database beginnings

Database Beginnings

CIS 121 – Computer Concepts II

Instructor: Ron Christensen

04/19/23 CIS 121 - Portland Community College

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What is Data?

• Data are facts about things, places, events

• Facts about data are called metadata

• Data are building blocks for information


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Common Data Applications

• Word Processors – Like fifth generation language, very difficult to track

• Spreadsheets – Mostly two dimensional. When items change, multiple spreadsheets become problem some.

• Databases – More efficient, real-time, on-line.


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DBMS – Database Management System

• DBMS software…– Manages metadata– Organizes data– Enforces security– Manages access to data and metadata– Enforces integrity


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Database

Information System

Figure 1.2

Input Output


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What is a Database (Black Box)?

• A computer accepts input, processes it according to some rules, and makes output.

• Everything will be represented as data, including the input and the output

• So what the DBMS is doing is taking the data produced (the input) and converting it into information (the output)


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Relational DBMS

• Relational refers to the method of organizing data, i.e. in tables

• Developed in the1970s• Most common of several different types of

DBMS systems– Hierarchical– Network– Object


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Microsoft ACCESS

• Relational DBMS software for Windows

• Available as part of MS-Office


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Type of Databases

• Production Database– Transaction oriented– Lots of well-defined read/write/update actions

• Decision Support Database– Query oriented– Complex queries– Few updates or writes


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A Bigger Picture…

• Databases are a critical part of information systems

• Information systems help people solve problems

• Your personal database and web page will form the basis of a personal information system


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Database

DBMS

Operating System

Software

Hardware

People

ApplicationPrograms

WriteandUse

Designand

Manage

Information SystemFigure 1.2


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Entities

• Entities are anything about which you want to know something– People, places, things, events, concepts

• Data are facts about entities


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Entity Sets

• Entity sets are collections of related entities. Entities are related by their classification:

• student entities are related by the fact that they are all students

• invoice entities are related by the fact that they are all invoices

• car entities are related by the fact that they are all cars


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Entity Sets, cont.•Entity sets are named as a broad definition of the whole entity.

•Entity and Entity set names are singular.•Entity and Entity set names are capitalized.

Examples:An entity named HR contains HR entities.An entity named EMPLOYEE contains employee records.An entity named DEPARTMENT contains department

records.


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Entity Sets, cont.

• Entity Sets can only contain related records– a STUDENT entity set may not contain

INVOICE data– a DEPARTMENT entity set may not contain

invoice data– a PRODUCT entity set may not contain

employee data

…. And so on


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Relational Databases

• Data is stored in TABLES (also called relational sets)

• Tables are collections of attributes for related records

• The reality is that lots of different things get stuffed into a table for a variety of reasons

• (Tables are another word for entity sets)


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Database Tables

• A database table is used to store a record (or tuple)– An entity set is a collection of related records

• An record is anything you want to keep track of, so an entity may be a person, place, thing, event, etc.

– (Record is another word for Entity)


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Database Table Components• At the conceptual level, a database table may be

viewed as a matrix.– Matrix rows are also known as tuples or records

• each row contains an record

– Matrix columns are also called fields or attributes.• Each column (field) contains the record’s attribute values


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Attributes

• Attributes are the characteristics that describe records– A STUDENT record may be described by

attributes that may include... • social security number• name• address• date of birth• major


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Records, Attributes, Data

• Records are things about which you want to know something, e.g. STUDENT

• Attributes describe something about the entity, e.g. the name of the student

• Data are the values of the attributes, e.g. DOE, JOHN


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Null

• A null is an absence of value

• A null is NOT– A blank– A zero

• A null has several meanings in a database– Value does not exist– Value is not known


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Attribute Names

• Attribute names are capitalized.

• For documentation reasons, attribute names are composed of two parts:– the first few characters reflect the entity they

help describe. – subsequent characters are sufficiently

descriptive to identify the attribute.


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Attribute Names, cont.

• Examples of attribute names:

EMP_LNAME = employee last name

STU_GPA = student grade point average

PROD_CODE = product code

CUST_LNAME = customer last name

INV_NUM = invoice number


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Keys

• Primary Key (PK)– an attribute (or combination of attributes) that

uniquely identifies each row (tuple) in a table.• A PK composed of two or more attributes is known

as a composite PK.

• Foreign Key (FK)– an attribute in one table whose values match the

PK values in a related table or whose “values” are null.

• FKs are used to link (connect) related tables.


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Data Integrity.

• Entity Integrity – PK uniquely identifies each entity in a table

• PK may not include nulls

• Referential Integrity– FK values in one table match the PK values in the

related table• FK may not include nulls


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A Conceptual View of a Database Table

Named attributes (fields)

The Primary Key (PK) is a unique record identifier. If you know the PK value, you will know all of its row’s attribute values

Each row representsan record

A row is also calleda tuple.

Each row/columnintersection containsonly one of an entity’s attribute values

Each column contains the values of an attribute. The EMP_FNAME column only contains employee first names; the EMP_PHONE may only contain employee phone numbers.

Tables are named. The table yousee here is the EMPLOYEE table.


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Entity Integrity

A table exhibits entity integrity when all of itsPrimary Key (PK) values uniquely identify eachtable row (record.)

EMPLOYEE table

1. A PK cannot contain duplicate values2. A PK cannot contains nulls

Note: A null indicates the absence of a value; it is not a blank. (You create a null when you tap the ENTER key without first making an entry. A blank is created when you tap the space bar and then tap the ENTER key.)


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Foreign keys (FK) and Referential Integrity

To maintain referential integrity, a foreign key (FK) must reference an existing PK value in a related table it may be null.

A Foreign Key (FK) is an attribute located in one table that “points to” a Primary Key (PK) in a related table. The use of FKs allows you relate one table to another.

INVOICE table

LINE table


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1. Simple (atomic)

2. Composite

A. Single-valued

B. Multi-valued

Derived

Attribute types


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Simple (Atomic) Attributes

• A simple (atomic) attribute cannot be decomposed into meaningful components

• Examples:

– The attribute EMP_LNAME cannot be decomposed, because you cannot subdivide EMP_LNAME into a set of new attributes.

– The attribute PROD_PRICE cannot be decomposed, because you cannot subdivide PROD_PRICE into a new set of attributes.


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Simple (Atomic) Attributes, cont.

Simple attributes may be ….

• single-valued

or

• multi-valued


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Simple (Atomic) Attributes, cont.

• Single-valued simple attributes• Example: an employee can have only one gender,

so EMP_GENDER is a single-valued attribute. The attribute EMP_GENDER cannot be decomposed, so it is a simple attribute.

• Multi-valued simple attributes• Example: an employee can have many degrees,

so EMP_DEGREE is multi-valued. The attribute EMP_DEGREE cannot be decomposed, so it is a simple attribute.


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Composite Attributes

•A composite attribute can be decomposed into meaningful components

• Example: an employee’s address, shown as

123 East Main Street, Nashville, TN 32123

may be decomposed into

EMP_ADDRESS = 123 East Main Street

EMP_CITY = Nashville

EMP_STATE = TN

EMP_ZIP = 32123


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Composite Attributes, cont.

A composite attribute may be ….

• single-valued

or

• multi-valued


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Composite Attributes, cont.

• single-valued composite attributes– Example: an employee can have only one date of

birth, so EMP_DOB is single-valued. But the attribute EMP_DOB can be decomposed into year, month, and day, so it is a composite attribute.

• multi-valued composite attributes– Example: an employee can have more than one

address, so EMP_ADDRESS may be multi-valued. The attribute EMP_ADDRESS can be decomposed into street address, city, state, and ZIP code, so it is a composite attribute.


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Attribute Storage• Each table row/column intersection contains a

single attribute value for a single entity.– Ideally, attributes are simple and single-valued.– Single-valued composite attributes are acceptable

• but composite attributes may make queries more complex and may impose reporting limitations.

– Multi-valued attributes, either simple or composite, may

• create structural problems• make queries more complex and may impose reporting

limitations.• May be necessary for a variety of reasons, but should be

avoided where possible


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Multi-valued Attribute Storage

• Multi-valued attributes are sometimes stored as – strings

• this approach yields query complexity and reporting limitations

– multiple attributes• this approach yields structural problems

• Ideally, multi-valued attributes are handled through the use of composite tables.


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Multi-valued Attributes Stored As Strings

Multi-valued attribute

Poor practice: Makes it difficult to generate queries such as“How many employees have earned BA or MBA degrees?”


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Storing Multi-valued Attributes In Separate Columns

Poor structure: many nulls table structure must be altered when additional degrees are earned


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Composite Tables

• Multi-valued attributes can generate many nulls, increasing uncertainty about the data

• One solution is to add another table, called a composite table or bridge table

• It is often better to use more tables rather than poor attributes in fewer tables


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Table name: DEGREE

Table name:EMPLOYEE

Table name:EDUCATION

A Composite Table (EDUCATION) is UsedTo Convert M:N Relationships To 1:M Relationships


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Supertype/Subtype Relationships Are UsedTo Eliminate or Control the Occurrence of Nulls

A table with many nulls

Subtype. (Table name: PILOT)

Supertype. (Table name: EMPLOYEE


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Relationships

• Tables can be related to each other in a variety of ways– 1:1 Relationships– 1:M Relationships– M:N Relationships– Recursive Relationships

• Tables are related by their PKs and FKs


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1:1 Relationships

• Entity in one table is related to only one entity in another table

• Example– STUDENT : SOCIAL SECURITY NUMBER

Each student has only one Social Security Number, each Social Security Number refers to only one student


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1:M Relationships

• Entity in one table is related to many entities in another table

• Example– STUDENT : TUITION INVOICE

Each student may have several tuition invoices, each tuition invoice is assigned to only one student


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M:N Relationships

• An entity can occur more than once on both sides of the relationship – causes several different problems in databases

• Example:– STUDENT : CLASS

Each student may register for many classes, each class may contain many students


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Some Issues with M:N

• May signal redundant data, resulting in anomalies– Modification anomaly– Deletion anomaly

• Keep it simple: DO NOT IMPLEMENT M:N RELATIONSHIPS. Use composite tables instead


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Recursive Relationships

• Entity is related to itself

• Examples– TEAM : TEAMTeams in an athletic league play each other

– CLASS : CLASSSome classes are pre-requisites for others


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Optional (vs. Mandatory) Relationships

• Optional relationships occur when entities in two tables may be related, but do not need to be.

• Example (Optional Relationship): – STUDENT : SOCIAL SECURITY NUMBERA student is not required to have a social security number

• Example (Mandatory Relationship)– STUDENT : CLASSA student must be registered in a class to be a student


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End of Lecture

database beginnings

Documents

portland community college

entity setsentity sets

method of organizing

student entities

studentsinvoice entities

invoicescar entities

database beginningscis

problemsyour personal