DD provide us with the base for a ERD Data Model

• Data Model – Can be implemented on a DBMS such as MS SQL Server, MS Access, etc– Consists of logical and physical view of the proposed systems data.

• DBMS – implementation platform – Database Management System such as MS SQL Server 2000 (MS Access)


• MS SQL Server is a server based database.

• Multi User – Multi Platform Systems

• Large, high volume traffic database systems

• Server holds database. Workstation provides access.

• For web or database systems if the access traffic is likely

to generate more than 20 concurrent database hits at a

time, it's time to move to a database server

• Generally, database servers like MS SQL Server are the

way to go for database or web/database systems

• Many and wide ranging user base for system

• Additional Security and Login features

• MySQL (free sql database used for connectivity to Websites via

PHP).

MS SQL Server V MS Access• MS Access is

Desktop based

• Small, low-traffic database systems

• Small, low-traffic web sites requiring database connectivity.

• Cannot handle heavy traffic from multiple users.


Advantages of the Database Approach

• No unnecessary duplication of data.• Greater consistency of data.• Wider availability of data.• Greater flexibility of use of data.• Improved data integrity.• Improved security.• Improved backup and recovery services.• Can change the data structure without altering associated

programs.• A database is dynamic: it can grow and change.• Data management can be more consistent and systematic.


Databases• “A shared collection of logically related data, and a

description of this data, designed to meet the information needs of an organisation.”‘Database Systems’ by Connolly & Begg Addison-Wesley, ISBN 0-201-70857-4

• “A database system can be thought of as a computerised record-keeping system. Such a system involves the data itself (stored in the database), hardware, software and – most important! – users.

• … Databases are integrated and (usually) shared; they are used to store persistent data.”‘An Introduction to Database Systems’ by C J Date, Addison-Wesley, ISBN 0-201-

38590-2 (7th Edition, 2000)


DBMS

• “A software system that enables users to define, create, maintain, and control access to the database.”

• Provides the interface between the user and the data in the database.

• Allocates storage to data and maintains indices so that any required data can be retrieved.

• Protects data against unauthorised access.• Safeguards data against corruption.• Provides recovery and restart facilities after a hardware or

software failure.


• Also referred to as Conceptual Model– A Data Model provides a particular way of thinking about data, at least in terms of its structure – Data Models include data descriptions, data relationships, data semantics, consistency constraints [Silberschatz et. al.] – Data model comprises three components: data structures, data manipulators, and general integrity rules [Codd (1970)]

• A Data Model is implementation independent– Not aimed at any particular computer software or hardware.

• DBMS supports an implementation of one or more Data Models– What data model is supported by a Relational Database Management System (Access, SQL, Oracle, etc.)– A RDBMS may have extensions to support other models.

• At what stage in the Systems Development Lifecycle will data modelling take place (early, middle, late)?

Data Model


– Data Models produced early in Systems Development

– Makes improvements in terms of : • NO DUPLICATION or REDUNDANT or NULL INFORMATION• REDUCTION IN PHYSICAL SIZE• QUICKER INFORMATION RETRIVAL

• LEADS TO A FULLY OPTIMISED SET OF TABLES

– Data Model produced by Case Tools techniques • Normalisation

– Rule based technique for transfering logical datastore view to physical view

• Entity Relationship Modelling. – Diagrammatic representation of a proposed systems database requirements

– Data Model provides • a full set of related tables and data

• Able to derive physical views (internal schema) of data

• Able to derive logical views (external schema) of data

Data Model


• Provide us with a Bottom Up approach to producing the database tables

• Technique covered in other modules

• Supplement on Normalisation is provided on the DD website

Normalisation (NF)

Entity Relationship Modelling (ERM)

• A data modelling CASE Tool Technique of interest• A diagrammatic representation of a systems database tables• Top Down approach to data modelling• Entity Relationship Diagram (ERD) used to map data model • Applying rules, translate ERD into a set of well-normalised tables• Provides both logical and physical view of tables


– TABLES– DATA

– Internal Schema View – database structure view that a DBMS requires.– in terms of Tables, Attributes (data fields) and Types (data defn.)– linkage between tables via primary and foreign keys – All Datastores decomposed to a set of TABLES– Physical View – for Designers

PHYSICAL VIEW

– FORMS– INFORMATION

– External Schema View– Form or Screen views provided to the end user.– A set of FORMS derived from the TABLES– Logical View – for Users

LOGICAL VIEW


The Three Level ANSI-SPARC Architecture

• In 1975 the ANSI Standards Planning and Requirements Committee proposed a standard terminology and general architecture for database systems.

• The objective is to separate each user’s view of the database from the way it is physically represented. 3 levels or views of data within a database:

• External Level– The users’ view of the database. Also known as the applications view.

• Conceptual Level – The overall view of the database. Also known as the global view.

• Internal Level– The physical representation of the database on the computer. Also

known as the storage view.


Schemas

• The overall description of the database is called the database schema. There are 3 different types of schema in the database.

• External Schema– There are multiple external schemas (or subschemas), each one

corresponding to a different view of the data.• Conceptual Schema

– There is one conceptual schema, which describes the data stored in the database, the relationships and the integrity constraints.

• Internal Schema– There is one internal schema, which describes how the data are stored

in the database and how they are accessed.


Schemas and Views

Inventory

H R

Finance

Production

Customer Service

Conceptual

Internal

External

External


Mapping• Provides the translation between the schemas at different levels. The DBMS is responsible

for mapping between the 3 types of schema.

• The DBMS must ensure that each external schema is derivable from the conceptual schema.

• The DBMS must use the information in the conceptual schema to map between each external schema and the internal schema.


Data Independence

• A major objective for the 3-level architecture is to provide data independence, ie upper levels must be unaffected by changes to lower levels.

• There are 2 kinds of data independence:

• Logical data independence

– refers to the immunity of the external schemas to changes in the conceptual schema.

– It should be possible to alter tables, columns or relationships without having to alter existing external schemas or rewrite application programs (other than those that are directly affected).

• Physical data independence

– refers to the immunity of the conceptual schema to changes in the internal schema.

– It should be possible to alter file organizations, storage devices, indexes, etc, without having to alter the conceptual or external schemas.


The Systems Catalogue

• The database schema is defined using a special language called a Data Definition Language (DDL).

• The result of the compilation of the DDL statements is a set of tables stored in special files collectively called the system catalog.

• This is a repository of meta-data (data about data), ie information describing the data in the database, typically containing the name, description, source and usage information for each data item.

• The system catalog is also known as the data dictionary or the data directory.


Database Language

• A Data Definition Language (DDL) is used to specify the data in the database.

• A Data Manipulation Language (DML) is used to access the data.• A Data Control Language (DCL) is used to control access to the data.• Some databases have a combined DDL, DML and DCL (often called a

Query Language), eg SQL.


Database Types - 3 Main Data Models

• Each database uses a definition language

– imposes restrictions on • what can be defined• how entities relate to each other

Network model

Hierarchical model

Relational model


Database Types - Network

Part No:

Supplier Name

Supplier Part No:

Link File

Can show all 1:n relationships between records


Database Types - Hierarchical

Supplier Part No:Supplier CodeLocation

Electrical Steel Oils Fasteners

QuantitySupplier Name

STOCK

Part No:


Data Files STOCK ITEM

RECORD

STOCK ITEMSTOCK ITEMSTOCK ITEMFILE

FIELD(S)

Part No:

Colour

Weight

Description

QuantityReorder Qty

Location Supplier NameSupplier Code

Supplier Part No:

12345

N/A

98

F37

Cadmium Bar 90mm dia

74

FerrisF2

c801

12345

FIELD VALUESKEY FIELD

PRIMARYKEY

Database Types - Relational


Logical vs. Physical

STOCK ITEMSTOCK ITEMSTOCK ITEM

FIELD(S)

Part No:

Colour

Weight

Description

QuantityReorder Qty


Supplier Part No:

12345

N/A

98

F37


74

FerrisF2

c801

12345

FIELD VALUES

LOGICAL

PHYSICAL

Database Types - Relational


Relationships - 1:1


Part No:

Colour

Weight

Description

QuantityReorder Qty

LocationSupplier Code

12345

N/A

98

F37


74

FerrisF2

c801

12345

Supplier Name

Supplier Part No:


Relationships - 1:n


Part No:

Colour

Weight

Description

QuantityReorder Qty


12345

N/A

98

F37


74

FerrisF2

c801

12345

Supplier Part No:


Relationships - m:n


Part No:

Colour

Weight

Description

QuantityReorder Qty


12345

N/A

98

F37


74

FerrisF2

c801

12345

Supplier Part No:


Relational Model Technique

Future Lectures will cover the

Entity Relationship Diagrams (ERD’s)

supplement 01 (a)database-introduction-1 supplement 01a database-introduction-1 hsq - databases...

Documents

files of data

data extracting data

system data

data modelling

stored data

useful data

database systems

data model case tools