CTIVITIES DURING THE SYSTEMS DEVELOPMENT LIFE CYCLE (SDLC)

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Created by
Katerina Mae

Cards (8)

  • 1.      PLANNING
    Enterprise Modelling
    -          Analyze current data processing.
    -          Analyze the general business functions and their database needs.
    -          Justify need for new data and databases in support of business.
    -          An Enterprise Data Model is an integrated view of the data produced and consumed across an entire organization.
    1. PLANNING
    Conceptual Data Modeling
    -          Identify scope of database requirements for proposed information system.
    -          Analyze overall data requirements for business function(s) supported by database.
  • 2.      ANALYSIS
    Conceptual Data Modeling
    -          Develop preliminary conceptual data model, including entities and relationships.
    -          Develop detailed conceptual data model, including all entities, relationships, attributes, and business rules.
    -          Make conceptual data model consistent with other models of information system.
    -          Populate repository with all conceptual database specifications.
  • 3.      DATABASE DESIGN
    Logical Database Design
    -          Analyze in detail the transactions, forms, displays, and inquiries (database views) required by the business functions supported by the database.
    -          Integrate database views into conceptual data model.
    -          Identify data integrity and security requirements, and populate repository.
  • 3. DATABASE DESIGN
    Physical Database Design and Definition
    -          Define database to DBMS (often generated from repository).
    -          Decide on physical organization of data.
    -          Design database processing programs.
  • DATABASE IMPLEMENTATION
    -          Code and test database processing programs.
    -          Complete database documentation and training materials.
    -          Install database and convert data from prior systems.
  • 5.     DATABASE MAINTENANCE
    -          Analyze database and database applications to ensure that evolving information requirements are met.
    -          Tune database for improved performance.
    -          Fix errors in database and database applications and recover database when it is contaminated.
  • DATA MODEL COMPARISON