1. DAVID M. KROENKE’S DATABASE PROCESSING, 10th Edition © 2006 Pearson Prentice Hall 2-1 David M. Kroenke’s Chapter One: Why DB? Database Processing: Fundamentals, Design, and Implementation

2. 2-2 Why database Share data –Data/information needs to be shared to run a business –We can run a company without its CEO, not without data Reduce redundancy –Reduce inconsistent data Support transaction Support data integrity Enforce security Support and enforce for standards Meet complicated requirements

3. 1-3 The problem of sharing with file systems Duplication Inconsistence Separated and isolated data –I have to fix 200 projectors made during the month of Dec 2008 How many did you make during that month? –I’ll get this data from the application regarding production How many, out of the ones you made, did you sell? –I may get this data from the application on distribution Can I get all data from one application and even cross reference over, say, serial number? (yes using SAP)

4. 1-4 An example of a database See book on page 4.

5. 1-5 Types of database applications Transactional –Single user, multi-user/Enterprise, e-commerce Batch –Most likely has no place to modify individual record Decision support –Needs DBMS support –Reporting and data mining

6. The components of a database system user, database application, DBMS, and database (see Figure 1-6) I am not so sure about Figure 1-7, because SQL is generally part of (supported by) DBMS and is very different from all other components in the figure. 1-6

7. Figure 1-12 Functions of a DBMS 2-7

8. Figure 1-14 Component of a Database –User Data –Indexes –Metadata –Other database objects Stored procedures Triggers Functions views 1-8

9. Database defined A database is a self-describing collection of integrated tables that are computerized (mostly from page 12) –Self describing –Collection of related tables/records –computerized (my appendage) It may support adding, modifying, and deleting of tables and records through DBMS communicated using SQL A logical database is a concept. A physical database is the realization of a logical database filled with data, supported by a DBMS that runs on a computer (the hardware) 1-9

10. Other definitions of database Collection of persistent data Collection of true propositions Made up of entities, relationships, and properties Implements a data model 1-10

11. Other definitions of database (2) Collection of persistent data –Stores enterprise information over time –Outlasts the running of a computer program –Updated and retrieved in OLTP operational/production system –Offers decision support via data warehouse Collection of true propositions –Whatever stored in the database is consider as truth 1-11

12. Other definitions of database (2) Made up of entities, relationships, and properties –An entity is a person, place, event or thing, about which we wish to store information –A relationship is a connection between entities, about which we wish to store information –A relationship can be considered as a special case of entities –Entities have properties –Properties are the characteristics of an entity instance Implements a data model –Database is a collection of true propositions –Data model is an abstract, self-contained, logical representation of the user’s model (not reality!!!) 1-12

13. Database development process Generally, a database is part of one or more applications which go through the steps of requirements gathering, design, implementation, testing, deploying, maintenance, and retirement Maintenance incurs major costs (up to 70%) Database Design –Based on existing database –For a new system –Redesign All Require domain knowledge 1-13

14. History of databases Figure 1-24 Nowadays, when we say database, we mean relational database 1-14

15. 2-15

16. Testing your understanding Three concepts –Database –Database management system (DBMS) –Database system True or False MS Access is not a database True or False MS Access is not a DBMS 1-16

17. Trends Object oriented DBMS – more of a research thing -- dead XML for document processing and exchange of information –Web service for data processing –Security –Wireless –PDA Data mining and decision support systems Unstructured queries DBMS for cloud computing such as RDS from AMAZON Column oriented storing vs. row oriented store No SQL 1-17