Developing Database Specifications TRACK 3

Learning Objectives At the end of the session, the participants should be able to Identify the information requirements of the organisation, resource centre/department, end-user. Identify areas wherein database can address the requirements. Write a database requirement specifications. Identify a minimal database design specification.

Why make specifications? Software Crisis  80-90%-do not meet their performance goals  80%-delivered late and over budget  40%-developments fail or are abandoned  < 40%-fully address training and skills requirements  < 25% -properly integrate business and technology objectives  10-20%-meets all their success criteria.

Reasons...  Lack of a complete requirement specification.  Lack of an appropriate development methodology.  Poor decomposition of design into manageable components.

Database Planning Systems Definition Requirements Collection and analysis Database Design DBMS Selection Application Design Implementation Data Conversion and loading Testing Evaluation & Maintenance Prototyping DDLC STEP 1 - DATABASE PLANNING  Feasibility Study - time frame - resource: budget, people  Integrate the database with the overall Information Architecture of the organization

Database Planning Systems Definition Requirements Collection and analysis Database Design DBMS Selection Application Design Implementation Data Conversion and loading Testing Evaluation & Maintenance Prototyping DDLC

DB Specs. Components  Requirements Specification Database Design Specification The WENDY Example - WENT Database Directory

Requirements Specs.  Statement of the Problem Domain  Objectives Data Requirements Transaction Requirements

DB Design Objectives  represent the data and the relationships between data required from the database application  provide a data model that supports any transactions required on the data  specify a minimal design that is appropriately structured to achieve the stated performance requirements for the database application

Relational DB Design Phases Building the logical/conceptual data model Building the physical database design

Data Modelling Entity-Relationship Diagram (ERD) - a tool for modelling data. 3 major concepts to remember Entity Attribute Relation

Other Concepts Entity type Example: FULLTIME FACULTY and PARTTIME FACULTY entities both keep the same sets of attributes like name, address, gender, department, position. The two entities can be generalised as FACULTY, which is the entity type.

Other Concepts Attribute Domain Example: The attribute GENDER can contain only any one of the following values: female, male Simple Attribute Example: Firstname is a simple attribute of the entity PERSON.

Other Concepts Composite Attribute Example: Name is a composite attribute that has three parts-- first name, middle name, last name Multi-valued Attribute Example: Area of expertise attribute can hold one or more values for a particular PERSON record.

Other Concepts Derived Attributes Example: The AGE is a derived attribute of the formula: BIRTHDAY – CURRENT DATE

Integrity Constraints  Required data  Attribute domain constraints  Entity integrity  Referential integrity