1. The Database Environment
Lecture 1

2. The database environment
To be able to function, an organisation needs information, e.g. list of books in a library, customer details in a retail business, specifications of cars and their components for a car manufacturer
Information may be defined as data represented in a meaningful form. Same data shown in different ways will provide different information to different viewers
A major requirement of any computer system is to store and retrieve data in a way that is meaningful to the end user – so the core of any Information System is data, which is to be transformed into information through data modelling

3. Definitions
Data: Meaningful facts, text, graphics, images, sound, video segments.
Database: An organized collection of logically related data.
Information: Data processed to be useful in decision making.
Metadata: Data that describes data.

4. Data in Context

5. Summarized data

6. Disadvantages of file processing systems
Still widely used today (e.g. for backup) but have the following problems:
Program-Data Dependence (see Fig.) – file descriptions are stored within each application that accesses file, so change to file structure requires changes to all file descriptions in all programs.
Data Redundancy (Duplication of data) – wasteful, inconsistent, loss of metadata integrity (same data has different names in different files, or same name may be used for different data in different files).
Limited Data Sharing – users have little opportunity to share data outside their own applications.
Lengthy Development Times – little opportunity to re-use previous development efforts.
Excessive Program Maintenance – factors above combine to create heavy maintenance load

7. Three file processing systems

8. Advantages of the database approach
Minimal Data Redundancy/Improved Consistency
Data Integration
Multiple Relationships

9. Database management system
A DBMS is a data storage and retrieval system which permits data to be stored non-redundantly while making it appear to the user as if the data is well-integrated.

10. Advantages of the database approach
Data Independence/Reduced Maintenance
Improved Data Sharing
Increased Application Development Productivity
Enforcement of Standards
Improved Data Quality (Constraints)
Better Data Accessibility/ Responsiveness
Security, Backup/Recovery, Concurrency

11. Costs and risks of the database approach
New, Specialized Personnel required
Installation Management Cost and Complexity
Conversion Costs
Need for Explicit Backup and Recovery
Organizational Conflict

12. Pine valley furniture company
We will be using this fictitious company as a case study
The company’s first step was to create an Enterprise Data Model (a model of the organisation that provides valuable information about how the organisation functions, as well as important constraints – it stresses the integration of data and processes by focussing on entities, relationships and business rules)
First make a list of all the high-level activities that support business activities

13. Pine valley furniture company
Enterprise data model is a graphical model that shows the high-level entities and the associations among them (see Fig.): An ENTITY-RELATIONSHIP DIAGRAM.
The three associations (relationships) are shown by lines connecting the entities
Each CUSTOMER places any number of ORDERS (conversely, each ORDER is placed by exactly one CUSTOMER)
Each ORDER contains any number of ORDER LINEs (conversely, each ORDER LINE is contained in exactly one ORDER)

14. Pine valley furniture company
Each PRODUCT has any number of ORDER LINES (conversely, each ORDER LINE is for exactly one PRODUCT)

15. Segment from enterprise data model

16. Tables Relational databases views all data in the form of tables
Following Figs. a and b shows four tables, Customer, Product, Order and OrderLine (the 4 entities shown in the previous ER diagram).
Each column represents an attribute, e.g. the Customer table has attributes ID, Name, Address..etc.
Relationships between entities are represented by values stored in columns of the corresponding tables, e.g. Customer_ID is an attribute of both the Customer table and the Order table. This makes it easy to link an order with its customer.

17. Fig. (a) Order and Order_Line tables

18. Fig. (b) Product and Customer tables

19. The range of database applications
Personal Database PCs/PDAs, Cellphones – OK in special situations where need to share data amongst users is unlikely to arise
Workgroup Database. Designed to support collaboration in a small team (less than 25 people)
Department Database typically larger than a workgroup ( people) and more diverse range of functions – e.g. personnel database
Enterprise Database – scope of the whole organisation. May be more than one, as a single database for a large organisation may be impractical due to performance difficulties for large databases, diverse needs of user groups, and difficulty of achieving common definition of data (metadata) for all users.

20. Typical data from a personal computer database

21. Workgroup database with local area network

22. An example of departmental database (Personnel Department)

23. An enterprise data warehouse

24. Components of the database environment
CASE Tools – automated tools used to design databases and applications
Repository – generalised knowledge for all data definitions, relationships, screen/report formats – an extended set of metadata for managing databases and other components of the information system
Database Management System (DBMS) – software (sometimes specialised hardware) used to define, create, maintain and provide controlled access to the database and the repository.
Database – an organised collection of logically related data occurrences

25. Components of the database environment
Application Programs – software used to create and maintain the database and provide information to users.
User Interface – languages, menus etc by which users interact with other system components
Data Administrators – people responsible for overall information resources of an organisation.
Systems analysts/programmers and end Users – people who add, delete and modify the database and who get information from it.

26. Components of the database environment

27. Evolution of database systems
1960’s – file processing systems: punch cards, paper tape, magnetic tape – sequential access and batch processing
1970s - Hierarchical and Network (legacy, some still used today) – difficulties = hard to access data (navigational record-at-a-time procedures), limited data independence, no widely accepted theoretical model (unlike relational)
1980s - Relational – E.F. Codd and others developed this theoretically well-founded model – all data represented in the form of tables – Oracle, DB2, Ingres
1990s - Object-oriented, but some organisations have to handle large amounts of both structured and unstructured data, so Object-relational databases developed.

28. Evolution of database systems
2000 and beyond – multi –tier, client-server, distributed environments, web-based, content-addressable storage, data mining

29. Evolution of database technologies

30. SQL Is:
Structured Query Language (some for historical reasons call it ‘Sequel’
The standard and most common language for relational database management systems
An SQL-based relational database application involves a user interface, a set of tables in the database, and a RDBMS with an SQL capability
Within the RDBMS SQL will be used to create the tables, translate user requests, maintain the data dictionary and system catalog, update an maintain the tables, establish security, and carry out backup and recovery procedures

31. The SQL environment
Following Fig. Shows a schematic of an SQL environment
Each database is contained in a catalog, which describes any object that is part of the database (regardless of which user created that object). Most companies keep at least two versions of any database they are using. PROD_C is the live production version, which captures real business data and this must be very tightly controlled and monitored. DEV_C is the development version used when the database is being built and continues to serve as a development tool where enhancements and maintenance efforts can be tested before application to the production database.
Each database will have a set of schemas associated with a catalog.
Schema = the structure that contains descriptions of objects created by a user (base tables, views, constraints)

32. A simplified schematic of a typical SQL environment

33. 3 types of SQL commands
1. Data Definition Language (DDL) commands - that define a database, including creating, altering, and dropping tables and establishing constraints
2. Data Manipulation Language (DML) commands - that maintain and query a database
3. Data Control Language (DCL) commands - that control a database, including administering privileges and committing data

34. DDL, DML, DCL, and the database development process

35. SQL Data types
CHAR(n) – fixed-length character data, n characters long Maximum length = 2000 bytes
VARCHAR2(n) – variable length character data, maximum 4000 bytes
LONG – variable-length character data, up to 4GB. Maximum 1 per table
NUMBER(p,q) – general purpose numeric data type
INTEGER(p) – signed integer, p digits wide
FLOAT(p) – floating point in scientific notation with p binary digits precision
DATE – fixed-length date/time in dd-mm-yy form

36. Syntax used in these notes
Capitals = command syntax (may not be required by the RDBMS)
Lowercase = values that must be supplied by user
Brackets = enclose optional syntax
Ellipses (...) = indicate that the accompanying syntactic clause may be repeated as necessary
Each SQL command ends with a semicolon ‘;’
In interactive mode, when the user presses the RETURN key, the SQL command will execute

37. SQL Database Definition
Data Definition Language (DDL) has these major CREATE statements:
CREATE SCHEMA – defines a portion of the database owned by a particular user. Schemas are dependent on a catalog and contain schema objects, including base tables and views, domains, constraints, assertions, character sets, collations etc.
CREATE TABLE – defines a new table and its columns. The table may be a base table or a derived table. Tables are dependent on a schema. Derived tables are created by executing a query that uses one or more tables or views.

38. SQL Database Definition
CREATE VIEW – defines a logical table from one or more tables or views. There are limitations on updating data through a view. Where views can be updated, those changes can be transferred to the underlying base tables originally referenced to create the view.

39. SQL database definition
Each of the previous create commands may be reversed using a DROP command, so DROP TABLE will destroy a table (including its definitions, contents and any schemas or views associated with it)
Usually only the table creator may delete the table
DROP SCHEMA and DROP VIEW will also delete the named schema or view.
ALTER TABLE may be used to change the definition of an existing table

40. Creating tables
Once data model is designed and normalised, the columns needed for each table can be defined using the CREATE TABLE command. The syntax for this is shown in the following Fig. These are the seven steps to follow:
1. Identify the appropriate datatype for each , including length and precision
2. Identify those columns that should accept null values. Column controls that indicate a column cannot be null are established when a table is created and are enforced for every update of the table

41. Creating tables
3. Identify those columns that need to be UNQUE - when the data in that column must have a different value (no duplicates) for each row of data within that table. Where a column or set of columns is designated as UNIQUE, this is a candidate key. Only one candidate key may be designated as a PRIMARY KEY
4. Identify all primary key-foreign key mates. Foreign keys can be established immediately or later by altering the table. The parent table in such a parent-child relationship should be created first. The column constraint REFERENCES can be used to enforce referential integrity

42. Creating tables
5. Determine values to be inserted into any columns for which a DEFAULT value is desired - can be used to define a value that is automatically inserted when no value is provided during data entry.
6. Identify any columns for which domain specifications may be stated that are more constrained than those established by data type. Using CHECK it is possible to establish validation rules for values to be inserted into the database
7. Create the table and any desired indexes using the CREATE TABLE and CREATE INDEX statements

43. Table creation
General syntax for CREATE TABLE

44. Table creation
The following Fig. Shows SQL database definition commands
Here some additional column constraints are shown, and primary and foreign keys are given names
For example, the CUSTOMER table’s primary key is CUSTOMER_ID
The primary key constraint is named CUSTOMER_PK, without the constraint name a system identifier would be assigned automatically and the identifier would be difficult to read

45. SQL database definition commands for Pine Valley Furniture

46. STEP 1
Defining attributes and their data types

47. STEP2
Non-nullable specifications
Note: primary keys should not be null

48. Identifying primary keys
STEP 3
Identifying primary keys
This is a composite primary key

49. STEP 4
Identifying foreign keys and establishing relationships

50. STEPS 5 and 6
Default values and domain constraints

51. STEP 7
Overall table definitions