Chapter 2Database Planning and Database

Architecture

Spring 2014

Data as a Resource

• Resource: an asset that has value and incurs cost

• Resources include capital equipment, financial assets, personnel, and data

• Database is a resource because– Operational data has value– Database incurs cost– Professionally managed by DBA

Characteristics of Data

• Data vs. information– Data: raw facts

• Example: printout of tables as they are stored, without headings saying what they mean

– Information: processed data, useful for decision-making

• Example: formatted report using database

Four Levels of Data1. Real world

• Enterprise in its environment• Mini-world, or Universe of Discourse – part of the world that is

represented in the database2. Conceptual Model

• Entities, entity sets, attributes, relationships• Often represented as ER, EER or UML diagram

3. Logical model of database-intension• Metadata, data about data• Record types, data item types, data aggregates• Schema - stored in data dictionary, catalog

4. Data occurrences-extension• Database itself• Data instances• files

Four Levels of Discussing DataRealm Objects Examples

Real WorldContainingMiniworld

Enterprise

Some aspects of the enterprise

Corporation, university, bank

Human resourcesStudent enrollmentCustomers and accounts

Conceptual Model EntittyAttributeEntity setRelationship

a student, a classname, scheduleall students, all classesStudent entity relates to class entity by being enrolled in it

Logical ModelMetadata: data definitions, stored in Data Dictionary

Record type

Data item type

Data Aggregator

Student record type, Class record type

stuid, classNumber

address, consisting of street, name, state, ZIP

DataOccurrences stored in the database

Student record occurrence

Data item occurrence

File

Database

Record of student Tom Smith

‘S1001’, ‘Smith’, ‘Tom’,’History’,90

Student file with 5000 Student records

University database containing Student file, Class file, Faculty file, …

Data Sublanguages

• DBMS uses a data sublanguage, with two parts– Data definition language (DDL) - used to define

the database– Data manipulation language (DML) - is used to

process the database– Data sublanguage may be embedded in a host

language-general programming language,such as Java, C, C++, C#, COBOL..

Characteristics of a Conceptual Database Model

– Faithfully mirrors the operations of the organization

– Flexible enough to allow changes as new information needs arise

– Supports many different user views– Independent of physical implementation– Does not depend on the model used by a

particular database management system

Stages in Database Design

• Analyze user environment• Develop conceptual data

model• Choose a DBMS• Develop logical model, by

mapping conceptual model to DBMS

• Develop physical model• Evaluate physical model• Perform tuning, if indicated• Implement physical model

Analyze User Environment

Develop Conceptual Model

Choose DBMS

Develop Logical Model

Develop Physical Model

Evaluate Physical Model

Tune System

Implement System

Design Tools

• CASE (Computer-Aided Software Engineering)– tools for system analysis, project management, designing

the data model, designing applications, implementing the database, prototyping, data conversion, generating application code, generating reports, testing

• Data dictionary• Project management software

Data Dictionary• Contains metadata• Can be integrated (system catalog, part of DBMS) or free-standing• Both useful for

– Collecting information about data in central location– Securing agreement on meanings of items– Communicating with users– Identifying inconsistencies – synonyms and homonyms– Keeping track of changes to DB structure– Determining impact of changes to DB structure– Identifying sources of/responsibility for items– Recording external/logical/physical models & mappings– Recording access control information– Providing audit information

• Catalog also provides audit information

Project Management Software• Tools to help plan and manage projects, especially those with many

people• Include several types of charts and graphs

– GANTT chart– PERT chart

• User specifies– Scope and objectives– Major tasks and phases– Task dependencies– Resources, including personnel– Timelines

• Software can– Generate calendars– Produce graphs with different views of project– Provide means of communication for staff

ID Task Name Start Finish DurationJan 4 2004 Jan 11 2004 Jan 18 2004

128 9 195 13 16 2115 2310 17 221876 11 14 20

1 4d1/8/20041/5/2004Define specifications

5 3d1/13/20041/9/2004Create E-R diagram

9 1d1/14/20041/14/2004Map E-R to relational model

10 1d1/15/20041/15/2004Normalize relational model

12 2d1/20/20041/19/2004Create EER diagram

13 1d1/21/20041/21/2004Map EER model to object-relationalmodel

14 2d1/23/20041/22/2004Create object-relational database

15 2d1/26/20041/23/2004Create UML diagram

16 1d1/27/20041/27/2004Map UML diagram to object-orientedmodel

17 2d1/29/20041/28/2004Create object-oriented database

Jan 25 2004

24 25

11 2d1/19/20041/16/2004Create relational database

26 27 28 29 30 31

8

7

6 4h1/9/20041/9/2004Identifyentities,attributes,relationships

4h1/12/20041/12/2004Identity cardinality,participationconstraints

1d1/13/20041/13/2004Draw diagram

4

3

2 2d1/6/20041/5/2004Interview users

1d1/7/20041/7/2004Identify transactions, reportsneeded

1d1/8/20041/8/2004Begin data dict, x-ref table

Resource Names

Adam

Adam, Beth

Beth,Colin

Adam

Adam, Beth

Adam, Colin

Beth

Adam

Colin

Adam, Beth, Colin

Adam

Beth

Beth

Colin

Adam

Gantt Chart for The Art Gallery Database Project

Database Administrator Skills

– DBA must be• Technically competent • Good manager• Have excellent interpersonal and communication skills

– Has primary responsibility for planning, designing, developing and managing the operating database

– Database designer may do conceptual and logical design; DBA does physical design, implementation, develops, manages system

Planning and Design Stage

– Preliminary planning– Identifying user requirements– Developing and maintaining the data dictionary– Designing the conceptual model– Choosing a DBMS– Developing the logical model– Developing the physical model

Development Phase

– Creating and loading the database– Developing user views– Writing and maintaining documentation– Developing and enforcing data standards– Developing and enforcing application program

standards– Developing operating procedures– Doing user training

Database Management Phase

• Monitoring performance• Tuning and reorganizing• Keeping current on database improvements

Three-level Database Architecture

• CODASYL DBTG and ANSI/X3/SPARC - database architecture at 3 levels of abstraction

• External• Logical• Internal

– Each with written description called a schema

• Rationale for separation of external and internal levels Different users need different

views of same data Users data needs may change

over time Hides complexity of database

storage structures Can change logical structure

without affecting all users Can change data and file

structures without affecting overall logical structure or users' views

Database structure unaffected by changes to the physical aspects of storage

External Level

• Consists of many user models or views• Has external records - records seen by users• May include calculated or virtual data• Described in external schemas (sub-schemas)• Used to create user interface

Logical Level• Entire information structure of database• “community view” as seen by DBA• Collection of logical records• Derived from conceptual model• All entities, attributes, relationships represented• Includes all record types, data item types,

relationships, constraints, semantic information, security and integrity information

• Relatively constant over time• Described in logical schema• Used to create logical record interface

Internal Level

• Implementation level• Includes data structures, file organizations used

by DBMS• Depends on which DBMS used• Described in internal schema• Used to create stored record interface with

operating system• Operating system creates physical files and

physical record interface, below DB

Retrieving Records in Three Level SystemUser A requests record of employee E101 through User Interface

DBMS receives request

DBMS checks under A’s external schema, external/logical mapping, logical schema in DD

DBMS checks to see if user A is authorized. If not, rejects request

DBMS checks logical/internal mapping, determines corresponding internal structures

DBMS uses stored record interface to request stored record from OS

OS identifies desired physical record and asks access method to retrieve it

Access method retrieves block of records to buffer, passes address of stored record to DBMS

DBMS checks logical/internal mapping, edits stored record, passes logical record to logical level

DBMS checks external/logical mapping, edits logical record, passes external record to User A

Difference in External, Logical, Stored and Physical Record

External Employee Records:

employeeName empNumber dept

JACK JONES E101 Marketing

Logical Employee Records:empid lastName firstName dept salary

E101 Jones Jack 12 55000

Stored Employee Records:

empid lastName firstName dept salary Forward pointer

Backward Pointer

E101 Jones Jack 12 55000 10101 10001

Physical Records:

Block header rec of E90 rec of E95 rec of E101 rec of E125

Data Independence

• Logical data independence– Immunity of external models to

changes in the logical model– Occurs at user interface level

• Physical data independence– Immunity of logical model to

changes in internal model– Occurs at logical interface level

External View

Logical Model

Internal Model

User Interface

User Interface

Data Models

• Collection of tools for describing structure of database

• Often includes a type of diagram and specialized vocabulary

• Description of the data, relationships in data, constraints on data, some data meanings

• Most permanent part in database architecture• corresponds to conceptual level or logical level• Intension or scheme of the database• May change with schema evolution

Entity-Relationship Model• A semantic model, captures meanings• Conceptual level model• Proposed by P.P. Chen in 1970s• Entities are real-world objects about which we collect data• Attributes describe the entities• Relationships are associations among entities• Entity set – set of entities of the same type• Relationship set – set of relationships of same type• Relationships sets may have descriptive attributes• Represented by E-R diagrams

Basic Symbols of E-R DiagramsSymbol Name Meaning Example

Rectangle

Oval

Diamond

Line

Entity Set

Attribute

Relationship

Links:Attribute to Entity

Student

stuid

Enroll

Student EnrollEntity Set to Relationship

Attribute to Relationship

Simplified E-R Diagram

Student ClassEnroll

ClassNumber

roomschedulegrade

credits

firstName

major

stuidlastName

Relational Model

• Record-based model • Logical-level model• Proposed by E.F. Codd• Based on mathematical relations• Uses relations, represented as tables• Columns of tables represent attributes• Tables represent relationships as well as entities• Successor to earlier record-based models—network

and hierarchical

Example Relation

Student

stuId lastName firstName major credits

S1001 Smith Tom History 90

S1002 Chin Ann Math 36

S1005 Lee Perry History 3

S1010 Burns Edward Art 63

S1013 McCarthy Owen Math 0

S1015 Jones Mary Math 42

S1020 Rivera Jane CSC 15

Object-oriented Model• Similar to E-R but includes encapsulation, inheritance• Objects have both state and behavior• State is defined by attributes• Behavior is defined by methods (functions or procedures)• Designer defines classes with attributes, methods, and

relationships• Class constructor method creates object instances• Each object has a unique object ID• Classes grouped into class hierarchies• Database objects have persistence• Both conceptual-level and logical-level model• UML class diagrams often used

Class Diagram

Object-relational model

• Adds to relational model

– new complex datatypes

– objects with attributes and methods

– inheritance

• SQL extended to handle objects

Semi-structured Model

• Collection of nodes, each with data, with different schemas

• Node contains a description of its own contents• Can be used for integrating existing databases• XML tags in documents describe structure• XML tags identify elements, sub-elements, attributes

in documents• XML DTD (Document Type Definition) or XML

Schema used to define structure