2 - Database - Fundamentals

8/13/2019 2 - Database - Fundamentals

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Connecting with Computer

Science, 2e

Chapter 6Database Fundamentals


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Connecting with Computer Science, 2e 2

Objectives

In this chapter you will: Consider the widespread use of databases Take a brief tour of database development history Learn basic database concepts Be introduced to popular database management

software

See how normalization makes your data moreorganized


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Why You Need to Know About...

Databases Data must be organized Effective computer professionals know correct

database design

Normalization Ensures an accurate and reliable database

Structured Query Language (SQL) Describes how information is retrieved from relational

database


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Database Applications

Database Data logically related and organized into a file or set

of files to allow access and use

Database applications Student grading and library inventory Genealogy studies and Social Security payments Real estate sales, video store rentals, and retail sales Space shuttle missions

Database development Essential part of computer professionals daily life



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Brief History of Database Management

Systems 1970 to 1975

Work of IBM employees E. F. Codd and C. J. Date Created theoretical model for designing data structures Model became foundation for database design Software for organizing and sorting data System R by IBM and Ingres by UC-Berkeley Structured Query Language (SQL) SQL: database standard Database management system (DBMS) for PCs

1978 C. Wayne Ratliff of Martin Marietta develops Vulcan



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Systems (contd.) 1980 to the present

Vulcan renamed dBASE II (no dBase I) Popularity of dBASE II inspires other companies

Paradox, Microsoft Access, and FoxPro Databases become essential for business

Corporate decision making Systems: inventory management to customer support


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Table 6-1, Popular database management systems


Systems (contd.)


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Database Management System

Fundamentals Six main DBMS functions

Manage database security Manage multiple users access to the database Manage database backup and recovery Ensure data integrity Provide an end-user interface to the database Provide a query language allowing users to modify

and view database information easily


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Database Concepts

Basic database elements Database: collection of one or more tables (entities) Table or entity: divided into rows and columns Row (record or tuple): collection of columns Column (field or attribute): represents specific

information

Domain: set of possible column values


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Figure 6-1, A database table consists of rows and columns

Database Concepts (contd.)


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Indexes

Special files occupying their own space Specify columns determining how information stored

in a table can be accessed more efficiently

Examples: music database and the telephone book Advantages

Flexibility: many different columns to sort against Searching and retrieval speeds up

Disadvantages Extra storage space Updating takes longer


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An Example of Indexing

Figure 6-2, You use database concepts in your everyday life


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An Example of Indexing (contd.)

Each database row has similar attributes Sort key: one or more columns used to determine

the datas sort order

One key or a combination of keys determines sortorder

Database information is stored in natural orsequential order

Order of records displayed equals the order recordsare entered


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Figure 6-3, Database records sorted by using the UPC column as a key



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Figure 6-4, Database records sorted by Brand_Name and Description



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Normalization

Set of rules dictating database design Eliminates duplication and inconsistencies Process: sequence of stages called normal forms

Five normal forms Third normal form provides sufficient structure

Three database design problems solved Representation of certain real-world items Redundancies (repetitions) in data Excluded and inconsistent information


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Preparing for Normalization: Gathering

Columns Make a list of all pertinent fields (columns or

attributes)

Source of fields: end-user reports or song inventory Write fields on the column list

Review user-specified input forms Convert each field from the report to column in table


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Figure 6-5, End-user report with table columns highlighted


Columns (contd.)


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Figure 6-6, Additional table columns can be gleaned

from input forms


Columns (contd.)


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Columns (contd.) Reconcile fields in report to column list Create tables of columns by combining associated

fields

Logically group related information Example: information on artist and song files

Gather data to create physical music database


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First Normal Form

Unnormalized table Row-column intersection with two or more values

First normal form (1NF) eliminates redundancies Create new record for duplicated column Fill in blanks so all columns in record have a value Columns with duplications: Album_Num,

Album_Name, Artist_Code, Artist_Name,

Media_Type, and Genre_Code Remaining redundancies are addressed later


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Second Normal Form

Next steps:Assign a primary key to the table Identify functional dependencies within the table

Primary key (PK) Column or combination of columns (composite)

uniquely identifying a row within a table

Examples: Student ID or Artist_Code


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Second Normal Form (contd.)

Determinant: column(s) used to determine valueassigned to another column in the same row

Example: Artist_Code determinant for Artist_Name Functional dependency: columns value dependenton another columns value

Each value of first column is matched to single valuein second

Example: Artist_Name functionally dependent onArtist_Code

Composite key: primary key made up of more thanone column



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Second normal form (2NF) First normal form and non-PK columns functionally

dependent on PK

Creating 2NF Determine columns not dependent on PK

Remove columns and place in new table Default 2NF: table without composite PK

Primary 2NF benefit: save disk space


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Figure 6-10, 2NF: Remove any columns that arent dependent

on the composite primary key and create a new table



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Third Normal Form

Third normal form (3NF) Eliminate transitive dependencies

Column dependent on another column not part of PK Example: Genre_Desc depends on Genre_Code

Each nonkey field should be a fact about the PK


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Figure 6-11, Songs table with the Genre_Desc column added

Third Normal Form (contd.)


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Creating 3NF Remove transitive dependencies Place removed columns in new table

Primary 3NF benefit: eliminates repetition and savesdisk space


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Figure 6-12, Songs and Genre tables in 3NF



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Figure 6-13, Eliminating repetition saves storage space



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The Database Design Process

Six steps to designing a normalized database Example:

Creation of student-grading system


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Step 1: Investigate and Define

Investigate and research modeled information Define purposes and uses of the database Use any documents end users work with to

complete tasks

Involve end users in design process Example: student-grading system based on a course

syllabus


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Step 2: Make a Master Column List

Create list of fields for information Possible field properties:

Field name Data type (char, varchar, number, date, etc.) Length Number of decimal places (if any)

Review users documents for fields Forms and reports good source for fields

Example fields: Student ID, First Name, Last Name, E-Mail, Grade Level, Grade Level Description, Homework

Average, Quiz Average, Test Average



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Step 3: Create the Tables

Logically group defined columns into tables Heart of design process Relies heavily on normalization rules

Main rules in database design: 1NF 3NF Table in 3NF: well defined

Normalizing databases Like cleaning a closet


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Figure 6-14, Tables created for the student-grading system

Step 3: Create the Tables (contd.)


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Step 4: Work on Relationships

Relationship: defines table relations Two types of relationships discussed in this chapter

One-to-many (1:M) One-to-one (1:1)

Primary and foreign keys are defined in each of thetables

Primary key (PK): determinant discussed earlier Foreign key (FK): column in one table is PK inanother


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Step 4: Work on Relationships (contd.)

One-to-many (1:M) Most common relationship Each record in Table A relates to multiple records in

Table B Requires that FK column(s) in many table refer to

PK column in one table

Example: Grades Table to Student Table

Copy editorChg. multipleto zero tomany?


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Figure 6-15, The relationship of Student

to Course Grade is one-to-many (1:M)



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One-to-one (1:1) For every record in Table A, there can be one and

only one matching record in Table B

Consider combining tables in 1:1 relationship Normally the two tables can be combined into one

table


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Step 5: Analyze the Design

Analyze work completed Search for design errors and refine tables as needed Follow normalization forms (ideally to 3NF) Correct any violations

ER models Visual diagram composed of entities and relationships

Entities represent the database tables Relationships show how tables relate to each other

Cardinality Shows numeric relations between entities


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Step 5: Analyze the Design (contd.)

Types of cardinality (and their notation) include: 0..1, 0:1 (zero to one) 0..M, 0:N, 0..*, 0..n (zero to many) 1..1, 1:1 (one to one) 1..M, 1:M, 1:N, 1..*, 1..n (one to many) M..1, M:1, N:1, *..1, n..1 (many to one) M..M, M:M, N:N, *..*, n..n (many to many)

Example: ER model for the student-grading system


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Figure 6-17, The student-grading system ER model in Visio

Step 5: Analyze the Design (contd.)


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Step 6: Reevaluate

Reevaluate database performance Ensure database meets all reporting and form needs Include the end users Explain each table and field being used Make sure fields are defined to users requirements Manipulate data structure with SQL commands


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Structured Query Language (SQL)

Structured Query Language (SQL) functions Manipulate data Define dataAdminister data

Many different dialects of SQL


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(contd.) SQL advantages

Reduces training time (syntax based in English) Makes applications portable (SQL is standardized) Reduces the amount of data being transferred Increases application speed

Following sections show basic SQL commands Creating tablesAdding (inserting) rows of data Querying table to select certain information


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Figure 6-18, A sample SQL statement and results


(contd.)


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CREATE TABLE Statement

CREATE TABLE statement: make a new table NULL/NOT NULL

Optional property indicates whether data required Syntax:


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CREATE TABLE Statement (contd.)

SQL statements to create table called Songs:


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INSERT INTO Statement

INSERT INTO statement: add new rows of data Requires a table name Square brackets ([]) specify optional columns Columns are on separate lines for readability

Syntax:INSERT INTO table_name [(column1,column2, . . . )]

VALUES (constant1, constant2, . . . )


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Figure 6-19, SQL INSERT INTO statement to add a record to the Songs

table and its result

INSERT INTO Statement (contd.)


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SELECT Statement

Retrieves data from one or more tables Syntax:

Specified order determines order of retrieval/display


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Figure 6-20, SQL SELECT statement to return the

name, media type, and track number for songs

SELECT Statement (contd.)


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WHERE Clause

Specifies additional criteria for retrieving data Fields should be included in fields selected

AND and OR keywordsAllow specification of multiple search criteriaAND indicates that all criteria must be met OR indicates only one criterion needs to be met


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Figure 6-21, SQL SELECT statement with a WHERE clause

and the results

WHERE Clause (contd.)


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Figure 6-22, More descriptive SQL SELECT statement with

a WHERE clause



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Figure 6-23, SQL SELECT statement with a WHERE clause and

AND versus OR



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Figure 6-24, SQL SELECT statement with an ORDER BY

clause and the results

ORDER BY Clause (contd.)


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Figure 6-25, SQL SELECT statement, using an

ORDER BY clause with the default ascending option



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Figure 6-26, SQL SELECT statement, using an ORDER BY

clause with the DESC option



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Many more options Specified on SELECT statement

Many more SQL commands used Maintaining, defining, and administering data found

within a database


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One Last Thought

Poorly organized database More of a hindrance than a benefit

Careful planning required How data will be structured and storedApplying normalization rules Using the right SQL statements to extract the kind of

information desired

Database Powerful tool used in many areas

Including business and computing


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Summary

Database Collection of logically related records

DBMS Software used to design, manage, and interface with

databases

Indexes Files that revise default sequential order of data

Normalization Process of removing data redundancies


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Summary (contd.)

Data is normalized with five normal forms First three normal forms most important

Primary key Uniquely identifies table entries

Foreign key Primary keys in other tables

Entity relationship model Visual diagram of tables and relationships


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Summary (contd.)

1:M and 1:1 notations indicate cardinality Six-step database design process Structured Query Language (SQL)

Manipulates, defines, and administers data Basic SQL statements

CREATE TABLE, INSERT INTO, SELECT

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2 - Database - Fundamentals