L7 data model and dbms architecture

Sep 27, 2013Download as ppt, pdf5 likes923 views

This document discusses database models and database systems architecture. It describes hierarchical, network, relational, entity-relationship, and object-relational database models. It also discusses database management systems, how they are used to access and manipulate databases based on different data models, and how database systems are typically architected in mainframe, personal, and client-server configurations.

Database ModelsDatabase Models
Database Systems ArchitectureDatabase Systems Architecture
Version 1.0Version 1.0
1Rushdi Shams, Dept of CSE, KUET

 Database is structured collection of
records of data stored in a computer
system
 Database Management System (DBMS) is
a computer software designed to
manage (Access/Manipulate/Duplicate)
database based on various Data
Models.
Rushdi Shams, Dept of CSE, KUET
2

Rushdi Shams, Dept of CSE, KUET
3
Database

 A data model is a formal description of
how data maybe structure, represented,
and accessed
 A database model is a theory or
specification describing how a database
is structured and can be used
Rushdi Shams, Dept of CSE, KUET
4

1. Hierarchical Model
2. Network Model
3. Relational Model
4. Entity-Relationship Model
5. Object Relational Model
Rushdi Shams, Dept of CSE, KUET
5

 Organized in Tree Structure
 Allows repeating information using
parent/child relationships
 Each parent can have many children but
a child will have only one parent
Rushdi Shams, Dept of CSE, KUET
6

Rushdi Shams, Dept of CSE, KUET
7
Customer Data
Name Address Phone Pointer to Checking
Acct. Data
Pointer to Auto
Loan Data
Maria Chavez 1441 Adams Court 605-777-8992
John Severson 8988 Grover Road 605-898-2314
Harold Brown 3511 Pluto Drive 605-666-3298
Checking Account Data
Acct. Number Current Balance Date Last
Transaction
986-335 445.11 07/11/03
988-310 2988.44 07/01/03
355-822 898.14 06/15/03
Auto Loan Data
Acct. Number Current Balance Date Last Pmt
100988 5676 06/15/03
101732 1545.33 07/01/03
Parent
Data
Child
Data
Pointer

Rushdi Shams, Dept of CSE, KUET
8
 Employee has many children
 But a child has only one parent

Rushdi Shams, Dept of CSE, KUET
9
 a is boss of b and d
 b is boss of c

 Allows each record to have multiple
parent and multiple children records
 More natural modelling than
hierarchical model
 But network model failed-
1. IBM made an improvement on
hierarchical model making it semi-
networked
2. Displaced by relational model, which
offered higher level of interface
Rushdi Shams, Dept of CSE, KUET
10

 Based on predicate logic and set theory
 Enforced database integrity
 Data are operated upon by means of
relational algebra
 Designs relations (tables) by
normalization
 Accessing data differs according to the
DBMS
Rushdi Shams, Dept of CSE, KUET
11

 The basic building blocks of this model
is-
1. Data type
2. Rows
3. Columns
4. Values
 Rows are called body and columns are
called heading
Rushdi Shams, Dept of CSE, KUET
12

 Illustrates logical database
 Commonly aids relational database
design
 End product of the model is Entity
Relation Diagram (ERD)
Rushdi Shams, Dept of CSE, KUET
13

 Relational model but allows user to
integrate a database with their own data
types and methods
 Mostly, external software runs over
traditional DBMS to provide this
functionality
 Polymorphism, inheritance, function
overloading, etc are present
Rushdi Shams, Dept of CSE, KUET
15

 Mainframe databases
• Both DBMS and applications run on mainframe
computer
• Users access database and applications using
terminals
 Personal databases
• Both DBMS and applications run on user’s
workstation
 Client/server databases
• DBMS runs on central server
• Applications run on user’s (client) workstation
Rushdi Shams, Dept of CSE, KUET
16

 Handling server and client failures
 Processing transactions
 Handling high data volumes
 Providing security
 Servicing multiple simultaneous users
Rushdi Shams, Dept of CSE, KUET
17

 Enterprise Edition (on central DB server)
 Express Edition
Or
 Oracle Personal Edition
 Personal database that acts just like a
client/server database
Rushdi Shams, Dept of CSE, KUET
18

 SQL*Plus & PL/SQL
 Developer
 Procedure Builder
 Form Builder
 Report Builder
 Graphics Builder
 Project Builder
Rushdi Shams, Dept of CSE, KUET
19

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Syntax and semanticsRushdi Shams

This document discusses syntax and natural language processing. It begins with an introduction on natural languages, grammar, and how understanding grammar is important for developing NLP systems. It then discusses the components of a language, including the lexicon, categorization of parts of speech, and grammar rules. Several examples of syntactic trees are provided to illustrate parsing sentences and representing syntactic structure. The document also discusses ambiguity, constituents, constructing grammar rules for noun phrases and adjectives, and some difficulties in natural language processing like anaphora, indexicality, and metonymy.

Propositional logicRushdi Shams

This document discusses propositional logic and knowledge representation. It introduces propositional logic as the simplest form of logic that uses symbols to represent facts that can then be joined by logical connectives like AND and OR. Truth tables are presented as a way to determine the truth value of propositions connected by these logical operators. The document also discusses concepts like models of formulas, satisfiable and valid formulas, and rules of inference like modus ponens and disjunctive syllogism that allow deducing new facts from initial propositions. Examples are provided to illustrate each concept.

Probabilistic logicRushdi Shams

This document discusses probabilistic logic and inference. It defines conditional probability and the product rule. It then shows examples of computing probabilities of events occurring together or conditionally, such as the probability of a toothache or the probability of a cavity given a toothache. The document also defines Bayes' rule for calculating conditional probabilities and shows an example of how a doctor could use it to determine the probability that a patient has meningitis given that they have a stiff neck.

L15 fuzzy logicRushdi Shams

Fuzzy logic is a form of multivalued logic that deals with approximate reasoning rather than binary logic. It allows intermediate values between conventional evaluations like true/false, yes/no, or 0/1. Fuzzy logic variables can have membership values between 0 and 1 and are not constrained to two truth values. It has been applied to fields like control theory and artificial intelligence. Fuzzy logic uses IF-THEN rules to represent knowledge with linguistic terms rather than precise quantitative values and allows for gradual transitions between categories.

Knowledge structureRushdi Shams

This document discusses knowledge representation and artificial intelligence. It describes how knowledge can be captured in atomic units and represented in a knowledge base that allows for inference of new facts. Examples of representing travel directions, family relationships, and employment status are provided. The structure of a knowledge base that contains facts and rules to seek new knowledge through queries is described. The document also discusses representing domain knowledge through semantic networks and ontologies that organize concepts in a hierarchy from abstract to specific.

Knowledge representationRushdi Shams

This document discusses propositional and first-order logic. It begins by introducing propositional logic and its limitations in representing knowledge. It then describes how first-order logic builds on propositional logic by adding objects, relations, and functions to increase its expressiveness. The syntax of first-order logic is explained, including constants, predicates, functions, variables, and quantifiers. Examples are given of atomic and complex sentences in first-order logic. Universal and existential quantification are defined along with common mistakes to avoid when using them. The document aims to explain the key concepts and differences between propositional and first-order logic.

First order logicRushdi Shams

The document discusses first-order logic (FOL) and its advantages over propositional logic for representing knowledge. It introduces the basic elements of FOL syntax, such as constants, predicates, functions, variables, and connectives. It provides examples of FOL expressions and discusses how objects and relations between objects can be represented. It also covers quantification in FOL using universal and existential quantifiers.

Belief functionRushdi Shams

This document provides an introduction to Dempster-Shafer theory and artificial intelligence. It discusses how Dempster-Shafer theory accounts for ignorance and uncertainty differently than probability theory by allowing beliefs to range from 0 to 1. It also explains how Dempster-Shafer theory represents beliefs as intervals bounded by belief and plausibility, and how conflicting evidence is handled. Several examples are provided to illustrate key concepts like belief, plausibility, and the effects of conflicting evidence.

L5 understanding hackingRushdi Shams

The document discusses the history and types of hackers. It notes that originally the term "hacker" simply referred to an adept computer user, but media began using it to refer only to computer criminals when cracking systems became popular. It categorizes hackers into different groups based on their motivations, from security experts and script kiddies to criminal hackers and disgruntled employees. It also outlines US laws regarding illegal computer access and spamming. Finally, it provides advice on protecting networks from the four main ways hackers can access systems: over the internet, directly on a network, via remote access, or on a wireless network.

L4 vpnRushdi Shams

VPN systems provide secure remote access to private networks by encrypting traffic and routing it through the public internet. They use IP encapsulation to embed private network packets within public internet packets, encrypting the payload for security. Common VPN protocols include IPSec, L2TP, and PPTP, with IPSec being the most secure as it performs both encryption of payloads and authentication of packet headers. Proper configuration and firewall usage are important to maintain security when using a VPN.

L3 defenseRushdi Shams

1) Packet filter firewalls operate at the network layer and filter network traffic based on IP addresses, ports, and protocols. They are fast but cannot block application-specific attacks. 2) Stateful inspection firewalls add awareness of transport layer connections to packet filtering but open high-numbered ports, increasing risk. 3) Application proxy firewalls authenticate users and can block application commands but are slower and less adaptable than other firewall types.

L2 Intrusion Detection System (IDS)Rushdi Shams

The document discusses network security and intrusion detection. It states that security must use a layered "defense in depth" strategy, as no single measure is sufficient on its own. While firewalls are common, simply allowing all web traffic enables malicious activity. Intrusion detection systems (IDS) monitor traffic for attack signatures. IDS gather information from systems and networks to identify breaches from outside or within an organization. Knowledge-based IDS apply information about known vulnerabilities and attacks to detect exploitation attempts.

L1 phishingRushdi Shams

The document discusses various techniques used in phishing attacks, including sending phishing emails disguised as legitimate companies to steal users' personal information. It notes that phishing attacks doubled from 2004 to 2005 according to one report. The document outlines common phishing techniques like using official-looking emails, URL obfuscation, and hosting malicious software on spoofed websites. It also discusses evolving threats like man-in-the-middle attacks, cross-site scripting, and exploiting weaknesses in interconnected systems and human tendencies to trust familiar brands.

Research Methodology and Tips on Better ResearchRushdi Shams

Common evaluation measures in NLP and IRRushdi Shams

Machine learning with nlp 101Rushdi Shams

Semi-supervised classification for natural language processingRushdi Shams

Natural Language Processing: ParsingRushdi Shams

Types of machine translationRushdi Shams

L1 l2 l3 introduction to machine translationRushdi Shams

Syntax and semanticsRushdi Shams

Propositional logicRushdi Shams

Probabilistic logicRushdi Shams

L15 fuzzy logicRushdi Shams

Knowledge structureRushdi Shams

Knowledge representationRushdi Shams

First order logicRushdi Shams

Belief functionRushdi Shams

L5 understanding hackingRushdi Shams

L4 vpnRushdi Shams

L3 defenseRushdi Shams

L2 Intrusion Detection System (IDS)Rushdi Shams

L1 phishingRushdi Shams

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L7 data model and dbms architecture

1. Database ModelsDatabase Models Database Systems ArchitectureDatabase Systems Architecture Version 1.0Version 1.0 1Rushdi Shams, Dept of CSE, KUET

2.  Database is structured collection of records of data stored in a computer system  Database Management System (DBMS) is a computer software designed to manage (Access/Manipulate/Duplicate) database based on various Data Models. Rushdi Shams, Dept of CSE, KUET 2

3. Rushdi Shams, Dept of CSE, KUET 3 Database

4.  A data model is a formal description of how data maybe structure, represented, and accessed  A database model is a theory or specification describing how a database is structured and can be used Rushdi Shams, Dept of CSE, KUET 4

5. 1. Hierarchical Model 2. Network Model 3. Relational Model 4. Entity-Relationship Model 5. Object Relational Model Rushdi Shams, Dept of CSE, KUET 5

6.  Organized in Tree Structure  Allows repeating information using parent/child relationships  Each parent can have many children but a child will have only one parent Rushdi Shams, Dept of CSE, KUET 6

7. Rushdi Shams, Dept of CSE, KUET 7 Customer Data Name Address Phone Pointer to Checking Acct. Data Pointer to Auto Loan Data Maria Chavez 1441 Adams Court 605-777-8992 John Severson 8988 Grover Road 605-898-2314 Harold Brown 3511 Pluto Drive 605-666-3298 Checking Account Data Acct. Number Current Balance Date Last Transaction 986-335 445.11 07/11/03 988-310 2988.44 07/01/03 355-822 898.14 06/15/03 Auto Loan Data Acct. Number Current Balance Date Last Pmt 100988 5676 06/15/03 101732 1545.33 07/01/03 Parent Data Child Data Pointer

8. Rushdi Shams, Dept of CSE, KUET 8  Employee has many children  But a child has only one parent

9. Rushdi Shams, Dept of CSE, KUET 9  a is boss of b and d  b is boss of c

10.  Allows each record to have multiple parent and multiple children records  More natural modelling than hierarchical model  But network model failed- 1. IBM made an improvement on hierarchical model making it semi- networked 2. Displaced by relational model, which offered higher level of interface Rushdi Shams, Dept of CSE, KUET 10

11.  Based on predicate logic and set theory  Enforced database integrity  Data are operated upon by means of relational algebra  Designs relations (tables) by normalization  Accessing data differs according to the DBMS Rushdi Shams, Dept of CSE, KUET 11

12.  The basic building blocks of this model is- 1. Data type 2. Rows 3. Columns 4. Values  Rows are called body and columns are called heading Rushdi Shams, Dept of CSE, KUET 12

13.  Illustrates logical database  Commonly aids relational database design  End product of the model is Entity Relation Diagram (ERD) Rushdi Shams, Dept of CSE, KUET 13

14. Rushdi Shams, Dept of CSE, KUET 14

15.  Relational model but allows user to integrate a database with their own data types and methods  Mostly, external software runs over traditional DBMS to provide this functionality  Polymorphism, inheritance, function overloading, etc are present Rushdi Shams, Dept of CSE, KUET 15

16.  Mainframe databases • Both DBMS and applications run on mainframe computer • Users access database and applications using terminals  Personal databases • Both DBMS and applications run on user’s workstation  Client/server databases • DBMS runs on central server • Applications run on user’s (client) workstation Rushdi Shams, Dept of CSE, KUET 16

17.  Handling server and client failures  Processing transactions  Handling high data volumes  Providing security  Servicing multiple simultaneous users Rushdi Shams, Dept of CSE, KUET 17

18.  Enterprise Edition (on central DB server)  Express Edition Or  Oracle Personal Edition  Personal database that acts just like a client/server database Rushdi Shams, Dept of CSE, KUET 18

19.  SQL*Plus & PL/SQL  Developer  Procedure Builder  Form Builder  Report Builder  Graphics Builder  Project Builder Rushdi Shams, Dept of CSE, KUET 19

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