The Database Environment and Development Process PDF
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This document presents an overview of database environments and development processes. It includes learning objectives, definitions of key terms, and descriptions of the database development life cycle. It also details advantages, disadvantages, and costs associated with database approaches.
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THE DATABASE ENVIRONMENT AND DEVELOPMENT PROCESS CHAPTER 1 Learning Objectives Define terms Name limitations of conventional file processing Explain the advantages of databases Identify the costs and risks of databases List components of a database environment Identify c...
THE DATABASE ENVIRONMENT AND DEVELOPMENT PROCESS CHAPTER 1 Learning Objectives Define terms Name limitations of conventional file processing Explain the advantages of databases Identify the costs and risks of databases List components of a database environment Identify categories of database applications Describe the database system development life cycle Explain the roles of individuals Describe evolution of databases Definition of Terms Database: an organized collection of logically related data. Data: a stored representation of meaningful objects and events. Structured: number, text, dates Unstructured: images, videos, documents Information: data processed to increase knowledge in the person using the data. Metadata: data that describes the properties and context of user data. Baker, Kenneth D. 324917628 Doyle, Joan E. 476193248 Finkle, Clive R. 548429344 Lewis, John C. 551742186 McFerran, Debra R. 409723145 Context helps users understand data. Graphical displays turn data into useful information that managers can use for decision-making and interpretation. Description of the properties or characteristics of the data, including data types, field sizes, allowable values, and data context. Disadvantages of File Processing Program-data dependence Duplication of data Limited data sharing Lengthy Development Times Excessive Program Maintenance Problems with Data Dependency Each application programmer must maintain his/her own data. Each application program needs to include code for each file’s metadata. Each application program must have its own processing routines for reading, inserting, updating, and deleting data. Lack of coordination and central control. Non-standard file formats Problems with Data Redundancy Waste of space to have duplicate data. Causes more maintenance headaches. Data changes in one file caus Biggest couldproblem: e inconsistencies Compromises in data integrity. SOLUTION: The Database Approach Central repository of shared data. Data is managed by a controlling agent. Stored in a standardized, convenient form. *Requires a Database Management System (DBMS) SOLUTION: The Database Approach A software system that is used to create, maintain, and provide controlled access to user databases. Order Filing System Central Invoicin Database DBMS Contains g employee, order, Syste inventory, m pricing, and Payroll customer data System DBMS manages data resources like an operating system manages hardware resources. Elements of the Database Approach Data models Graphical diagram capturing the nature and relationship of data Enterprise Data Model – high-level entities and relationships for the organization. Entities Noun form describing a person, place, object, event, or concept. Elements of the Database Approach Relationships Between entities Usually one-to-many (1:M), many-to-many (M:N), but could also be one-to-one (1:1). Relational Databases Database technology involving tables (relations) representing entities and primary/ foreign keys representing relationships. Advantages of the Database Approach Program-data independence Planned data redundancy Improved data consistency Improved data sharing Increased application development productivity Enforcement of standards accessibility, and Improved data quality, responsiveness Reduced program maintenance Improved decision support Costs and Risks of the Database Approach New, specialized personnel Installation and cost and management complexity Conversion costs Need for explicit backup and recovery Organizational conflict Components of the database environment Components of the Database Environment Data Modeling and Design Tools – automated tools used to design databases and application programs. Repository – a centralized storehouse of metadata. Database Management System (DBMS) – software for managing the database. Database – a storehouse of the data. Application Programs – software using the data. Components of the Database Environment User Interface – text, graphical displays, menus, etc. for the user. Data/Database Administrators – personnel responsible for maintaining the database. System Developers – personnel responsible for designing the database and software. End Users – people who use the applications and Enterprise Data Model First step in the database development process. Specifies scope and general content. Overall picture of organizational data at a high level of abstraction. Entity-relationship diagram. Descriptions of entity types. Relationship between entities. Business rules. Approaches to Database and IS Development SDLC System Development Life Cycle Detailed, well-planned development process Time-consuming, but comprehensive Long development cycle Approaches to Database and IS Development Prototyping Rapid application development (RAD) Cursory attempt at conceptual data Define modeling the database during development of the initial the prototype Repeat maintenance implementation activities an prototype with d Systems Development Life Cycle Planning Analysis Logical Design Physical Design Implementation Maintenance Systems Development Life Cycle Planning Purpose: Preliminary understanding Deliverable: Request for study Analysis Logical Design Physical Design Database Activity Enterprise modeling Conceptual data Implementation modeling Maintenance Systems Development Life Cycle Planning Purpose: Thorough requirements analysis and structuring Deliverable: Functional system specifications Analysis Logical Design Physical Design Database Activity Thorough and conceptual data integrated Implementation modeling. Maintenance Systems Development Life Cycle Planning Purpose: Information requirements elicitation and structure Deliverable: Detailed design specification Analysis Logical Design Physical Design Database Activity Logical database design (transactions, forms, Implementation views, data integrity, displays, and security. Maintenance Systems Development Life Cycle Planning Purpose: Develop technology and organizational specifications Deliverable: Program/data structures Analysis technology purchases, , redesigns organizational Logical Design Physical Design Database Activity Physical database design (define database to Implementation DBMS, physical data organization database processing programs) Maintenance Systems Development Life Cycle Planning Purpose: Programming, training, installation, testing, documenting Deliverable: Operational program Analysis documentation, training materials Logical Design Physical Design Database Activity Database including coded programs, implementation, Implementation documentation, installation, and conversion Maintenance Systems Development Life Cycle Planning Purpose: Monitor, repair, and enhance Deliverable: Periodic audits Analysis Logical Design Physical Design Database Activity Database maintenance performance analysis , and Implementation tuning, error corrections Maintenance Prototyping Methodology Managing People and Projects Project – a planned undertaking of related activities to reach an objective with a beginning and an end. Initiated and planned in the planning stage of SDLC. Executed during analysis, design, and implementation. Closed at the end of implementation. Managing Project: People Involved Business analysts System analysts Database analysts and data modelers Users Programmers Database architects Data administrators Project managers Other technical experts Evolution of Database Systems Driven by four main objectives: Need for program-data independence. Desire to manage more complex data types and structures. Ease of data access for less technical personnel. Needfor more powerful decision support platforms. Evolution of Database Systems Evolution of Database Systems Evolution of Database Systems Thank you! ♥