This document discusses key concepts in database management systems including:
1. It defines schema, sub-schema, instances, entities, attributes, and domains.
2. It explains different types of attributes such as simple, composite, single-valued, multi-valued, and derived attributes with examples.
3. It discusses mapping constraints including one-to-one, one-to-many, many-to-one, and many-to-many relationships and provides examples.
DBMS Campus crack Question Prepared by Randhir KumarRandhir Chouhan
This document contains a summary of database concepts prepared by Mr. Randhir Kumar. It defines key terms like database, DBMS, database system, data models, ER model, relational model, and normal forms like 1NF, 2NF and 3NF. It also covers transaction management concepts like atomicity and durability, and database architecture topics such as query optimization, indexing, and the system catalog.
An Object Oriented DBMS stores data as objects that use object-oriented concepts like classes, inheritance, and encapsulation. Objects have attributes that can be simple like integers or complex like collections. Classes group similar objects and subclasses inherit attributes and behaviors from superclasses. Objects communicate through messages that invoke methods. The DBMS maps classes and objects to tables and tuples in a relational database, which loses some semantic information about class hierarchies.
The document discusses several semantic database models including the Semantic Data Model (SDM), Semantic Association Model (SAM), DAPLEX, and Information Flow Objects (IFO) model. It describes the key concepts and constructs of each model such as classes, attributes, relationships, and operations. SDM represents real-world entities as classes with attributes and defines subclass and interclass connections, while SAM models concepts and associations between them using different types of relationships.
This document contains information about a Relational Database Management Systems course prepared by D.GAYA, an Assistant Professor. It includes an introduction to database systems, definitions of key terms like data, information, databases, and database management systems. It describes characteristics of DBMS like data being stored in tables, reduced data redundancy, supporting multiple users, and providing security. It also discusses database structures like tables, records, fields, relationships, entities, attributes, and different types of relationships.
This document contains study material prepared by D.GAYA, Assistant Professor of Computer Science at Pondicherry University Community College, for the subject Relational Database Management System. It covers various topics related to SQL including basic SQL reports and commands, data types, joins, DDL, DML, DCL commands, and binary data types. Examples are provided to explain concepts such as creating and dropping databases, creating tables, commenting in SQL, and using the TO_HEX and HEX_TO_BINARY functions for binary data.
The document defines various database concepts including database, DBMS, database system, data independence, data models, relational algebra, relational calculus, normalization, and SQL. It also describes database architecture including the RDBMS kernel, subsystems, data dictionary, and how users communicate with an RDBMS using SQL. The key differences between SQL and other languages are that SQL is non-procedural and declarative, allowing users to specify what data to retrieve rather than how to retrieve it.
Islamic University Previous Year Question Solution 2019 (ADBMS)Rakibul Hasan Pranto
Database administrators (DBAs) manage databases and are responsible for tasks like creating the database schema, defining storage structures and access methods, modifying the schema or physical organization when needed, granting authorization for data access, and specifying integrity constraints. Other database roles include application programmers, sophisticated users, specialized users, standalone users, native users, and system analysts who are responsible for database design, structure, and properties.
The document provides information on databases, DBMS, database systems, advantages of DBMS over file processing systems, levels of data abstraction, integrity rules, extension and intension, System R, data independence, views, data models including E-R and object-oriented models, entities, entity sets, attributes, relations, relationships, keys, normalization, relational algebra, relational calculus, and other database concepts.
DBMS Campus crack Question Prepared by Randhir KumarRandhir Chouhan
This document contains a summary of database concepts prepared by Mr. Randhir Kumar. It defines key terms like database, DBMS, database system, data models, ER model, relational model, and normal forms like 1NF, 2NF and 3NF. It also covers transaction management concepts like atomicity and durability, and database architecture topics such as query optimization, indexing, and the system catalog.
An Object Oriented DBMS stores data as objects that use object-oriented concepts like classes, inheritance, and encapsulation. Objects have attributes that can be simple like integers or complex like collections. Classes group similar objects and subclasses inherit attributes and behaviors from superclasses. Objects communicate through messages that invoke methods. The DBMS maps classes and objects to tables and tuples in a relational database, which loses some semantic information about class hierarchies.
The document discusses several semantic database models including the Semantic Data Model (SDM), Semantic Association Model (SAM), DAPLEX, and Information Flow Objects (IFO) model. It describes the key concepts and constructs of each model such as classes, attributes, relationships, and operations. SDM represents real-world entities as classes with attributes and defines subclass and interclass connections, while SAM models concepts and associations between them using different types of relationships.
This document contains information about a Relational Database Management Systems course prepared by D.GAYA, an Assistant Professor. It includes an introduction to database systems, definitions of key terms like data, information, databases, and database management systems. It describes characteristics of DBMS like data being stored in tables, reduced data redundancy, supporting multiple users, and providing security. It also discusses database structures like tables, records, fields, relationships, entities, attributes, and different types of relationships.
This document contains study material prepared by D.GAYA, Assistant Professor of Computer Science at Pondicherry University Community College, for the subject Relational Database Management System. It covers various topics related to SQL including basic SQL reports and commands, data types, joins, DDL, DML, DCL commands, and binary data types. Examples are provided to explain concepts such as creating and dropping databases, creating tables, commenting in SQL, and using the TO_HEX and HEX_TO_BINARY functions for binary data.
The document defines various database concepts including database, DBMS, database system, data independence, data models, relational algebra, relational calculus, normalization, and SQL. It also describes database architecture including the RDBMS kernel, subsystems, data dictionary, and how users communicate with an RDBMS using SQL. The key differences between SQL and other languages are that SQL is non-procedural and declarative, allowing users to specify what data to retrieve rather than how to retrieve it.
Islamic University Previous Year Question Solution 2019 (ADBMS)Rakibul Hasan Pranto
Database administrators (DBAs) manage databases and are responsible for tasks like creating the database schema, defining storage structures and access methods, modifying the schema or physical organization when needed, granting authorization for data access, and specifying integrity constraints. Other database roles include application programmers, sophisticated users, specialized users, standalone users, native users, and system analysts who are responsible for database design, structure, and properties.
The document provides information on databases, DBMS, database systems, advantages of DBMS over file processing systems, levels of data abstraction, integrity rules, extension and intension, System R, data independence, views, data models including E-R and object-oriented models, entities, entity sets, attributes, relations, relationships, keys, normalization, relational algebra, relational calculus, and other database concepts.
This document discusses object-oriented data modeling concepts including objects, classes, inheritance, and persistent programming languages. It defines an object as having data variables, messages it responds to, and methods implementing those messages. Classes group objects and inheritance allows subclasses to inherit attributes and methods from parent classes. Persistent programming languages allow objects to be directly manipulated from a programming language and stored in a database without explicit data formatting changes or loading/storing.
The document discusses DBMS viva questions and answers. It contains 61 questions and their explanations related to key concepts in database management systems including databases, DBMS, data models, data storage, transaction management, and more. The questions cover topics like data independence, normalization, indexing, and recovery mechanisms in DBMS.
The document discusses object database systems and their advantages over relational database management systems (RDBMS). It notes problems with representing real-world entities in RDBMSs and describes how object-oriented and object-relational database models address these issues better by allowing for inheritance, complex data types, and encapsulation of both data and behavior. The key advantages of object database systems include more closely modeling real-world entities and supporting reuse through inheritance. Object-relational database systems combine object and relational approaches for increased flexibility.
The document provides an overview of relational database concepts and the Oracle database implementation. It describes the life cycle development phases, theoretical and conceptual aspects of relational databases, and how SQL is used with Oracle's RDBMS and ORDBMS. It also covers basic SQL statements like SELECT and restrictions, data types, database objects, SQL statements, operators, and comparisons that can be used with SQL.
This document provides an overview of a Relational Database Management System (RDBMS) unit prepared by D.GAYA, an Assistant Professor of Computer Science at Pondicherry University Community College. It defines key RDBMS concepts and components, including database languages, the query processor, runtime and database managers, and the database engine. It also outlines benefits of RDBMS such as data security, sharing, integration and abstraction/independence. Applications mentioned include following ACID properties, multi-user access, multiple views, and security features. Finally, it briefly introduces data modeling and different data models.
hExarAbax makkAmasjix samayaM anni rojulu 5:00 am - 9:00 pm
(Mecca Masjid timings in Hyderabad - All days 5:00 am - 9:00 pm)
User query: makkAmasjix PIju eVMwa?
(What is the fee for Mecca Masjid?)
POS-tagger: makkAmasjix PIju/WQ eVMwa
Replace with root word: makkAmasjix PIju/WQ eMwa
Context Handler: Updates context to 'makkAmasjix'
Advanced Filter: Keywords - makkAmas
This presentation contains the concepts related to database design using ER Diagram. The content is adapted from the contents of the authors of the book mentioned in the reference.
Overview of Object-Oriented Concepts Characteristics by vikas jagtapVikas Jagtap
Object-oriented data base systems are proposed as alternative to relational systems and are aimed at application domains where complex objects play a central role.
The approach is heavily influenced by object-oriented programming languages and can be understood as an attempt to add DBMS functionality to a programming language environment
Guidelines for ER to Relational Mapping.
Mapping rules/ guidelines for mapping various ER constructs to Relational model with appropriate examples
Relational Query Languages Formal Query Languages
Introduction to Relational Algebra
Relational operators
Set operators
Join operators
Aggregate functions.
Grouping operator
Relational Calculus concepts
Relational algebra queries for data retrieval with sample relational schemas. relational algebra operations.
The document discusses object-oriented databases and the need for complex data types that traditional databases cannot support well. It covers the core concepts of the object-oriented data model including objects, classes, inheritance, and object identity. Key advantages of the object-oriented approach include its ability to model complex relationships and enable persistence of programming language objects.
This document provides an overview of database management systems (DBMS). It defines a DBMS as software that manages data and allows for data to be accessed by multiple users and applications. The document then covers the introduction, properties, benefits, types, entity relationship diagrams, and differences between DBMS and relational DBMS. It provides examples and definitions for each topic.
This document discusses fuzzy querying of relational databases. It begins by introducing fuzzy relational database management systems (FRDBMS), which allow imprecise queries using fuzzy logic. It then presents the basic concepts of fuzzy logic and membership functions. The architecture of an FRDBMS is described, including how it translates fuzzy queries into equivalent SQL queries. An example student database is used to demonstrate a fuzzy query for "poor performers" and how it returns more graded results than an exact SQL query. The document concludes that FRDBMS improves the expressiveness of queries over traditional databases.
T EXT M INING AND C LASSIFICATION OF P RODUCT R EVIEWS U SING S TRUCTURED S U...csandit
Text mining and Text classification are the two pro
minent and challenging tasks in the field of
Machine learning. Text mining refers to the process
of deriving high quality and relevant
information from text, while Text classification de
als with the categorization of text documents
into different classes. The real challenge in these
areas is to address the problems like handling
large text corpora, similarity of words in text doc
uments, and association of text documents with
a subset of class categories. The feature extractio
n and classification of such text documents
require an efficient machine learning algorithm whi
ch performs automatic text classification.
This paper describes the classification of product
review documents as a multi-label
classification scenario and addresses the problem u
sing Structured Support Vector Machine.
The work also explains the flexibility and performan
ce of the proposed approach for e
fficient text classification.
This document contains lecture material on Relational Database Management Systems (RDBMS) and PL/SQL prepared by D.GAYA, an Assistant Professor of Computer Science at Pondicherry University Community College. The document covers PL/SQL concepts such as blocks, variables, data manipulation using DML statements, triggers, procedures, functions, packages, and exception handling. It provides examples and explanations of PL/SQL blocks, variable declaration and assignment, data types, and manipulating data through insertion, updating, deletion, and selection using SQL statements within PL/SQL blocks. The document is intended to teach second year B.Voc students in the Software Development program about PL/SQL and RDBMS.
This document provides an overview of database management systems and conceptual modeling. It defines key terms like DBMS, database schema, instance, physical schema, logical schema, and data model. It also describes data abstraction levels, the entity-relationship model, relational model components like tuples and relations, and relational algebra and calculus operations. The document consists of questions and answers on database concepts and topics like data modeling, the storage manager, and the entity-relationship diagram.
This document provides an introduction to database design and applications (DBDA). It discusses the differences between file systems and database management systems (DBMS)/relational database management systems (RDBMS). It also covers the three schema architecture of a DBMS, including the conceptual, internal, and external schemas. Additionally, it discusses data independence and the advantages of using a DBMS compared to a file system. The document provides a brief history of DBMS and describes some popular DBMS software. It also outlines the characteristics, advantages, and disadvantages of using a DBMS.
This document provides an introduction to database management systems (DBMS) and structured query language (SQL). It defines key DBMS concepts like data models, database architecture, and SQL data types. The main data models covered are relational, network, and hierarchical. It describes the components of entity relationship (ER) diagrams like entities, attributes, and relationships. It also gives examples of SQL data types and discusses how data types are specified when creating database tables in SQL.
This document provides an overview of database management systems (DBMS) including their characteristics and applications. It discusses why DBMS are used, their ACID properties, support for multi-user access, multiple views, security features, use of relational tables, isolation of data and applications, normalization to reduce redundancy, consistency, query languages, and types of users. Entity relationship modeling and the relational data model are also introduced.
The document provides information on database management systems (DBMS) compared to file systems, components of a DBMS, types of databases, advantages of using a DBMS, relational database management systems (RDBMS), levels of data abstraction in a DBMS using a three-schema architecture, types of data independence, introduction to database design including entities, entity sets, attributes, relationships and relationship sets, and ER modeling.
This document provides an overview of database management systems. It discusses what data is and how it differs from information. It then describes some issues with traditional file systems for data storage and how database management systems were created to overcome these deficiencies. The key characteristics of a database management system are then outlined, including using real-world entities, relation-based tables, isolation of data and application, normalization to reduce redundancy, consistency, and ACID properties. The document also discusses database architecture types, data models, the relational model, database schemas and instances, and SQL. Finally, it covers some database design concepts like entities and attributes, relationships and keys, and generalization and specialization.
This document discusses object-oriented data modeling concepts including objects, classes, inheritance, and persistent programming languages. It defines an object as having data variables, messages it responds to, and methods implementing those messages. Classes group objects and inheritance allows subclasses to inherit attributes and methods from parent classes. Persistent programming languages allow objects to be directly manipulated from a programming language and stored in a database without explicit data formatting changes or loading/storing.
The document discusses DBMS viva questions and answers. It contains 61 questions and their explanations related to key concepts in database management systems including databases, DBMS, data models, data storage, transaction management, and more. The questions cover topics like data independence, normalization, indexing, and recovery mechanisms in DBMS.
The document discusses object database systems and their advantages over relational database management systems (RDBMS). It notes problems with representing real-world entities in RDBMSs and describes how object-oriented and object-relational database models address these issues better by allowing for inheritance, complex data types, and encapsulation of both data and behavior. The key advantages of object database systems include more closely modeling real-world entities and supporting reuse through inheritance. Object-relational database systems combine object and relational approaches for increased flexibility.
The document provides an overview of relational database concepts and the Oracle database implementation. It describes the life cycle development phases, theoretical and conceptual aspects of relational databases, and how SQL is used with Oracle's RDBMS and ORDBMS. It also covers basic SQL statements like SELECT and restrictions, data types, database objects, SQL statements, operators, and comparisons that can be used with SQL.
This document provides an overview of a Relational Database Management System (RDBMS) unit prepared by D.GAYA, an Assistant Professor of Computer Science at Pondicherry University Community College. It defines key RDBMS concepts and components, including database languages, the query processor, runtime and database managers, and the database engine. It also outlines benefits of RDBMS such as data security, sharing, integration and abstraction/independence. Applications mentioned include following ACID properties, multi-user access, multiple views, and security features. Finally, it briefly introduces data modeling and different data models.
hExarAbax makkAmasjix samayaM anni rojulu 5:00 am - 9:00 pm
(Mecca Masjid timings in Hyderabad - All days 5:00 am - 9:00 pm)
User query: makkAmasjix PIju eVMwa?
(What is the fee for Mecca Masjid?)
POS-tagger: makkAmasjix PIju/WQ eVMwa
Replace with root word: makkAmasjix PIju/WQ eMwa
Context Handler: Updates context to 'makkAmasjix'
Advanced Filter: Keywords - makkAmas
This presentation contains the concepts related to database design using ER Diagram. The content is adapted from the contents of the authors of the book mentioned in the reference.
Overview of Object-Oriented Concepts Characteristics by vikas jagtapVikas Jagtap
Object-oriented data base systems are proposed as alternative to relational systems and are aimed at application domains where complex objects play a central role.
The approach is heavily influenced by object-oriented programming languages and can be understood as an attempt to add DBMS functionality to a programming language environment
Guidelines for ER to Relational Mapping.
Mapping rules/ guidelines for mapping various ER constructs to Relational model with appropriate examples
Relational Query Languages Formal Query Languages
Introduction to Relational Algebra
Relational operators
Set operators
Join operators
Aggregate functions.
Grouping operator
Relational Calculus concepts
Relational algebra queries for data retrieval with sample relational schemas. relational algebra operations.
The document discusses object-oriented databases and the need for complex data types that traditional databases cannot support well. It covers the core concepts of the object-oriented data model including objects, classes, inheritance, and object identity. Key advantages of the object-oriented approach include its ability to model complex relationships and enable persistence of programming language objects.
This document provides an overview of database management systems (DBMS). It defines a DBMS as software that manages data and allows for data to be accessed by multiple users and applications. The document then covers the introduction, properties, benefits, types, entity relationship diagrams, and differences between DBMS and relational DBMS. It provides examples and definitions for each topic.
This document discusses fuzzy querying of relational databases. It begins by introducing fuzzy relational database management systems (FRDBMS), which allow imprecise queries using fuzzy logic. It then presents the basic concepts of fuzzy logic and membership functions. The architecture of an FRDBMS is described, including how it translates fuzzy queries into equivalent SQL queries. An example student database is used to demonstrate a fuzzy query for "poor performers" and how it returns more graded results than an exact SQL query. The document concludes that FRDBMS improves the expressiveness of queries over traditional databases.
T EXT M INING AND C LASSIFICATION OF P RODUCT R EVIEWS U SING S TRUCTURED S U...csandit
Text mining and Text classification are the two pro
minent and challenging tasks in the field of
Machine learning. Text mining refers to the process
of deriving high quality and relevant
information from text, while Text classification de
als with the categorization of text documents
into different classes. The real challenge in these
areas is to address the problems like handling
large text corpora, similarity of words in text doc
uments, and association of text documents with
a subset of class categories. The feature extractio
n and classification of such text documents
require an efficient machine learning algorithm whi
ch performs automatic text classification.
This paper describes the classification of product
review documents as a multi-label
classification scenario and addresses the problem u
sing Structured Support Vector Machine.
The work also explains the flexibility and performan
ce of the proposed approach for e
fficient text classification.
This document contains lecture material on Relational Database Management Systems (RDBMS) and PL/SQL prepared by D.GAYA, an Assistant Professor of Computer Science at Pondicherry University Community College. The document covers PL/SQL concepts such as blocks, variables, data manipulation using DML statements, triggers, procedures, functions, packages, and exception handling. It provides examples and explanations of PL/SQL blocks, variable declaration and assignment, data types, and manipulating data through insertion, updating, deletion, and selection using SQL statements within PL/SQL blocks. The document is intended to teach second year B.Voc students in the Software Development program about PL/SQL and RDBMS.
This document provides an overview of database management systems and conceptual modeling. It defines key terms like DBMS, database schema, instance, physical schema, logical schema, and data model. It also describes data abstraction levels, the entity-relationship model, relational model components like tuples and relations, and relational algebra and calculus operations. The document consists of questions and answers on database concepts and topics like data modeling, the storage manager, and the entity-relationship diagram.
This document provides an introduction to database design and applications (DBDA). It discusses the differences between file systems and database management systems (DBMS)/relational database management systems (RDBMS). It also covers the three schema architecture of a DBMS, including the conceptual, internal, and external schemas. Additionally, it discusses data independence and the advantages of using a DBMS compared to a file system. The document provides a brief history of DBMS and describes some popular DBMS software. It also outlines the characteristics, advantages, and disadvantages of using a DBMS.
This document provides an introduction to database management systems (DBMS) and structured query language (SQL). It defines key DBMS concepts like data models, database architecture, and SQL data types. The main data models covered are relational, network, and hierarchical. It describes the components of entity relationship (ER) diagrams like entities, attributes, and relationships. It also gives examples of SQL data types and discusses how data types are specified when creating database tables in SQL.
This document provides an overview of database management systems (DBMS) including their characteristics and applications. It discusses why DBMS are used, their ACID properties, support for multi-user access, multiple views, security features, use of relational tables, isolation of data and applications, normalization to reduce redundancy, consistency, query languages, and types of users. Entity relationship modeling and the relational data model are also introduced.
The document provides information on database management systems (DBMS) compared to file systems, components of a DBMS, types of databases, advantages of using a DBMS, relational database management systems (RDBMS), levels of data abstraction in a DBMS using a three-schema architecture, types of data independence, introduction to database design including entities, entity sets, attributes, relationships and relationship sets, and ER modeling.
This document provides an overview of database management systems. It discusses what data is and how it differs from information. It then describes some issues with traditional file systems for data storage and how database management systems were created to overcome these deficiencies. The key characteristics of a database management system are then outlined, including using real-world entities, relation-based tables, isolation of data and application, normalization to reduce redundancy, consistency, and ACID properties. The document also discusses database architecture types, data models, the relational model, database schemas and instances, and SQL. Finally, it covers some database design concepts like entities and attributes, relationships and keys, and generalization and specialization.
This document contains information about a Relational Database Management Systems course prepared by D.GAYA, an Assistant Professor. It includes an introduction to database systems, definitions of key terms like data, information, databases, and database management systems. It describes characteristics of DBMS like data being stored in tables, reduced data redundancy, supporting multiple users, and providing security. It also discusses database structures like tables, records, fields, relationships, entities, attributes, and different types of relationships.
The document discusses database design and normalization. It covers key concepts in database design including the entity-relationship model, normalization forms, functional dependencies, and multi-valued dependencies. The goal of normalization is to organize data to reduce redundancy and dependency issues by decomposing tables to satisfy certain normal forms up to fifth normal form. Normalization involves identifying functional dependencies between attributes and ensuring tables comply with rules for each normal form.
The document discusses class visibility in object-oriented design. It defines a class as a description of objects with similar roles that consist of attributes and operations. Attributes represent an object's state while operations define what it can do. The document explains that in UML, classes use visibility notation (+ public, - private, # protected, ~ package) to specify whether attributes and operations are accessible to members of the same class, derived classes, or other classes. It provides an example of class visibility and discusses defining attributes, including different types like simple, composite, single/multi-valued, derived, complex, key, and stored attributes.
The document discusses modeling data objects in an entity relationship diagram. It covers key concepts like entities, attributes, relationships, and keys. It provides examples of how to represent different types of relationships between entities like one-to-one, one-to-many, and many-to-many. The document also discusses modeling weak entities, documenting the ER diagram, normalizing the data to avoid anomalies, and determining the scope of the database and application system.
The document discusses the three levels of data abstraction in database management systems: the view level describes different views of data for users, the conceptual level defines how data is structured and related, and the physical level hides where data is actually stored on disk drives and managed by database administrators. Data abstraction involves hiding irrelevant details from users at different levels to provide customized views and achieve data independence between users and the physical storage of information.
There are three levels of data abstraction: the physical level describes how data is actually stored, the logical level describes what data is stored and the relationships between data, and the view level describes how users interact with the database. A database schema defines the logical structure of a database, including tables, fields, and relationships. An instance is the current state of data stored in the database at a given time. Physical data independence allows the physical schema to be modified without changing the logical schema. Data models include the relational model using tables, the entity-relationship model using entities and relationships, object-based models, and semi-structured models like XML.
The document provides an overview of object-oriented concepts. It discusses that software development is increasingly relying on object-oriented paradigms due to benefits like improved modeling of real-world problems and reusability. Key concepts discussed include classes and objects, encapsulation, inheritance, polymorphism, and object composition. Various object-oriented methodologies like those proposed by Coad/Yourdon, Booch, Rumbaugh, and Jacobson are also summarized.
What is Data ?
What is Information?
Data Models, Schema and Instances
Components of Database System
What is DBMS ?
Database Languages
Applications of DBMS
Introduction to Databases
Fundamentals of Data Modeling and Database Design
Database Normalization
Types of keys in database management system
Distributed Database
The document discusses data modeling and the entity-relationship (ER) model. It defines key concepts like the ER model, entities, attributes, relationships and keys. The ER model is used to develop a conceptual design for a database through entity-relationship diagrams. These diagrams show entities, attributes and relationships. Entities can have primary keys, foreign keys and other types of keys to uniquely identify records. The ER model provides a high-level view of data that is later mapped to relational database schemas.
This document provides an overview of key concepts in database management systems including:
- The main components of a DBMS including the query processor, storage manager, and disk storage.
- The three schema architecture separating the conceptual, internal, and external schemas.
- Database languages like DDL, DML, DCL, and TCL and their purposes.
- Entity-relationship modeling including entities, attributes, relationships, and extensions.
- Different types of database users such as administrators, designers, programmers, and end users.
This document provides an overview of key concepts in database management systems including:
- The main components of a DBMS including the query processor, storage manager, and disk storage.
- The three schema architecture separating the conceptual, internal, and external schemas.
- Database languages like DDL, DML, DCL, and TCL and their purposes.
- Entity-relationship modeling including entities, attributes, relationships, and extensions.
- Different types of database users such as administrators, designers, programmers, and end users.
The document discusses database essentials including database management systems, database applications, the purpose of database systems, data models, database languages, database architecture, and the relational data model. Specifically, it defines what a DBMS is, provides examples of common database applications, describes why databases were developed to address limitations of file processing systems, outlines several data models including the relational model, discusses database languages for defining and manipulating data, presents the client-server architecture of database systems, and explains key concepts of the relational model including tables, tuples, attributes, relations, and domains.
Database Design and the ER Model, Indexing and HashingPrabu U
This document provides an overview of database design and the entity-relationship (ER) model. It discusses the database design process, including initial, conceptual, logical, and physical design phases. It then describes the key concepts of the ER model, including entities, attributes, relationships, cardinalities, participation constraints, and keys. The document explains how to design ER diagrams and how to remove redundant attributes. It provides examples of one-to-one, one-to-many, many-to-one, and many-to-many relationships. Finally, it demonstrates how to represent complex attributes like composite, multi-valued, and derived attributes in an ER diagram.
The document discusses object-oriented programming and its evolution from structured procedural programming. It describes some of the key disadvantages of structured procedural programming, including a lack of code reusability, extensibility and maintainability. Object-oriented programming aims to address these issues by emphasizing data over procedures and dividing programs into reusable objects that encapsulate both data and functions. The document outlines several fundamental elements of object-oriented programming, including objects, classes, encapsulation, inheritance, polymorphism and dynamic binding.
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
Freshworks Rethinks NoSQL for Rapid Scaling & Cost-EfficiencyScyllaDB
Freshworks creates AI-boosted business software that helps employees work more efficiently and effectively. Managing data across multiple RDBMS and NoSQL databases was already a challenge at their current scale. To prepare for 10X growth, they knew it was time to rethink their database strategy. Learn how they architected a solution that would simplify scaling while keeping costs under control.
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
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12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
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Dbms question (3)
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DBMS QUESTIONS
1.) Define: Schema, Sub-schema, Instances, Entity, Attribute, and Domain.
Schema: It is the set of formulas that specify integrity constraints imposed on database.
Sub-schema: In database management, an individual user's partial view of the database is called sub-
schema.
Instances: The information stored in database at the particular movement is called instance.
Entity: It represents the field of database.
Attribute: It is a column of table in database.
Domain: It is set of permissible value of an attributes.
2.) Explain with examples different types of Attributes.
Simple Attributes: Attributes which can’t be divided into subparts are called Simple Attributes.
For example, Age of a person is simple attribute, Employee Number is simple Attribute.
Composite Attributes: Attributes which can be divided into subparts. These subparts are basic
attributes with independent meanings of their own.
For example, Name of a person is composite attribute as it can be further divided into First Name,
Middle Name and Last Name.
Single – Valued Attribute: A single valued attribute can have only a single value.
For example a person can have only one 'date of birth', 'age' etc. That is a single valued attributes can
have only single value. But it can be simple or composite attribute. That is 'date of birth' is a composite
attribute, 'age' is a simple attribute. But both are single valued attributes.
Multi – Valued Attribute: Multi valued attributes can have multiple values. For instance a person may
have multiple phone numbers, multiple degrees etc.
Derived Attribute: An attribute that’s value is derived from a stored attribute.
For example, age and its value are derived from the stored attribute Date of Birth.
3.) Explain mapping constraints.
One – One One – Many
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Many – One Many – Many
One- One Relationship:
In this type of relationship, one attribute of a particular table is associated with only one attribute of
another table.
For example, An Instructor is associated with only one student via advisor.
A Student is associated with only one Instructor via advisor.
Many – One Relationship:
In this type of relationship, many attributes of a particular table is associated with only one attribute of
another table.
For example, Many Instructors are advising only one student.
One - Many Relationship:
In this type of relationship, only one attribute of particular table is associated with many attributes of
another table.
For example, An instructor is advising many students.
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Many – Many Relationship:
In this type of relationship, many attributes of particular table is associated with many attributes of
another table.
For example, Many instructors are advising many students.
4.) Explain different types of keys with examples.
Super Key: Super key is a set of one or more attributes that are taken collectively whose values or tuple
is identified uniquely.
For example, Enrollment no., Email Id of Student table are super keys of that particular table.
Candidate key: It is not proper subset of super key. The content of super key can be a candidate key
but not vice versa.
For example, Enrollment No. is a candidate key as it is a super key but no subsets of it is super key.
Primary key: It is a candidate key which represents a particular attributes whose values are unique and
not NULL.
For example, Enrollment No. is a primary key of student table as it is unique of particular student. It is
not possible that students have same Enrollment No and also that a student is without Enrollment No.
Foreign key: Foreign key is a primary key of another table. Any attribute of a particular table is a
foreign key if that attribute is derived from another table and is also a primary key of that table.
For example, If student ID is a primary key of student table then it can be used as a foreign key in Exam
table where the name can be known of student with the help of student ID.
5.) Explain enhanced entity relationship models with following:
a.) Specialization
b.) Generalization
c.) Categorization.
d.) Aggregation
Specialization: It is a top down process that designates sub grouping entity set that are distinct from
other entities in the set. The attributes are inherited to lower level entity set from higher level entity
set.
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person
ID
Name
address
employee student
salary tot_credits
instructor secretary
rank hours_perweek
Specialization & Generalization
Generalization: It is a bottom up process. It combines the entities having same features into a higher
level entity set.
Aggregation: Aggregation is an abstraction in which relationship sets are treated as higher level entity
sets. Here a relationship set is embedded inside an entity set, and these entity sets can participate in
relationships.
6.) Advantages and Disadvantages of DBMS.
Advantages:
i. Reduces data redundancy.
ii. Reduces errors and increase the level of consistency.
iii. Greater data integrity and independence from application programs.
iv. Improved Data security.
v. Improved data access to users through use of host and query languages.
vi. Many people can access same database at same time from anywhere.
Disadvantages
i. Database systems are complex, difficult and time taking to design.
ii. Substantial hardware and software start up costs.
iii. Initial training is required for all programmers and users.
5. 5|P a g e
7.) Advantages and Disadvantages of File system.
Advantages
i. There is not much requirement when it comes to facility. Just some spaces are required to
continue.
ii. It is user friendly in case of training as just a little training is required for it.
iii. It is less expensive.
Disadvantages
i. File description are stored with each application program that access a given file.
ii. There are chances of duplication of data in file system as it is manually done.
iii. In case, if we want a particular data from all the stored data then it’s much difficult to fetch out as
the users have to sequentially go through each and every data files.
iv. There is no security or is less secured.
8.) Explain levels of Abstraction of data in DBMS.
OR Explain the View of data in DBMS.
There are three levels of Data Abstraction in DBMS. They are:
i. Internal Level/ Physical level Storage views.
ii. Conceptual Level/Logical Level/Community users views.
iii. External Level/Individual users views.
Internal Level:
- This level is the lowest level representation of the entire database. It is described by means of
internal schema.
- The internal level is all about how data are stored actually, what physical sequence the stored
records are in and so on. The internal schema is written using data definition language (the internal
DDL).
Conceptual Level:
- This level is the next higher level of abstraction which describes what data are stored in the
database and what relationships exist among those data. Thus, it is the representation of the entire
information content of the database in the way; user wants to see rather than as users is forced to
see by limitation.
- The Logical level describes the entire database in terms of small number of relatively simpler
structures but implementation of simpler structures may involve complex physical-level structures
of which the user doesn’t need to be aware. This is referred to as physical data independence.
- The conceptual view consists of many occurrences of many types of conceptual records. For
example, it might consist of a collection of department record occurrences, plus a collection of
employee record occurrences, plus a collection of supplier record occurrences and so on.
- The conceptual view is defined by means of conceptual schema, which includes definitions of each
of the various conceptual records types.
External Level:
- The highest level of abstraction describes only part of the entire database.
- Even though the Logical Level uses simpler structures, complexity remains because of the variety of
information stored in large database. Many users don’t need all this information; instead, they
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need to access only a part of database. The External level of abstraction exists to simplify their
interaction with the system.
9.) Explain the Database Languages.
There are four types of Database languages. They are:
i. DML (Data Manipulation Language)
ii. DDL (Data Definition Language)
iii. DCL (Data Control Language)
iv. TCL (Transaction Control Language)
DML (Data Manipulation Language)
- It is used/ function is to manipulate data.
- It consist Commands like INSERT, DELETE, MERGE, UPADTE.
- INSERT command add tuples/ attributes to an existing table.
- DELETE command removes existing tuples / attributes from a table.
- UPDATE command modifies a set of existing table tuples/attributes.
- MERGE command is used to combine the data of multiple tables.
DDL (Data Definition Language)
- DDL manages the table and index structure.
- It consist Commands like CREATE, ALTER, DROP, TRUNCATE and REPLACE.
- CREATE Command creates an object(table) in the database.
- ALTER Command modifies the structure of an existing object in various ways.
- TRUNCATE Command deletes all data from a table in a very fast way, deleting the data inside table
and not the table itself.
- DROP Command deleted an object in database usually that cannot be ‘ROLL BACK’.
- REPLACE Command is used to rename the table.
DCL (Data Control Language)
- DCL authorizes users or a group of users to access and manipulate data.
- It consist Commands like GRANT and REVOKE.
- GRANT Command authorizes one or more users to perform an operation or a set of operations on
an object.
- REVOKE Command eliminates a grant which were given to users.
TCL (Transaction Control Language)
- TCL deals with transaction of data i.e. to completely remove or save the data as per requirements.
- It consist Commands like COMMIT and ROLLBACK.
- COMMIT Command causes all data changes in a transaction to be made permanent.
- ROLLBACK Command causes all data changes since the last COMMIT or ROLLBACK to be discarded,
leaving the state of data as it was prior to those changes.
10.) Explain different types of database users.
There are three types of database users. They are:
i. Database Administrator (DBA)
ii. Application developers
7. 7|P a g e
iii. Application’s end users
Database Administrator
- DBA are the one who design and build the DBMS product and the only ones who can work on its
code. No other than DBA can know about coding behind the product.
- For example, ORACLE, My SQL, etc.
- A database administrator’s responsibilities can include the following:
i. Installing and upgrading database server and application tools.
ii. Allocating system storage and planning future storage requirements for the database
system.
iii. Creating primary database storage structures after application developers have designed
the application.
iv. Creating primary objects (tables, views, indexes) once application developers have designed
an application.
v. Modifying database structures, as necessary, from information given by application
developers.
vi. Enrolling users and maintaining system security.
vii. Planning for backup and recovery of the database information.
Application developers
- They are the one to design and create application that uses DBMS and after that design the needed
database and maintain it. The responsibilities of Application developers include the following tasks:
i. Designing and developing the database application.
ii. Designing the database structures for an application.
iii. Estimating storage requirements for an application.
iv. Specifying modifications of database structure for an application.
v. Establishing security measures for an application during development.
Application end users
- They are the one that interact with application or utilities. A typical end user’s responsibilities
includes following tasks:
i. Entering, modifying or deleting the data, where permitted.
ii. Generating reports from the data.
11.) Define: Schema diagram, Relational data model, Relational query language and Relational algebra.
Schema diagram: It is a pictorial depiction of the schema of a database that shows the relations in the
database, their attributes and primary keys and foreign keys.
Relational data model: It is based on a collection of tables. The user of a database may query these
tables, insert new tuples, delete tuples, and update (modify) tuples.
Relational query language: It defines a set of operations that operate on tables, and output tables as
their results. These operations can be combined to get expressions that express desired queries.
Relational Algebra: It provides a set of operations that take one or more relations as input and return a
relation as an output. Practical query languages such as SQL are based on the relational algebra, but
add a number of useful syntactic features.
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12.) Explain database system architecture with diagram in detail.
The Database systems can be centralized, or client-server, where one server machine executes work on
behalf of multiple client machines. Database systems can also be designed to exploit parallel computer
architectures.
Most users of the database system today are not present at the site of the database system, but
connect to it through a network. We can therefore differentiate between client machines, on which
remote database user’s work, and server machines, on which the database system runs.
Naïve users Application Sophisticated Database
(tellers, agents, web programmers users administrator
users) (analysis)
use write use use
Application Application Query Administration
interfaces programs tools tools
Compiler & DML queries DDL interpreter
linker
Application DML compiler
program object & organizer
code
Query evaluation
engine
query processor
Buffer manager File manager Authorization & Transaction
integrity manager manager
storage manager
disk storage
indices Data
dictionary
data Statistical data
System architecture
9. 9|P a g e
Database applications are usually partitioned into two or three parts. In a two-tier architecture, the
application resides at the client machine, where it invokes database system functionally at the server
machine through query language statements.
In a three-tier architecture, the client machine acts as merely a front end and does not contain any
direct database calls. Instead, the client end communicates with an application server, usually through
a forms interface. The application server in turn communicates with a database system to access data.
users users
client
application application
network network
database system Application server
server
Database system
(a) Two-tier architecture (b) Three-tier architecture
13.) Explain Relational Query Languages.
A query language is a language in which user requests information from the database. These languages
are usually on a level higher than that of a standard programming language. Query languages can be
categorized as either procedural or nonprocedural.
In procedural language, the user instructs the system to perform a sequence of operations on the
database to get the desired result.
In nonprocedural language, the user describes the desired information without giving a specific
procedure for obtaining that information.
Schema of the University database is as follow:
classroom(building, room_number, capacity)
department(dept_name, building, budget)
course(course_id, title, dept_name, credits)
instructor(ID, name, dept_name, salary)
student(stu_ID, name, dept_name, tot_cred)
10. 10 | P a g e
Query languages are used in both ways i.e. procedural and nonprocedural. There are number of ‘pure’
query languages: The relational algebra is procedural, whereas the tuple relational calculus and domain
relational calculus are nonprocedural.
The relational algebra is a set of operations that take one or two relations as input and procedure a
new relation as their result. The relational calculus uses predicate logic to define the result as desired
without giving any specific algebraic procedure.
14.) Explain Relational Operations with example.
There are six basic operators/ operations which all procedural relational query languages have. They
are:
i. Select : σ
ii. Project : ∏
iii. Rename : ρ
iv. Union : ∪
v. Set difference :
vi. Cartesian Product : x
Select Operation: σ
- The Select operations select the tuples satisfying given condition.
σ(branch_name) = “Anand” (Bank)
- In the above example, σ is the select operator after that is the condition in which except the
operators, others are in subscript and in the end is the table name in parenthesis.
- The comparisons can be done using =, ≤, ≥, <, >.
σ(amount) > 10000 (Bank)
- Several conditions can be combined by using (AND), (OR) and (NOT).
σ(branch_name) = “Anand” amount = 10000 (Bank)
- Relation : r
α β γ
A 1 1
A 2 1
B 3 1
B 4 2
- σβ = γ (r)
α β γ
A 1 1
- In the above example, the select operation show us the relation as per the condition given and the
one which don’t follow the condition are hidden/ left out.
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Project Operation: ∏
- The Project operation is a unary operation (operate on one relation) that returns its argument
relations, with certain attributes left out.
- The attributes which we want is to be listed with ∏ and the table name in the parenthesis. It can be
shown as below:
∏branch_name,amount(Bank)
- Relation: r α β γ
A 1 1
A 2 1
B 3 4
B 4 5
- ∏σ,γ(r)
α γ α γ
A 1 A 1
=
A 1 B 4
B 4 B 5
B 5
- In the above example, the project operation shows us the attributes which are in the condition and
rest are left out. In this example, the repeated relations are shown just once.
- Composition of relational operators can be shown as below:
∏branch_name,amount(σloan_no=2948755428(Bank))
Rename: ρ
- The Rename operation is an unary operator used to rename the attributes of relation. It can be
shown as:
Ρa/b(r)
- Here, ‘b’ attribute of the relation r is renamed to ‘a’ attribute.
- For example, to rename ‘branch_name’ attribute to ‘cust_city’ of the relation Bank, we can do as
follow:
Ρcust_city/branch_name(Bank)
Union: ∪
- The union operation is binary operator (operate on pairs of relation). For union operator, the
relations to which we are using Union operator should have same attributes and also the domains
of all the attributes of those relations must be same. It can be shown as below:
∏cust_name(Borrower) ∪ ∏cust_name(Depositer)
12. 12 | P a g e
- Relation: r,s α β α β
A 1 A 2
A 2 B 3
B 1
r s
- r ∪ s:
α β
A 1
A 2
B 1
B 3
- In the above example, the union operation shows us all the set of attributes of both the relations
and the repeated ones are just shown once.
Set difference:
- The Set difference operation is a binary operator which works as set intersection. The two relations
involved in set interactions must also be union-compatible. It can be shown as below:
∏cust_name(Borrower) ∏cust_name(Depositer)
- Relation: r,s α β α β
A 1 A 2
A 2 B 3
B 1
r s
- r s: α β
A 1
B 1
B 3
- In the above example, the set operation shows us the tuples other than those which are in both the
relations.
13. 13 | P a g e
Cartesian product: x
- The Cartesian product operation is a binary operator used to combine each tuple of one relation to
each tuple of another relation. It can be shown as R x S.
- Relation: r,s
α β γ
A 1 E
A 2 F
B 3
B 4
r s
- r x s:
α β γ
A 1 E
A 1 F
A 2 E
A 2 F
B 3 E
B 3 F
B 4 E
B 4 F
- In the above example Cartesian product operation shows us the combination of each tuple of
relation r to each tuple of relation s.
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15.) Explain Entity Relationship Model
The entity-relational (E-R) data model was developed to facilitate database design by allowing
specification of an enterprise schema that represents the overall logical structure of a database.
The E-R model is very useful in mapping the meaning and interactions of real-world problem into a
conceptual schema. The E-R model employs three basic concepts: entity sets relationship sets, and the
attributes.
Entity Sets: An entity is a thing or object that is present in the real word which is distinguishable from
all other objects. For example, each person in the university is an entity. An entity has a set of
properties and the values for some set of properties may uniquely identify an entity.
An entity set is a set of entities of the same type that share the same properties, or attributes. For
example, a group of people who are instructor in the University can be defined as the entity set
instructor. An entity is represented by a set of attributes. Attributes are the detailed information
possessed by each member in an entity set. For example, Instructor entity may have attributes ID,
Name, dept_name and salary.
Each entity has a value for its attributes. For example, a particular instructor entity may have the value
GT31001 for ID, the value Karan for Name, the value CSE for dept_name and the value 50000 for salary.
Instructor E-R Symbol for Entity set
ID
name
salary
Rectangle shape divided into two parts indicates an Entity Set. The first part represents an Entity set
and the second part represents the attributes of that particular entity.
Relationship Sets: A relationship is an association among several entities. For, example, we can define
a relationship advisor that associates instructor Karan with the student Ranvijay. This means
relationship specifies that Karan is an advisor of student Ranvijay.
A Relationship set is a set of relationships of the same type. Formally, it is a mathematical relation on
n ≥ 2 (possibly non distinct) entity sets. If E1, E2, … , En are entity sets, then a relationship set R is a
subset of
{(e1, e2, .., en) |e1 E1, e2 E2, … , en En}
Where (e1, e2, .., en) is a relationship.
A relationship can always be not possible with a single valued attributes i.e. it may sometime require
more values to represent. For such case, we should create a multi-valued attribute.
It is not necessary that there is only one relation between the several entities. There may be chances
for two relations between the entities or three relation or many more. For example, a student and
instructor are associated with proj_guide but there may be chances that those two entity sets are also
associated with eval_for. This is shown in below figure.
15. 15 | P a g e
The number of entity sets that participate in a relationship set is the degree of the relationship set. A
binary relationship set is of degree 2; a ternary relationship set is of degree 3.
advisor E-R symbol relationship sets
Diamond shape represents relationship sets.
Attributes: For each attribute, there is a set of permitted values, called the domain, or value set of that
attribute.
Formally, an attribute of an entity set is a function that maps from the entity set into domain. Since, an
entity set may have several attributes; each entity can be described by a set of (attribute, data value)
pairs, one pair for each attribute of the entity set. For example, a particular instructor may be
described by the set {(ID,GT31001),(Name, Karan),(dept_name, CSE),(salary,50000)}, meaning that the
entity describes a person named Karan whose instructor ID is GT31001, who is a member of CSE
department with the salary of 50000. The attribute values describing an entity constitute a significant
portion of the data stored in the database.
An attribute, as used in the E-R model, can be characterized by the following attribute types.
Simple Attributes: Attributes which can’t be divided into subparts are called Simple Attributes.
For example, Age of a person is simple attribute, Employee Number is simple Attribute.
Composite Attributes: Attributes which can be divided into subparts. These subparts are basic
attributes with independent meanings of their own.
For example, Name of a person is composite attribute as it can be further divided into First Name,
Middle Name and Last Name.
Single – Valued Attribute: A single valued attribute can have only a single value.
For example a person can have only one 'date of birth', 'age' etc. That is a single valued attributes can
have only single value. But it can be simple or composite attribute. That is 'date of birth' is a composite
attribute, 'age' is a simple attribute. But both are single valued attributes.
Multi – Valued Attribute: Multi valued attributes can have multiple values. For instance a person may
have multiple phone numbers, multiple degrees etc.
Derived Attribute: An attribute that’s value is derived from a stored attribute.
For example, age and its value are derived from the stored attribute Date of Birth.
16.) Explain Weak Entity Set.
An entity set that does not have sufficient attributes to from a primary key is termed as weak entity
set. An entity set that has a primary key is termed as solid entity set.
For a weak entity set to be meaningful, it must be associated with another entity set, called
indentifying or owned entity set. Every weak entity must be associated with an identifying entity; that
is, the weak entity set is to be existence dependent on the identifying entity set. The relationship
associating the weak entity set with the identifying entity set is called identifying relationship.
The discriminator of a weak entity set is a set of attributes that allows the distinction to be made
among the entities in the weak entity set that depends on one particular strong entity. For example,
the discriminator of the weak entity set section consists of attributes sec_id, year and semester, since,
for each course, this set of attributes uniquely identifies one single section for that course. The
discriminator of weak entity set is also called partial key of the set.
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The primary key of the weak entity set is formed by the primary of the identifying entity set, plus the
weak entity set’s discriminator. In case of the entity set section, its primary key is {course_id, sec_id,
yaer, semester}, where course_id is the primary key of the identifying entity set, namely course, and
{sec_id, year, semester) distinguishes section entities for the same course.
In E-R diagrams, a weak entity set is depicted via rectangle, like a strong entity set, but there are two
main differences:
- The discriminator of a weak entity in underlined with a dashed, rather than a solid line.
- The relationship set connecting the weak entity set to the identifying strong set is depicted by a
double diamond.
Double lines indicate total participation of an entity in a relationship set.
Double diamonds represent identifying relationship sets link to weak entity set.