introduction to data management chapter 1, pratt & adamski
TRANSCRIPT
Data and Information
DATA: Facts concerning people, objects, vents or other entities. Databases store data.
INFORMATION: Data presented in a form suitable for interpretation.
Data is converted into information by programs and queries. Data may be stored in files or in databases. Neither one stores information.
KNOWLEDGE: Insights into appropriate actions based on interpreted data.
Basic Principles
DATABASE: A shared collection of interrelated data designed to meet the varied information needs of an organization.
DATABASE MANAGEMENT SYSTEM: A collection of programs to create and maintain a database.
DefineConstructManipulate
Advantages of Database Processing
More information from same data
Shared dataBalancing conflicts
among usersControlled
redundancyConsistency
IntegritySecurityIncreased
productivityData
independence
Disadvantages of Database Processing
Increased sizeIncreased complexity
More expensive personnelIncreased impact of failureDifficulty of recoveryCost
Especially server and mainframe systems
Files and Databases
Metadata “Data about data”
Description of fieldsDisplay and format instructionsStructure of files and tablesSecurity and access rulesTriggers and operational rules
History of Database Management
File Management SystemsHierarchical ModelIBM “Information Management System (IMS)” 1966
Network ModelCharles Bachman’s “Integraded Data Store (IDS)”
1965Conference on Data Systems Languages /DataBase
Task Group CODASYL/DBTG (1971)
Relational ModelE.F. Codd, 1970
File Management Systems
Provided facilities to extract data and share files, but did not implement any way to connect records in one file to those in another. Relationships had to be implemented in application code.
Database vs File Systems
Program 1
Program 2
Program 3
Meta-Data
Meta-Data
Meta-Data
Data
Program 1
Program 2
Program 3
Meta- Data
Data
FILE SYSTEM
DATABASE
Structured Databases
Relationships were implemented by physical pointers (called “sets”) which allowed records to be connected in different files. Hierarchical databases allow only one parent set; networks allow several. These permit efficient processing but the sets must be constructed on data entry and cannot be rearranged later.
Relational Models
Relational models implement relationships with matched data values in related files (called primary and foreign keys). Any attributes can be matched. The connection is established at retrieval so interconnections can be developed as needed.
STUDENT
SECTION
INSTRUCTOR
Hierarchy
COLLEGECOLLEGE
Each file can have only one parent. To implement a second “parent” (COLLEGE) we have to implement a shadow copy.
STUDENT
SECTION
INSTRUCTOR
Network
COLLEGE
Each file can have several parents. Both SECTION and COLLEGE are “parent” files..
SECTION
Relational
COLLEGE
Each file can have several parents. Both SECTION and COLLEGE are “parent” files..
STUDENTCOLLEGE-KEY
INSTRUCTORCOLLEGE-KEY
SECTION-STUDENTSECTION-KEYSTUDENT-KEY
SECTION-INSTRUCTORSECTION-KEYINSTRUCTOR-KEY
Relational Terminology
Entity Person, place, thing or event about
which we wish to keep dataAttribute
property of an entityRelationship
an association among entities (entity records)
KERR MCGEE’S LIFE CYCLE
STAGE PROCESS MODEL DATA MODEL
Initialization Report Report
Feasibility ReportHigh Level DFD
Process Analysis (Business Chart)High Level E/R Diagram
Requirements General
DFDHigh Level Dictionary
Top Down E/RFile Specifications
Requirements Logical
DFDData DictionaryFile SpecificationsProcess Logic
Bottom Up E/RAction Diagrams
System Design Structure ChartsModule IPO SpecificationScreen/Report LayoutsCleanup
Volume/Usage AnalysisPhysical SchemaIndex/Record Specs
Coding/Testing Test PlanLogs and DocumentationCode
Implementation Installation Plan Population Plan
Data Management
Designing and managing information in a data base environment requires:
Understanding the principles of data modeling in system design.
Using SQL for data manipulation.Understanding the concepts of
managing data in a database environment.
Information System Modeling Approaches
PROCESS MODELING: The traditional method of designing systems by following the changes to data flows.
DATA MODELING: An approach to system development that specifies the file structure that conforms to the things important to the organization.
PROTOTYPING: An iterative approach that focuses on building small operating
OBJECT MODELING (Event driven design):Defines objects that contain data and associated processing rules encapsulated together.