Lesson 2: Database Development Process

• Database Development Activities During the Systems Development Life Cycle (SDLC)
• Systems Development Life Cycle


  1. Planning

  2. Analysis

  3. Design

  4. Implementation

  5. Maintenance
• Albert Einstein: 'If you can't explain it simply, you don't understand it well enough.'
• Planning


  To develop a preliminary understanding of a business situation and how information systems might help solve a problem or make an opportunity possible
• Planning Deliverable


  A written request to study the possible changes to an existing system or the development of a new system that addresses an information systems solution to the business problems or opportunities
• Analysis


  To analyze the business situation thoroughly to determine requirements, to structure those requirements, and to select among competing system features
• Analysis Deliverable


  The functional specifications for a system that meets user requirements and is feasible to develop and implement
• Design


  To elicit and structure all information requirements; to develop all technology and organizational specifications
• Design Deliverable


  Detailed functional specifications of all data, forms, reports, displays, and processing rules; program and database structures, technology purchases, physical site plans, and organizational redesigns
• Implementation


  To write programs, build data files, test and install the new system, train users, and finalize documentation
• Implementation Deliverable


  Programs that work accurately and to specifications, documentation, and training materials
• Maintenance


  To monitor the operation and usefulness of a system, and to repair and enhance the system
• Maintenance Deliverable


  Periodic audits of the system to demonstrate whether the system is accurate and still meets user's needs
• Enterprise Modeling


  1. Analyze current data processing

  2. Analyze the general business functions and their database needs

  3. Justify need for new data and databases in support of business
• Enterprise Data Model


  An integrated view of the data produced and consumed across an entire organization. A data architectural framework used for integration. It enables the identification of shareable and/or redundant data across functional and organizational boundaries
• Conceptual Data Modeling


  1. Identify scope of database requirements for proposed information system

  2. Analyze overall data requirements for business function(s) supported by database

  3. Develop preliminary conceptual data model, including entities and relationships

  4. Compare preliminary conceptual data model with enterprise data model

  5. Develop detailed conceptual data model, including all entities, relationships, attributes, and business rules
• Logical Database Design


  1. Analyze in detail the transactions, forms, displays, and inquiries (database views) required by the business functions supported by the database

  2. Integrate database views into conceptual data model

  3. Identify data integrity and security requirements, and populate repository
• Physical Database Design


  1. Define database to DBMS (often generated from repository)

  2. Decide on physical organization of data

  3. Design database processing programs
• Logical Data Model (LDM)

  Includes entities (tables), attributes (columns/fields) and relationships (keys).
• Physical Data Model (PDM)


  Includes tables, columns, keys, data types, validation rules, database triggers, and access constraints. Uses more defined and less generic specific names for tables and columns, such as abbreviated column names, limited by the database management system (DBMS) and any company defined standards. Requires a knowledge of the specific DBMS that will be used to implement the database
• Conceptual Data Model (CDM)


  Includes high-level data constructs. Non-technical names, so that executives and managers at all levels can understand the data basis of Architectural Description. Represent data from the viewpoint of the organization, independent of any technology
• Database Implementation


  1. Code and test database processing programs

  2. Complete database documentation and training materials

  3. Install database and convert data from prior systems
• Database Maintenance


  1. Analyze database and database applications to ensure that evolving information requirements are met

  2. Tune database for improved performance

  3. Fix errors in database and database applications and recover database when it is contaminated
• Two Approaches to Database and Information Systems Development

  • Waterfall
  • Rapid Application Development (RAD)
• Waterfall


  Detailed, well-planned development process. Time-consuming, but comprehensive. Long development cycle
• Rapid Application Development (RAD)


  Iterative process of rapidly repeating analysis, design, and implementation steps until they converge on the system the user wants
• Prototyping


  Popular RAD method. Repeat implementation and maintenance activities with new prototype versions
• Agile Software Development Methodologies

  • Scrum
  • Kanban
  • Lean
  • XP
• Agile Core Values


  • Individuals and interactions over processes and tools
  • Working software over comprehensive documentation
  • Customer collaboration over contract negotiation
  • Responding to change over following a plan
• Agile Key Principles


  • Satisfying customers is of foremost importance
  • Develop projects with inspired contributors
  • Interactions are best when done in person
  • Software that works is a measure of progress
  • Reflect and adapt on an ongoing basis
• RAD or Agile Software Development should be considered when a project involves unpredictable and / or changing requirements or when most of the necessary database structures already exist
• Planning Deliverable

  A written request to study the possible changes to an existing system or the development of a new system that addresses an information systems solution to the business problems or opportunities.
• Analysis Deliverable


  The functional specifications for a system that meets user requirements and is feasible to develop and implement.
• Design Deliverable


  Detailed functional specifications of all data, forms, reports, displays, and processing rules; program and database structures, technology purchases, physical site plans, and organizational redesigns.
• Implementation Deliverable


  Programs that work accurately and to specifications, documentation, and training materials.
• Maintenance Deliverable


  Periodic audits of the system to demonstrate whether the system is accurate and still meets user's needs
• Logical Data Model (LDM)


  Uses business names for entities & attributes.
• Logical Data Model (LDM)


  Is independent of technology platform; describes the data in terms of data management technology which will be used
• Physical Data Model (PDM)


  Uses more defined and less generic specific names for tables and columns, such as abbreviated column names, limited by the database management system (DBMS) and any company defined standards
• Physical Data Model (PDM)


  Requires a knowledge of the specific DBMS that will be used to implement the database