Chapter 1 Introduction Database Management System DBMS n

Chapter 1: Introduction

Database Management System (DBMS) n DBMS contains information about a particular enterprise l Collection of interrelated data l Set of programs to access the data l An environment that is both convenient and efficient to use n Database Applications: l Banking: transactions l Airlines: reservations, schedules l Universities: registration, grades l Sales: customers, products, purchases l Online retailers: order tracking, customized recommendations l Manufacturing: production, inventory, orders, supply chain l Human resources: employee records, salaries, tax deductions n Databases can be very large. n Databases touch all aspects of our lives 1. 2

University Database Example n Application program examples l Add new students, instructors, and courses l Register students for courses, and generate class rosters l Assign grades to students, compute grade point averages (GPA) and generate transcripts n In the early days, database applications were built directly on top of file systems 1. 3

Data Models n A collection of tools for describing Data l Data relationships l Data semantics l Data constraints l n Relational model n Entity-Relationship data model (mainly for database design) n Object-based data models (Object-oriented and Object-relational) n Semistructured data model (XML) n Other older models: l l Network model Hierarchical model 1. 7

Relational Model n Relational model (Chapter 2) n Example of tabular data in the relational model Columns Rows 1. 8

A Sample Relational Database 1. 9

Data Definition Language (DDL) n Specification notation for defining the database schema Example: create table instructor ( ID char(5), name varchar(20), dept_name varchar(20), salary numeric(8, 2)) n DDL compiler generates a set of table templates stored in a data dictionary n Data dictionary contains metadata (i. e. , data about data) l Database schema l Integrity constraints 4 Primary key (ID uniquely identifies instructors) 4 Referential integrity (references constraint in SQL) – e. g. dept_name value in any instructor tuple must appear in department relation l Authorization 1. 11

SQL n SQL: widely used non-procedural language Example: Find the name of the instructor with ID 22222 select name from instructor where instructor. ID = ‘ 22222’ l Example: Find the ID and building of instructors in the Physics dept. select instructor. ID, department. building from instructor, department where instructor. dept_name = department. dept_name and department. dept_name = ‘Physics’ l n Application programs generally access databases through one of Language extensions to allow embedded SQL l Application program interface (e. g. , ODBC/JDBC) which allow SQL queries to be sent to a database n Chapters 3, 4 and 5 l 1. 12

Database Design? n Is there any problem with this design? 1. 14

The Entity-Relationship Model n Models an enterprise as a collection of entities and relationships l Entity: a “thing” or “object” in the enterprise that is distinguishable from other objects 4 Described l by a set of attributes Relationship: an association among several entities n Represented diagrammatically by an entity-relationship diagram: What happened to dept_name of instructor and student? 1. 15

History of Database Systems n 1950 s and early 1960 s: l Data processing using magnetic tapes for storage 4 Tapes l provided only sequential access Punched cards for input n Late 1960 s and 1970 s: l Hard disks allowed direct access to data l Network and hierarchical data models in widespread use l Ted Codd defines the relational data model 4 Would 4 IBM 4 UC l win the ACM Turing Award for this work Research begins System R prototype Berkeley begins Ingres prototype High-performance (for the era) transaction processing 1. 16

History (cont. ) n 1980 s: Research relational prototypes evolve into commercial systems 4 SQL becomes industrial standard l Parallel and distributed database systems l Object-oriented database systems n 1990 s: l Large decision support and data-mining applications l Large multi-terabyte data warehouses l Emergence of Web commerce l n Early 2000 s: XML and XQuery standards l Automated database administration n Later 2000 s: l Giant data storage systems 4 Google Big. Table, Yahoo PNuts, Amazon, . . l 1. 17

End of Chapter 1 1. 18

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