IMS1907 Database Systems

1
IMS1907 Database Systems

• Summer Semester 2004/2005
• Lecture 3
• Database System Development and the SDLC

2
Database Systems Development

• Databases are key components of information
  systems
• The development of the database must be
  coordinated with all other activities in the
  development lifecycle
• Database development requires specialised skills
  and knowledge
• Like IS development, database development
  requires a structured approach

3
Database Systems Development

• Database development requires a focus on the
  information needs of a business
• Information Engineering (IE) is a popular,
  data-oriented methodology used to develop
  database systems
• data are modelled in the organisational context,
  not in the usage, processing or technology
  context
• business context changes slowly ? stable
  databases
• top-down planning

4
Database Systems Development

• Top-down planning
• specific IS needs are deduced from understanding
  of information needs
• broad perspective
• useful for considering integration of system
  components
• understanding of relationship between IS and
  business objectives
• understanding of the impact of IS across
  organisation

5
Database Systems Planning

• IE Planning phase
• goal is to align information technology and its
  usage with the overall strategic goals of the
  organisation
• alignment is essential to achieving maximum
  benefits from the investment in technology
• aims at an enterprise view of the information
  needs of an organisation
• three steps in the phase

6
Database Systems Planning

• The three steps in the IE Planning phase
• identify strategic planning factors
• identify corporate planning objects
• develop an enterprise model

7
Database Systems Planning

• Step 1 - identify strategic planning factors
• goals
• critical success factors (CSF)
• problem areas
• see Hoffer, Prescott and McFadden, (2005), Table
  2-2, p. 41
• Identifying these factors enables
• the development of planning context
• the linkage of IS plans with strategic business
  plans
• setting of priorities for new IS requests

8
Database Systems Planning

• Step 2 - identify corporate planning objects
• organisational units
• organisational locations
• business functions
• entity types
• information systems
• see Hoffer et al, (2005), Table 2-3, p. 42
• Defines business scope and where IS changes can
  occur

9
Database Systems Planning

• Step 3 develop an Enterprise Model
• functional decomposition of each business
  function
• enterprise data model
• various planning matrices
• see Hoffer et al, (2005), Figure 2-3, p. 44
• Helps simplify problems, isolate attention
• Identify business rules
• Setting development priorities, scheduling
  activities

10
Database Systems Planning

• Planning matrices
• location-to-function
• unit-to-function
• information system-to-data entity
• supporting function-to-data entity
• information system-to-objective
• Identifying orphans, missing entities, missing
  functions, unassigned functions, unassigned
  units, necessary systems, prioritisation of
  development

11
Database Systems Development

• Not all database systems arise from a top-down
  planning approach
• Bottom-up requests can cause a need for
  development
• operational level requests
• projects requested by IS users to perform job
• need for data management improvements
• There is still a need for an enterprise model of
  data
• data already exists? new data requirements? more
  than one database?

12
Database Development and the SDLC

• Enterprise modelling

Initiation
Conceptual data modelling
Analysis
Logical database design
Design
Physical database design and definition
Implementation
Database implementation
Review
Database review
Database maintenance
Maintenance
13
Enterprise Modelling

• Review enterprise modelling components identified
  during planning
• Analyse current IS, database and data processing
• Analyse general business functions and data needs
• Describe new information and data needs
• Determine which data already exists
• Justify need for new data and databases to
  support business

14
Enterprise Data Model

• High-level view of major things of significance
  to the organisation
• Similar to entity-relationship modelling but not
  as detailed
• Business-oriented descriptions of elements
• Statements of business rules governing data
  validity

15
Enterprise Data Model

• A possible simplified Enterprise Data Model for
  Amazon.com

16
Conceptual Data Modelling

• Identify scope of database requirements
• Analyse overall data requirements to support
  functionality
• Develop preliminary data model -
  entity-relationship (ER) modelling
• Compare conceptual ER model with enterprise data
  model
• Develop detailed conceptual data model
  entities, relationships, attributes, and business
  rules
• Make conceptual model consistent with other IS
  models
• Populate repository with all conceptual DB
  specifications

17
Logical Database Design

• Transform conceptual model into logical data
  model
• analyse in detail transactions, forms, displays
  and enquiries (DB view) needed to support
  functions
• integrate database views and newly discovered
  requirements into conceptual model
• identify data integrity and security requirements
  
• transform reconciled data specifications into
  stable data structures dependent on type of
  DBMS
• Start to specify logic for maintaining and
  querying database
• Populate repository

18
Physical Database Design and Definition

• Requires knowledge of specific DBMS used
• Define database to DBMS (often generated by
  repository)
• Decide on physical organisation of data
  records, file organisation, indexes, clustering
• Design database processing programs necessary to
  generate information
• Enables secure and efficient handling of data
  processing needs
• Coordinated with design of other IS components
  programs, hardware, operating systems, networks

19
Database Implementation

• Code, test and install database processing
  programs
• Complete database documentation and training
  materials
• Put procedures in place for ongoing support of DB
  and IS
• Install database
• Load and convert data from legacy systems
• Load any new data needed
• Put database into production

20
Database Maintenance

• Analyse database and database applications to
  ensure evolving information needs are met
• Tune database for optimum performance
• Fix errors in database and database applications
• Recover or rebuild database if corrupted or
  contaminated due to program or system malfunction
  or failure
• Typically the longest step in DB development
  lasts throughout the life of the database and
  associated applications

21
Packaged Data Models

• Reuse of standard, but flexible, proven data
  models
• Can save time in modelling data requirements
• Comparatively low cost
• Can be customised and incorporated into other
  data models
• Developed by industry specialists and DBMS
  vendors
• Based on experience and expertise across industry
  sectors
• Two principal types of packaged data models
• universal data models
• industry-specific data models

22
Packaged Data Models

• Universal data models
• core subject areas common to many businesses
  customers, products, accounts, documents,
  projects
• core functions common to businesses that follow
  similar patterns purchasing, accounting,
  receiving, PM
• Provide templates for one or more of these areas
• Based on the fact that although differing in
  detail, underlying data structures are similar

23
Packaged Data Models

• Industry-specific data models
• generic data models for use in specific industry
  area
• available for nearly every major industry group
  health care, telecommunications, discrete
  manufacturing, process manufacturing, banking,
  insurance, mining, etc
• see Hoffer et al, (2005), Figure 2-7, p. 51
• Based on fact that process and data needs are
  similar within industry, but can differ across
  industries

24
People Involved in Database Development

• Systems Analysts
• analyse business situation
• identify business needs to meet problems or
  opportunities
• Database Analysts
• determine requirements for database
• design database
• Users
• provide assessment of information needs
• monitor that system meets their requirements and
  needs

25
People Involved in Database Development

• Programmers
• design and write programs to maintain and access
  data
• Data and Database Administrators
• responsibility for existing and future databases
• ensure consistency and integrity across databases
• expert consulting and training
• Other technical experts
• networks, operating systems, communications,
  testing, documentation

26
References

• Elmasri, R. and Navathe, S.B., (2000),
  Fundamentals of Database Systems, (3rd edn.),
  Addison-Wesley, Reading, Massachusetts, USA.
• Hoffer, J.A., Prescott, M.B. and McFadden, F.R.,
  (2005), Modern Database Management, (7th edn.),
  Pearson Education Inc., Upper Saddle River, NJ,
  USA.