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Fundamentals of Database Systems

Seventh Edition

Chapter 1

Databases and Database Users

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Learning Objectives

1.1 Types of Databases and Database Applications

1.2 Basic Definitions

1.3 Typical D B M S Functionality

1.4 Example of a Database (University)

1.5 Main Characteristics of the Database Approach

1.6 Types of Database Users

1.7 Advantages of Using the Database Approach

1.8 Historical Development of Database Technology

1.9 Extending Database Capabilities

1.10 When Not to Use Databases

Types of Databases and Database Applications

Traditional Applications:

Numeric and Textual Databases

More Recent Applications:

Multimedia Databases

Geographic Information Systems (G I S)

Biological and Genome Databases

Data Warehouses

Mobile databases

Real-time and Active Databases

First part of book focuses on traditional applications

A number of recent applications are described later in the book (for example, Chapters 24,25,26,27,28,29)

Recent Developments (1 of 2)

Social Networks started capturing a lot of information about people and about communications among people-posts, tweets, photos, videos in systems such as:

Facebook

Twitter

Linked-In

All of the above constitutes data

Search Engines- Google, Bing, Yahoo : collect their own repository of web pages for searching purposes

Recent Developments (2 of 2)

New Technologies are emerging from the so-called non-database software vendors to manage vast amounts of data generated on the web:

Big Data storage systems involving large clusters of distributed computers (Chapter 25)

N O S Q L (Not Only S Q L) systems (Chapter 24)

A large amount of data now resides on the “cloud” which means it is in huge data centers using thousands of machines.

Basic Definitions

Database:

A collection of related data.

Data:

Known facts that can be recorded and have an implicit meaning.

Mini-world:

Some part of the real world about which data is stored in a database. For example, student grades and transcripts at a university.

Database Management System (D B M S):

A software package/ system to facilitate the creation and maintenance of a computerized database.

Database System:

The D B M S software together with the data itself. Sometimes, the applications are also included.

Impact of Databases and Database Technology

Businesses: Banking, Insurance, Retail, Transportation, Healthcare, Manufacturing

Service Industries: Financial, Real-estate, Legal, Electronic Commerce, Small businesses

Education: Resources for content and Delivery

More recently: Social Networks, Environmental and Scientific Applications, Medicine and Genetics

Personalized Applications: based on smart mobile devices

Figure 1.1 Simplified database system environment

Typical D B M S Functionality

Define a particular database in terms of its data types, structures, and constraints

Construct or Load the initial database contents on a secondary storage medium

Manipulating the database:

Retrieval: Querying, generating reports

Modification: Insertions, deletions and updates to its content

Accessing the database through Web applications

Processing and Sharing by a set of concurrent users and application programs – yet, keeping all data valid and consistent

Application Activities Against a Database

Applications interact with a database by generating

Queries: that access different parts of data and formulate the result of a request

Transactions: that may read some data and “update” certain values or generate new data and store that in the database

Applications must not allow unauthorized users to access data

Applications must keep up with changing user requirements against the database

Additional D B M S Functionality

D B M S may additionally provide:

Protection or Security measures to prevent unauthorized access

“Active” processing to take internal actions on data

Presentation and Visualization of data

Maintenance of the database and associated programs over the lifetime of the database application

Called database, software, and system maintenance

Example of a Database (with a Conceptual Data Model) (1 of 2)

Mini-world for the example:

Part of a UNIVERSITY environment.

Some mini-world entities:

STUDENTs

COURSEs

SECTIONs (of COURSEs)

(academic) DEPARTMENTs

INSTRUCTORs

Example of a Database (with a Conceptual Data Model) (2 of 2)

Some mini-world relationships:

SECTIONs are of specific COURSEs

STUDENTs take SECTIONs

COURSEs have prerequisite COURSEs

INSTRUCTORs teach SECTIONs

COURSEs are offered by DEPARTMENTs

STUDENTs major in DEPARTMENTs

Note: The above entities and relationships are typically expressed in a conceptual data model, such as the ENTITY-RELATIONSHIP data model (see Chapters 3, 4)

Figure 1.2 Example of a simple database (1 of 4)

COURSE

Course_name	Course_number	Credit_hours	Department
Intro to Computer Science	C S1310	4	C S
Data Structures	C S3320	4	C S
Discrete Mathematics	MATH2410	3	MATH
Database	C S3380	3	C S

Figure 1.2 Example of a simple database (2 of 4)

SECTION

Section_identifier	Course_number	Semester	Year	Instructor
85	MATH2410	Fall	07	King
92	CS1310	Fall	07	Anderson
102	CS3320	Spring	08	Knuth
112	MATH2410	Fall	08	Chang
119	CS1310	Fall	08	Anderson
135	CS3380	Fall	08	Stone

Figure 1.2 Example of a simple database (3 of 4)

GRADE_REPORT

Student_number	Section_identifier	Grade
17	112	B
17	119	C
8	85	A
8	92	A
8	102	B
8	135	A

Figure 1.2 Example of a simple database (4 of 4)

PREREQUISITE

Course_number	Prerequisite_number
C S3380	C S3320
C S3380	MATH2410
C S3320	C S1310

Main Characteristics of the Database Approach (1 of 3)

Self-describing nature of a database system:

A D B M S catalog stores the description of a particular database (e.g. data structures, types, and constraints)

The description is called meta-data*.

This allows the D B M S software to work with different database applications.

Insulation between programs and data:

Called program-data independence.

Allows changing data structures and storage organization without having to change the D B M S access programs.

* Some newer systems such as a few N O S Q L systems need no meta-data: they store the data definition within its structure making it self describing

Figure 1.3 Example of a simplified database catalog (1 of 2)

RELATIONS

Relation_name	No_of_columns
STUDENT	4
COURSE	4
SECTION	5
GRADE_REPORT	3
PREREQUISITE	2

Figure 1.3 Example of a simplified database catalog (2 of 2)

COLUMNS

Column_name	Data_type	Belongs_to_relation
Name	Character (30)	STUDENT
Student_number	Character (4)	STUDENT
Class	Integer (1)	STUDENT
Major	Major_type	STUDENT
Course_name	Character (10)	COURSE
Course_number	XXXXNNNN	COURSE
….	….	….
….	….	….
….	….	….
Prerequisite_number	XXXXNNNN	PREREQUISITE

Note: Major_type is defined as an enumerated type with all known majors. XXXXNNNN is used to define a type with four alphabetic characters followed by four numeric digits.

Main Characteristics of the Database Approach (2 of 3)

Data Abstraction:

A data model is used to hide storage details and present the users with a conceptual view of the database.

Programs refer to the data model constructs rather than data storage details

Support of multiple views of the data:

Each user may see a different view of the database, which describes only the data of interest to that user.

Main Characteristics of the Database Approach (3 of 3)

Sharing of data and multi-user transaction processing:

Allowing a set of concurrent users to retrieve from and to update the database.

Concurrency control within the D B M S guarantees that each transaction is correctly executed or aborted

Recovery subsystem ensures each completed transaction has its effect permanently recorded in the database

O L T P (Online Transaction Processing) is a major part of database applications. This allows hundreds of concurrent transactions to execute per second.

Database Users

Users may be divided into

Those who actually use and control the database content, and those who design, develop and maintain database applications (called “Actors on the Scene”), and

Those who design and develop the D B M S software and related tools, and the computer systems operators (called “Workers Behind the Scene”).

Database Users – Actors on the Scene (1of 2)

Actors on the scene

Database administrators:

Responsible for authorizing access to the database, for coordinating and monitoring its use, acquiring software and hardware resources, controlling its use and monitoring efficiency of operations.

Database Designers:

Responsible to define the content, the structure, the constraints, and functions or transactions against the database. They must communicate with the end-users and understand their needs.

Database End Users (1 of 2)

Actors on the scene

End-users: They use the data for queries, reports and some of them update the database content. End-users can be categorized into:

Casual: access database occasionally when needed

Naïve or Parametric: they make up a large section of the end-user population.

They use previously well-defined functions in the form of “canned transactions” against the database.

Users of Mobile Apps mostly fall in this category

Bank-tellers or reservation clerks are parametric users who do this activity for an entire shift of operations

Social Media Users post and read information from websites

Database End Users (2 of 2)

Sophisticated:

These include business analysts, scientists, engineers, others thoroughly familiar with the system capabilities.

Many use tools in the form of software packages that work closely with the stored database.

Stand-alone:

Mostly maintain personal databases using ready-to-use packaged applications.

An example is the user of a tax program that creates its own internal database.

Another example is a user that maintains a database of personal photos and videos.

Database Users – Actors on the Scene (2 of 2)

System Analysts and Application Developers

This category currently accounts for a very large proportion of the I T work force.

System Analysts: They understand the user requirements of naïve and sophisticated users and design applications including canned transactions to meet those requirements.

Application Programmers: Implement the specifications developed by analysts and test and debug them before deployment.

Business Analysts: There is an increasing need for such people who can analyze vast amounts of business data and real-time data (“Big Data”) for better decision making related to planning, advertising, marketing etc.

Database Users – Actors behind the Scene

System Designers and Implementors: Design and implement D B M S packages in the form of modules and interfaces and test and debug them. The D B M S must interface with applications, language compilers, operating system components, etc.

Tool Developers: Design and implement software systems called tools for modeling and designing databases, performance monitoring, prototyping, test data generation, user interface creation, simulation etc. that facilitate building of applications and allow using database effectively.

Operators and Maintenance Personnel: They manage the actual running and maintenance of the database system hardware and software environment.

Advantages of Using the Database Approach (1 of 2)

Controlling redundancy in data storage and in development and maintenance efforts.

Sharing of data among multiple users.

Restricting unauthorized access to data. Only the D B A staff uses privileged commands and facilities.

Providing persistent storage for program Objects

E.g., Object-oriented D B M S s make program objects persistent– see Chapter 12.

Providing Storage Structures (e.g. indexes) for efficient Query Processing – see Chapter 17.

Advantages of Using the Database Approach (2 of 2)

Providing optimization of queries for efficient processing.

Providing backup and recovery services.

Providing multiple interfaces to different classes of users.

Representing complex relationships among data.

Enforcing integrity constraints on the database.

Drawing inferences and actions from the stored data using deductive and active rules and triggers.

Additional Implications of Using the Database Approach (1 of 2)

Potential for enforcing standards:

This is very crucial for the success of database applications in large organizations. Standards refer to data item names, display formats, screens, report structures, meta-data (description of data), Web page layouts, etc.

Reduced application development time:

Incremental time to add each new application is reduced.

Additional Implications of Using the Database Approach (2 of 2)

Flexibility to change data structures:

Database structure may evolve as new requirements are defined.

Availability of current information:

Extremely important for on-line transaction systems such as shopping, airline, hotel, car reservations.

Economies of scale:

Wasteful overlap of resources and personnel can be avoided by consolidating data and applications across departments.

Historical Development of Database Technology (1 of 3)

Early Database Applications:

The Hierarchical and Network Models were introduced in mid 1960s and dominated during the seventies.

A bulk of the worldwide database processing still occurs using these models, particularly, the hierarchical model using I B M’s I M S system.

Relational Model based Systems:

Relational model was originally introduced in 1970, was heavily researched and experimented within I B M Research and several universities.

Relational D B M S Products emerged in the early 1980s.

Historical Development of Database Technology (2 of 3)

Object-oriented and emerging applications:

Object-Oriented Database Management Systems (O O D B M S s) were introduced in late 1980s and early 1990s to cater to the need of complex data processing in C A D and other applications.

Their use has not taken off much.

Many relational D B M S s have incorporated object database concepts, leading to a new category called object-relational D B M S s (O R D B M S s)

Extended relational systems add further capabilities (e.g. for multimedia data, text, X M L, and other data types)

Historical Development of Database Technology (3 of 3)

Data on the Web and E-commerce Applications:

Web contains data in H T M L (Hypertext markup language) with links among pages.

This has given rise to a new set of applications and E-commerce is using new standards like X M L (eXtended Markup Language). (see Chapter 13).

Script programming languages such as P H P and JavaScript allow generation of dynamic Web pages that are partially generated from a database (see Chapter 11).

Also allow database updates through Web pages

Extending Database Capabilities (1 of 3)

New functionality is being added to D B M S s in the following areas:

Scientific Applications – Physics, Chemistry, Biology - Genetics

Earth and Atmospheric Sciences and Astronomy

X M L (eXtensible Markup Language)

Image Storage and Management

Audio and Video Data Management

Data Warehousing and Data Mining – a very major area for future development using new technologies (see Chapters 28-29)

Spatial Data Management and Location Based Services

Time Series and Historical Data Management

The above gives rise to new research and development in incorporating new data types, complex data structures, new operations and storage and indexing schemes in database systems.

Extending Database Capabilities (2 of 3)

Background since the advent of the 21st Century:

First decade of the 21st century has seen tremendous growth in user generated data and automatically collected data from applications and search engines.

Social Media platforms such as Facebook and Twitter are generating millions of transactions a day and businesses are interested to tap into this data to “understand” the users

Cloud Storage and Backup is making unlimited amount of storage available to users and applications

Extending Database Capabilities (3 of 3)

Emergence of Big Data Technologies and N O S Q L databases

New data storage, management and analysis technology was necessary to deal with the onslaught of data in petabytes a day (10**15 bytes or 1000 terabytes) in some applications – this started being commonly called as “Big Data”.

Hadoop (which originated from Yahoo) and Mapreduce Programming approach to distributed data processing (which originated from Google) as well as the Google file system have given rise to Big Data technologies (Chapter 25). Further enhancements are taking place in the form of Spark based technology.

N O S Q L (Not Only S Q L- where S Q L is the de facto standard language for relational D B M S s) systems have been designed for rapid search and retrieval from documents, processing of huge graphs occurring on social networks, and other forms of unstructured data with flexible models of transaction processing (Chapter 24).

When not to use a D B M S (1 of 2)

Main inhibitors (costs) of using a D B M S:

High initial investment and possible need for additional hardware.

Overhead for providing generality, security, concurrency control, recovery, and integrity functions.

When a D B M S may be unnecessary:

If the database and applications are simple, well defined, and not expected to change.

If access to data by multiple users is not required.

When a D B M S may be infeasible:

In embedded systems where a general purpose D B M S may not fit in available storage

When not to use a D B M S (2 of 2)

When no D B M S may suffice:

If there are stringent real-time requirements that may not be met because of D B M S overhead (e.g., telephone switching systems)

If the database system is not able to handle the complexity of data because of modeling limitations (e.g., in complex genome and protein databases)

If the database users need special operations not supported by the D B M S (e.g., G I S and location based services).

Chapter Summary

Types of Databases and Database Applications

Basic Definitions

Typical D B M S Functionality

Example of a Database (University)

Main Characteristics of the Database Approach

Types of Database Users

Advantages of Using the Database Approach

Historical Development of Database Technology

Extending Database Capabilities

When Not to Use Databases