MIS 673: Database Analysis and Design

Objectives: Know how to analyze an environment and draw its

semantic data model Understand data analysis and database design

process Be able to evaluate and refine data structures Know how to convert semantic data models into a

relational one Implement a relational database and query it using

SQL Understand new trends in data management and

analysis Understand the coexistence of data and process

modeling

Grading: midterm 20% final 20% homework 20% research project 15% computer assignments 15% participation 10%

MIS 673: Database Analysis and Design

Homework

ReadingsReadings Written assignments:Written assignments:

Selected questionsSelected questions ProblemsProblems ExercisesExercises

Team Research Project

Teams of five Research topics:

A field case, concept or product Must relate to advanced database technology Can be based on the research of the literature

Outcomes: Written report up to 5000 words Presentation lasting 30 minutes

J. Martin: Four levels of data environment Files Application databases Subject databases Information Systems

File Systems and Databases

Files

Separate files are used for most applications

Simple, easy to implement Large proliferation of files,

high redundancy Data inconsistency, anomalies Exhibit structural dependence Changes are difficult, slow,

expensive

Data-Centered System Development

DATA

Data Data creationcreation

Data Data updatingupdating

““What-if?” What-if?” analysis and analysis and decision supportdecision support

Summary, analysis, Summary, analysis, chart & report chart & report generationgeneration

Generation of Generation of documentsdocuments

InformatioInformation searchingn searching

AuditsAudits

DBMS

Application Databases

Separate databases are designed for separate applications

Large proliferation of databases, high redundancy, high maintenance costs

May be more expensive than files environment

Major advantages of database operation are not achieved

Subject Databases

Databases are independent of specific applications Data for business objects are associated and represented

in shared databases Thorough data analysis and modeling are needed Much lower maintenance costs Leads to faster application development Requires a change in system analysis methods

True benefits True benefits can be achievedcan be achieved

Information Systems

Databases are organized for fast information retrieval

A variety of languages and query facilities are often used

New elements are added as they are needed Should coexist with Subject Databases

Database System

Stores the definitions (metadata = data about data) in a data dictionary

Creates complex structures making programming easier

Translates logical into physical requests Provides a security system Allows multiple-user access Provides backup and recovery procedures Promotes and enforces integrity Provides user interfaces for querying

Data Analysis and Modeling

Models: simplified abstractions of real world

Goal: deriving effective information from an efficient database

Database model: a collection of logical constructs

Two categories: conceptual (semantic) and implementation

Degrees of Data Abstraction

Semanticmodel

Userview 1

Userview 2

Implemen-tation model

Physicalmodel

High degreeof abstraction

Medium degreeof abstraction

Low degreeof abstraction

Conceptual Schema: an Example

PROFESSOR CLASS STUDENT

CLASSROOM

1 M M N

M

1

teaches contains

requires

is taught by attends

hosts

Components: - -

EntitiesRelationships

MIS673, Week 1 Summary

Database analysis and design Data models Refinement of data structures Conversion of semantic into implementation

data model Implementation of a relational database Structured Query Language (SQL) New trends in data management Relationship with process modeling