1. IMS1907 Database Systems Summer Semester 2004/2005 Lecture 3 Database System Development and the SDLC

2. Monash University 20042 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 Database Systems Development

3. Monash University 20043 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 Database Systems Development

4. Monash University 20044 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 Database Systems Development

5. Monash University 20045 IE Planning phase –goal is to align information technology and it’s 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 Database Systems Planning

6. Monash University 20046 The three steps in the IE Planning phase –identify strategic planning factors –identify corporate planning objects –develop an enterprise model Database Systems Planning

7. Monash University 20047 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 Database Systems Planning

8. Monash University 20048 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 Database Systems Planning

9. Monash University 20049 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 Database Systems Planning

10. Monash University 200410 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 Database Systems Planning

11. Monash University 200411 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? Database Systems Development

12. Monash University 200412 Enterprise modelling Database Development and the SDLC Initiation Analysis Design Implementation Review Maintenance Conceptual data modelling Logical database design Database implementation Physical database design and definition Database review Database maintenance

13. Monash University 200413 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. Monash University 200414 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. Monash University 200415 Enterprise Data Model A possible simplified Enterprise Data Model for Amazon.com CUSTOMER BOOK CD SALE

16. Monash University 200416 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. Monash University 200417 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. Monash University 200418 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. Monash University 200419 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. Monash University 200420 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. Monash University 200421 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. Monash University 200422 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. Monash University 200423 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. Monash University 200424 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 People Involved in Database Development

25. Monash University 200425 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 People Involved in Database Development

26. Monash University 200426 References Elmasri, R. and Navathe, S.B., (2000), Fundamentals of Database Systems, (3 rd edn.), Addison-Wesley, Reading, Massachusetts, USA. Hoffer, J.A., Prescott, M.B. and McFadden, F.R., (2005), Modern Database Management, (7 th edn.), Pearson Education Inc., Upper Saddle River, NJ, USA.