Introduction to Database and Transactions Flashcards
Organized collection of logically related data
Database
Stored representations of meaningful objects and events
Data
Two Classifications of Data
- Structured
2. Unstructured
Classification of data that are numbers, text, dates
Structured
Classification of data that are images, video, documents
Unstructured
Data processed to increase knowledge in the person using the data
Information
Data that describes the properties and context of user data
Metadata
Turn data into useful information that managers can use for decision making and interpretation
Graphical Displays
What are the 5 Disadvantages of File Processing?
- Program-Data Dependence
- Duplication of Data
- Limited Data Sharing
- Lengthy Development Times
- Excessive Program Maintenance
All programs maintain metadata for each file they use
Program-Data Dependence
Different systems/programs have separate copies of the same data
Duplication of Data
No centralized control of data
Limited Data Sharing
Programmers must design their own file formats
Lengthy Development Times
80% of information systems budget
Excessive Program Maintenance
- Waste of space to have duplicate data
- Causes more maintenance headaches
Problems with Data Redundancy
What is the iggest problem of Problems with Data Redundancy?
- Data changes in one file could cause inconsistencies
- Compromises in data integrity
What is the solution for Problems with Data Redundancy?
Database Approach
- Central repository of shared data
- Data is managed by a controlling agent
- Stored in a standardized, convenient form
Database Approach
What is required in Database Approach?
Database Management System (DBMS)
A software system that is used to create, maintain, and provide controlled access to user databases
Database Management System
Contains employee,
order, inventory,
pricing, and
customer data
Central Database
What are the 10 Advantages of the Database Approach?
- Program-data Independence
- Planned Data Redundancy
- Improved Data Consistency
- Improved Data Sharing
- Increased Application Development Productivity
- Enforcement of Standards
- Improved Data Quality
- Improved Data Accessibility and Responsiveness
- Reduced Program Maintenance
- Improved Decision Support
What are the 5 Costs and Risks of the Database Approach?
- New, specialized personnel
- Installation and Management Cost and Complexity
- Conversion Costs
- Need for Explicit Backup and Recovery
- Organizational Conflict
What are the 4 Elements of the Database Approach?
- Data Models
- Entities
- Relationships
- Relational Databases
Graphical system capturing nature and relationship of data.
Data Models
Two Classifications of Data Models
- Enterprise Data Model
2. Project Data Model
Classification of data model that has a high-level entities and relationships for the organization.
Enterprise Data Model
Classification of data model that has more detailed view, matching data structure in database or data warehouse.
Project Data Model
- Noun form describing a person, place, object, event, or concept
- Composed of attributes
Entities
- Between entities
- Usually one-to-many (1:M) or many-to-many (M:N)
Relationships
Database technology involving tables (relations) representing entities and primary/foreign keys representing relationships.
Relational Databases
9 Components of the Database Environment
- CASE Tools
- Repository
- Database Management System (DBMS)
- Database
- Application Programs
- User Interface
- Data/Database Administrators
- System Developers
- End Users
Computer-aided software engineering
CASE Tools
Centralized storehouse of metadata
Repository
Software for managing the database
Database Management System (DBMS)
Storehouse of the data
Database
Software using the data
Application Programs
Text and graphical displays to users
User Interface
Personnel responsible for maintaining the database
Data/Database Administrators
Personnel responsible for designing databases and software
System Developers
People who use the applications and databases
End Users
- First step in the database development process
- Specifies scope and general content
- Overall picture of organizational data at high level of abstraction
- Entity-relationship diagram
- Descriptions of entity types
- Relationships between entities
- Business rules
Enterprise Model
Two Approaches to Database and IS Development
- SDLC
2. Prototyping
- Detailed, well-planned development process
- Time-consuming, but comprehensive
- Long development cycle
SDLC (System Development Life Cycle)
- Cursory attempt at conceptual data modeling
- Define database during development of initial prototype
- Repeat implementation and maintenance activities with new prototype versions
Prototyping with the use of Rapid Application Development (RAD)
Part in Systems Development Life Cycle
Purpose: preliminary understanding
Deliverable: request for study
Database Activity: enterprise modeling and early conceptual data modeling
Planning
Part in Systems Development Life Cycle
Purpose: thorough requirements analysis and structuring
Deliverable: functional system specifications
Database Activity: thorough and integrated conceptual data modeling
Analysis
Part in Systems Development Life Cycle
Purpose: information requirements elicitation and structure
Deliverable: detailed design specifications
Database Activity: logical database design (transactions, forms, displays, views, data integrity and security)
Logical Design
Part in Systems Development Life Cycle
Purpose: develop technology and organizational specifications
Deliverable: program/data structures, technology purchases, organization redesigns
Database Activity: physical database design (define database to DBMS, physical data organization, database processing programs)
Physical Design
Part in Systems Development Life Cycle
Purpose: programming, testing, training, installation, documenting
Deliverable: operational programs, documentation, training materials
Database Activity: database implementation, including coded programs, documentation, installation and conversion
Implementation
Part in Systems Development Life Cycle
Purpose: monitor, repair, enhance
Deliverable: periodic audits
Database Activity: database maintenance, performance analysis and tuning, error corrections
Maintenance
Prototyping Database Methodology:
- Analyze requirements
- Develop preliminary data model
Conceptual Data Modeling
Prototyping Database Methodology:
- Analyze requirements in detail
- Integrate database views into conceptual data model
Logical Database Design
Prototyping Database Methodology:
- Define new database contents to DBMS
- Decide on physical organization for new data
- Design database processing programs
Physical Database Design and Definition
Prototyping Database Methodology:
- Code database processing
- Install new database contents, usually from existing data sources
Database Implementation
Prototyping Database Methodology:
- Analyze database to ensure it meets application needs
- Fix errors in database
Database Maintenance
Prototyping Database Methodology:
- Analyze database for improved performance
- Fix errors in database
Database Maintenance
3 Database Schema
- External Schema
- Conceptual Schema
- Internal Schema
Classification of Database Schema:
- User Views
- Subsets of Conceptual Schema
- Can be determined from business-function/data entity matrices
- DBA determines schema for different users
External Schema
Classification of Database Schema:
- E-R models
Conceptual Schema
Classification of Database Schema:
- Logical structures
- Physical structures
Internal Schema
2 Structures of Internal Schema
- Logical Structures
2. Physical Structures
A planned undertaking of related activities to reach an objective that has a beginning and an end
Project
Who are involved in managing projects? (9)
- Business Analysts
- Systems Analysts
- Database Analysts and Data Modelers
- Users
- Programmers
- Database Architects
- Data Administrators
- Project Managers
- Other technical experts
Evolution of Database Systems is driven by Four Main Objectives:
- Need for program-data independence -> reduced maintenance
- Desire to manage more complex data types and structures
- Ease of data access for less technical personnel
- Need for more powerful decision support platforms
2 Enterprise Applications
- Enterprise Resource Planning (ERP)
2. Data Warehousing Implementations
Three-tiered Client/Server Database Architecture:
- Database of vendors, purchase orders, vendor invoices
Accounts Payable Processing Browser
Three-tiered Client/Server Database Architecture:
- Database of customer receipts and our payments to vendors
Cash Flow Analyst Browser
Three-tiered Client/Server Database Architecture:
- No local database
Customer Service Representative Browser
Three-tiered Client/Server Database Architecture:
- A/P, A/R, order processing, inventory control, and so forth; access and connectivity to DBMS, Dynamic Web pages; management of session
Application/Web Server
Three-tiered Client/Server Database Architecture:
- Transaction databases containing all organizational data or summarizes of data on department servers
Enterprise Server with DBMS
Enterprise database application that integrate all enterprise functions (manufacturing, finance, sales, marketing, inventory, accounting, human resources)
Enterprise Resource Planning (ERP)
Enterprise database application that Integrated decision support system derived from various operational databases.
Data Warehouse