This document provides an overview of the key concepts in entity-relationship (ER) modeling for database design. It begins with an outline of the database design process and an example database application for a company (COMPANY). It then defines the core components of ER modeling, including entities, attributes, relationships, relationship types, and ER diagrams. The document presents the initial ER design for the COMPANY database and refines it by introducing relationships. It also covers additional concepts like weak entity types, constraints, and recursive relationships. The overall summary provides a high-level introduction to ER modeling concepts and how they are applied to design a sample database schema.
This document provides an overview of database system concepts and architecture. It discusses data models, schemas, instances, and states. It also describes the three-schema architecture, data independence, DBMS languages and interfaces, database system utilities and tools, and centralized and client-server architectures. Key classification of DBMSs are also covered.
The document discusses the entity-relationship (ER) model for conceptual database design. It describes the basic constructs of the ER model including entities, attributes, relationships, keys, and various modeling choices. The ER model is useful for capturing the semantics of an application domain and producing a conceptual schema before logical and physical design.
4 the relational data model and relational database constraintsKumar
The document discusses the relational data model and constraints in relational databases. It begins by defining key concepts in the relational model such as relations, tuples, attributes, domains and relation schemas. It then covers relational constraints including key constraints, entity integrity constraints, and referential integrity constraints. Examples are provided to illustrate these concepts and constraints. The chapter aims to provide an overview of the formal relational model and constraints that must hold in relational databases.
Data Modeling Using the EntityRelationship (ER) Modelsontumax
The document provides an overview of entity-relationship (ER) modeling and the ER diagram notation. It discusses key ER modeling concepts like entities, attributes, relationships, and relationship constraints. An example database schema for a company is used to illustrate these concepts. The example requirements are analyzed to identify entity types, relationship types, and refine the initial design. Notation for displaying entity types, relationships, and constraints in ER diagrams is also described.
This document provides an overview of databases and database management systems (DBMS). It discusses how databases evolved from file systems to address flaws in data management. It describes what a DBMS is and its functions in managing the database structure and controlling data access. The document also summarizes different database models including hierarchical, network, relational, entity-relationship, and object-oriented models. It highlights advantages and disadvantages of each model.
Dbms 10: Conversion of ER model to Relational ModelAmiya9439793168
The document discusses the conversion of an entity-relationship (ER) model to a relational model by describing how different ER constructs such as strong/weak entities, relationships, composite/multi-valued attributes, generalization/specialization, and aggregation map to relational schemas and tables. Strong entities become tables with their primary key and attributes, while weak entities include the primary key of their identifying entity. Relationships become tables linking the participating entity primary keys. Descriptive attributes may also be included.
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.
This document provides an overview of database system concepts and architecture. It discusses data models, schemas, instances, and states. It also describes the three-schema architecture, data independence, DBMS languages and interfaces, database system utilities and tools, and centralized and client-server architectures. Key classification of DBMSs are also covered.
The document discusses the entity-relationship (ER) model for conceptual database design. It describes the basic constructs of the ER model including entities, attributes, relationships, keys, and various modeling choices. The ER model is useful for capturing the semantics of an application domain and producing a conceptual schema before logical and physical design.
4 the relational data model and relational database constraintsKumar
The document discusses the relational data model and constraints in relational databases. It begins by defining key concepts in the relational model such as relations, tuples, attributes, domains and relation schemas. It then covers relational constraints including key constraints, entity integrity constraints, and referential integrity constraints. Examples are provided to illustrate these concepts and constraints. The chapter aims to provide an overview of the formal relational model and constraints that must hold in relational databases.
Data Modeling Using the EntityRelationship (ER) Modelsontumax
The document provides an overview of entity-relationship (ER) modeling and the ER diagram notation. It discusses key ER modeling concepts like entities, attributes, relationships, and relationship constraints. An example database schema for a company is used to illustrate these concepts. The example requirements are analyzed to identify entity types, relationship types, and refine the initial design. Notation for displaying entity types, relationships, and constraints in ER diagrams is also described.
This document provides an overview of databases and database management systems (DBMS). It discusses how databases evolved from file systems to address flaws in data management. It describes what a DBMS is and its functions in managing the database structure and controlling data access. The document also summarizes different database models including hierarchical, network, relational, entity-relationship, and object-oriented models. It highlights advantages and disadvantages of each model.
Dbms 10: Conversion of ER model to Relational ModelAmiya9439793168
The document discusses the conversion of an entity-relationship (ER) model to a relational model by describing how different ER constructs such as strong/weak entities, relationships, composite/multi-valued attributes, generalization/specialization, and aggregation map to relational schemas and tables. Strong entities become tables with their primary key and attributes, while weak entities include the primary key of their identifying entity. Relationships become tables linking the participating entity primary keys. Descriptive attributes may also be included.
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 key design issues in entity-relationship (ER) database schemas including:
1) Distinguishing between entities and attributes and how they are modeled, such as whether a phone number is an attribute of employees or its own entity.
2) Modeling relationships between entities as either binary or ternary relationships and how ternary relationships can be broken down into multiple binary relationships.
3) Relationship design considerations like whether a relationship such as an employee working in a department should allow for multiple time periods or just one.
The document discusses object-oriented databases and their advantages over traditional relational databases, including their ability to model more complex objects and data types. It covers fundamental concepts of object-oriented data models like classes, objects, inheritance, encapsulation, and polymorphism. Examples are provided to illustrate object identity, object structure using type constructors, and how an object-oriented model can represent relational data.
Dbms classification according to data modelsABDUL KHALIQ
CLASSIFICATION ACCORDING TO DATA MODELS
Hierarchal Model
In a hierarchical data model, data are organized into a tree-like structure.
Network Model
based on an enlargement of the concept of hierarchical data bases.
Relational Model
Data are stored in tables
Object Oriented model
Object oriented data base systems are the most recent development in data base technology.
Introduction
Definations
Advantages and Disadvantages
PowerPoint Presentation
PowerPoint Presentation for free
This document is from a textbook on database systems. It introduces fundamental concepts such as what a database is, the role of database management systems, and typical database functionality including defining schemas, loading data, querying, and concurrency control. It also discusses different types of database users and the advantages of the database approach such as data sharing and integrity enforcement. Examples of entity-relationship diagrams and database relations are provided to illustrate conceptual data modeling.
This document discusses the entity-relationship (ER) model for conceptual database design. It defines key concepts like entities, attributes, relationships, keys, and participation constraints. Entities can be strong or weak, and attributes can be simple, composite, multi-valued, or derived. Relationships associate entities and can specify cardinality like one-to-one, one-to-many, or many-to-many. The ER model diagrams the structure and constraints of a database before its logical and physical implementation.
This document discusses database languages used in database management systems (DBMS). It describes three types of database languages: data definition language (DDL) used to define and modify the database schema; data manipulation language (DML) used to insert, update, delete and retrieve data; and data control language (DCL) used to control access privileges. Examples are provided for common statements in each language type like CREATE, ALTER, DROP for DDL and INSERT, UPDATE, DELETE, SELECT for DML. Case sensitivity and data types are also briefly covered.
The document provides an introduction to database management systems (DBMS). It can be summarized as follows:
1. A DBMS allows for the storage and retrieval of large amounts of related data in an organized manner. It removes data redundancy and allows for fast retrieval of data.
2. Key components of a DBMS include the database engine, data definition subsystem, data manipulation subsystem, application generation subsystem, and data administration subsystem.
3. A DBMS uses a data model to represent the organization of data in a database. Common data models include the entity-relationship model, object-oriented model, and relational model.
This document discusses object-relational databases and how they extend relational databases to support complex data types and object-oriented features. It covers topics like nested relations, structured types, inheritance, and reference types. It provides examples of how to define complex types and values, perform queries using complex attributes, and map object-oriented concepts to the relational model.
This document discusses different types of database models including high-level, representation, and low-level models. It describes the entity-relationship model as a high-level model that focuses on entities, attributes, and relationships without representation concerns. The relational model and hierarchical model are presented as representation models that describe how data is physically structured and stored. Key aspects of each model like structure, terminology, advantages, and disadvantages are summarized.
This document provides an introduction to SQL and database systems. It begins with example tables to demonstrate SQL concepts. It then covers the objectives of SQL, including allowing users to create database structures, manipulate data, and perform queries. Various SQL concepts are introduced such as data types, comparison operators, logical operators, and arithmetic operators. The document also discusses SQL statements for schema and catalog definitions, data definition, data manipulation, and other operators. Example SQL queries are provided to illustrate concepts around selecting columns, rows, sorting, aggregation, grouping, and more.
The document provides an overview of ADO.NET and its core classes:
- ADO.NET uses datasets to store data from a database in memory and data provider objects like connections, commands, and data adapters to retrieve and update data in the database.
- The .NET Framework includes the SQL Server and OLE DB data providers, which provide classes like SqlConnection and OleDbConnection to connect to databases.
- Core classes like SqlCommand represent SQL statements, and SqlDataAdapter links commands and connections to datasets to load and save data.
This document discusses SQL commands for creating tables, adding data, and enforcing integrity constraints. It covers the core SQL commands: DDL for defining schema, DML for manipulating data, DCL for controlling access, DQL for querying data, and TCL for transactions. Specific topics summarized include data types, primary keys, foreign keys, indexes, views, stored procedures, functions and triggers. Integrity constraints like NOT NULL, UNIQUE, CHECK, DEFAULT are explained. The document also covers SQL queries with filtering, sorting, patterns and ranges. Authorization using GRANT and REVOKE commands is briefly covered.
This slide explains the conversion procedure from ER Diagram to Relational Schema.
1. Entity set to Relation
2. Relationship set to Relation
3. Attributes to Columns, Primary key, Foreign Keys
This document discusses entity-relationship (E-R) modeling concepts including specialization, generalization, aggregation, and redundant relationships. It provides definitions and examples of each concept. Specialization defines subclasses based on distinguishing attributes. Generalization defines a superclass from common attributes of subclasses. Aggregation treats relationships as higher-level entities. An E-R diagram example shows representing aggregation. Another example shows a diagram with redundant relationships.
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.
Object relational database management systemSaibee Alam
this presentation provide a full explanation of object relational database management system. its a part of advanced database management system. important topic of computer science if you are UG/PG student or preparing for some competitive exam.
This document provides an introduction to database management systems (DBMS). It discusses what a DBMS is, common database applications, and drawbacks of using file systems to store data that DBMS aim to address, such as data redundancy, integrity issues, and concurrent access problems. It also summarizes key components of a DBMS, including its logical and physical levels of abstraction, data models, data definition and manipulation languages, storage management, query processing, transaction management, and common database architectures.
Database architecture uses programming languages to design software for businesses, focusing on designing, developing, implementing, and maintaining computer programs. The architecture of a database system depends on the computer system it runs on, and a database system can be centralized or use a client-server model with client machines for users and a server for the database system.
Cardinality and participation constraintsNikhil Deswal
Cardinality and participation constraints define the relationships between entities in a database. Cardinality constraints specify the maximum number of entities that can participate in a relationship, such as one-to-one, one-to-many, or many-to-many. Participation constraints indicate whether participation of an entity in a relationship is total, meaning every entity must participate, or partial, meaning only some entities participate. These constraints help maintain data integrity and ensure only valid relationships are stored in the database.
This document discusses file processing systems and their components. It defines key terms like field, record, and file. It describes how a file processing system organizes and stores data in independent files of records without using databases. It classifies different types of files by their functions, such as master files, transaction files, report files, work files, program files, and text files. It outlines some advantages of file processing systems like lower costs and ease of use, as well as disadvantages like data redundancy, difficult data access, isolation, integrity, and security issues.
Data modeling using the entity relationship modelJafar Nesargi
The document describes key concepts in entity relationship modeling including entity types, attributes, relationships, keys, and constraints. It provides an example database application to track employees, departments, and projects within a company. It then defines entity types for departments, projects, employees, and dependents with their attributes. It also describes relationship types, cardinalities, roles, and other modeling constructs used to design the conceptual schema.
This chapter discusses data modeling using the entity-relationship model. It includes figures illustrating the phases of database design, ER schema diagrams for a COMPANY database, different entity types and relationships, and examples of conceptual schemes for various databases modeled using ER diagrams.
The document discusses several key design issues in entity-relationship (ER) database schemas including:
1) Distinguishing between entities and attributes and how they are modeled, such as whether a phone number is an attribute of employees or its own entity.
2) Modeling relationships between entities as either binary or ternary relationships and how ternary relationships can be broken down into multiple binary relationships.
3) Relationship design considerations like whether a relationship such as an employee working in a department should allow for multiple time periods or just one.
The document discusses object-oriented databases and their advantages over traditional relational databases, including their ability to model more complex objects and data types. It covers fundamental concepts of object-oriented data models like classes, objects, inheritance, encapsulation, and polymorphism. Examples are provided to illustrate object identity, object structure using type constructors, and how an object-oriented model can represent relational data.
Dbms classification according to data modelsABDUL KHALIQ
CLASSIFICATION ACCORDING TO DATA MODELS
Hierarchal Model
In a hierarchical data model, data are organized into a tree-like structure.
Network Model
based on an enlargement of the concept of hierarchical data bases.
Relational Model
Data are stored in tables
Object Oriented model
Object oriented data base systems are the most recent development in data base technology.
Introduction
Definations
Advantages and Disadvantages
PowerPoint Presentation
PowerPoint Presentation for free
This document is from a textbook on database systems. It introduces fundamental concepts such as what a database is, the role of database management systems, and typical database functionality including defining schemas, loading data, querying, and concurrency control. It also discusses different types of database users and the advantages of the database approach such as data sharing and integrity enforcement. Examples of entity-relationship diagrams and database relations are provided to illustrate conceptual data modeling.
This document discusses the entity-relationship (ER) model for conceptual database design. It defines key concepts like entities, attributes, relationships, keys, and participation constraints. Entities can be strong or weak, and attributes can be simple, composite, multi-valued, or derived. Relationships associate entities and can specify cardinality like one-to-one, one-to-many, or many-to-many. The ER model diagrams the structure and constraints of a database before its logical and physical implementation.
This document discusses database languages used in database management systems (DBMS). It describes three types of database languages: data definition language (DDL) used to define and modify the database schema; data manipulation language (DML) used to insert, update, delete and retrieve data; and data control language (DCL) used to control access privileges. Examples are provided for common statements in each language type like CREATE, ALTER, DROP for DDL and INSERT, UPDATE, DELETE, SELECT for DML. Case sensitivity and data types are also briefly covered.
The document provides an introduction to database management systems (DBMS). It can be summarized as follows:
1. A DBMS allows for the storage and retrieval of large amounts of related data in an organized manner. It removes data redundancy and allows for fast retrieval of data.
2. Key components of a DBMS include the database engine, data definition subsystem, data manipulation subsystem, application generation subsystem, and data administration subsystem.
3. A DBMS uses a data model to represent the organization of data in a database. Common data models include the entity-relationship model, object-oriented model, and relational model.
This document discusses object-relational databases and how they extend relational databases to support complex data types and object-oriented features. It covers topics like nested relations, structured types, inheritance, and reference types. It provides examples of how to define complex types and values, perform queries using complex attributes, and map object-oriented concepts to the relational model.
This document discusses different types of database models including high-level, representation, and low-level models. It describes the entity-relationship model as a high-level model that focuses on entities, attributes, and relationships without representation concerns. The relational model and hierarchical model are presented as representation models that describe how data is physically structured and stored. Key aspects of each model like structure, terminology, advantages, and disadvantages are summarized.
This document provides an introduction to SQL and database systems. It begins with example tables to demonstrate SQL concepts. It then covers the objectives of SQL, including allowing users to create database structures, manipulate data, and perform queries. Various SQL concepts are introduced such as data types, comparison operators, logical operators, and arithmetic operators. The document also discusses SQL statements for schema and catalog definitions, data definition, data manipulation, and other operators. Example SQL queries are provided to illustrate concepts around selecting columns, rows, sorting, aggregation, grouping, and more.
The document provides an overview of ADO.NET and its core classes:
- ADO.NET uses datasets to store data from a database in memory and data provider objects like connections, commands, and data adapters to retrieve and update data in the database.
- The .NET Framework includes the SQL Server and OLE DB data providers, which provide classes like SqlConnection and OleDbConnection to connect to databases.
- Core classes like SqlCommand represent SQL statements, and SqlDataAdapter links commands and connections to datasets to load and save data.
This document discusses SQL commands for creating tables, adding data, and enforcing integrity constraints. It covers the core SQL commands: DDL for defining schema, DML for manipulating data, DCL for controlling access, DQL for querying data, and TCL for transactions. Specific topics summarized include data types, primary keys, foreign keys, indexes, views, stored procedures, functions and triggers. Integrity constraints like NOT NULL, UNIQUE, CHECK, DEFAULT are explained. The document also covers SQL queries with filtering, sorting, patterns and ranges. Authorization using GRANT and REVOKE commands is briefly covered.
This slide explains the conversion procedure from ER Diagram to Relational Schema.
1. Entity set to Relation
2. Relationship set to Relation
3. Attributes to Columns, Primary key, Foreign Keys
This document discusses entity-relationship (E-R) modeling concepts including specialization, generalization, aggregation, and redundant relationships. It provides definitions and examples of each concept. Specialization defines subclasses based on distinguishing attributes. Generalization defines a superclass from common attributes of subclasses. Aggregation treats relationships as higher-level entities. An E-R diagram example shows representing aggregation. Another example shows a diagram with redundant relationships.
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.
Object relational database management systemSaibee Alam
this presentation provide a full explanation of object relational database management system. its a part of advanced database management system. important topic of computer science if you are UG/PG student or preparing for some competitive exam.
This document provides an introduction to database management systems (DBMS). It discusses what a DBMS is, common database applications, and drawbacks of using file systems to store data that DBMS aim to address, such as data redundancy, integrity issues, and concurrent access problems. It also summarizes key components of a DBMS, including its logical and physical levels of abstraction, data models, data definition and manipulation languages, storage management, query processing, transaction management, and common database architectures.
Database architecture uses programming languages to design software for businesses, focusing on designing, developing, implementing, and maintaining computer programs. The architecture of a database system depends on the computer system it runs on, and a database system can be centralized or use a client-server model with client machines for users and a server for the database system.
Cardinality and participation constraintsNikhil Deswal
Cardinality and participation constraints define the relationships between entities in a database. Cardinality constraints specify the maximum number of entities that can participate in a relationship, such as one-to-one, one-to-many, or many-to-many. Participation constraints indicate whether participation of an entity in a relationship is total, meaning every entity must participate, or partial, meaning only some entities participate. These constraints help maintain data integrity and ensure only valid relationships are stored in the database.
This document discusses file processing systems and their components. It defines key terms like field, record, and file. It describes how a file processing system organizes and stores data in independent files of records without using databases. It classifies different types of files by their functions, such as master files, transaction files, report files, work files, program files, and text files. It outlines some advantages of file processing systems like lower costs and ease of use, as well as disadvantages like data redundancy, difficult data access, isolation, integrity, and security issues.
Data modeling using the entity relationship modelJafar Nesargi
The document describes key concepts in entity relationship modeling including entity types, attributes, relationships, keys, and constraints. It provides an example database application to track employees, departments, and projects within a company. It then defines entity types for departments, projects, employees, and dependents with their attributes. It also describes relationship types, cardinalities, roles, and other modeling constructs used to design the conceptual schema.
This chapter discusses data modeling using the entity-relationship model. It includes figures illustrating the phases of database design, ER schema diagrams for a COMPANY database, different entity types and relationships, and examples of conceptual schemes for various databases modeled using ER diagrams.
The document discusses database normalization and various normal forms including first normal form (1NF), second normal form (2NF), third normal form (3NF), and Boyce-Codd normal form (BCNF). It provides examples of tables that are and are not in different normal forms and describes how to decompose tables to higher normal forms by removing functional dependencies between non-key attributes or attributes within a candidate key.
The document discusses various commands used in database management systems like Oracle. It explains commands to create, alter, delete and modify database tables. Additional commands covered include inserting, updating, selecting and displaying data from tables. Examples are provided for each command syntax. The document also discusses creating tables from other tables and inserting records between tables using queries. Finally, multiple exercises are provided to apply the covered commands.
SQL databases authorize access to objects through a system of privileges. Nine privileges control access to relations, including SELECT, INSERT, and DELETE. Privileges can be granted to users and PUBLIC using GRANT statements, and revoked using REVOKE. Grant diagrams visually represent privilege relationships between users as nodes and edges to show who has been granted which privileges, directly or indirectly. Edges are added or removed from the diagram based on GRANT and REVOKE operations to model changes in privileges over time.
Aggregate functions summarize data from multiple rows into a single value. Common aggregate functions include SUM, COUNT, AVG, MIN, and MAX. SUM adds values, COUNT counts rows, AVG calculates the average, and MIN and MAX find the minimum or maximum value. When using aggregate functions, all non-aggregate columns in the select clause must be included in the GROUP BY clause.
The document discusses relational algebra and its operators. It introduces the five basic relational algebra operators - project, restrict, cartesian product, union and difference. It provides examples of how each operator works and how they can be combined. The operators allow querying relational databases at a logical level and provide data independence from the physical storage structure.
This document discusses debugging techniques for database crashes and errors. It begins by explaining how to determine if a crash was caused by an application error or server issue. It then covers analyzing the error log to understand the problem and find clues like the crashing query. Debugging techniques like resolving stack traces and determining assertion types are also outlined. Finally, examples of error log analysis are provided.
Data integrity refers to maintaining accurate and consistent data throughout its lifecycle. It is important for information security as it prevents unauthorized changes to data from storage, retrieval, processing or malicious intent. Entity integrity and referential integrity help ensure data integrity. Entity integrity uses primary keys to uniquely identify rows and prevent duplicates. Referential integrity uses foreign keys to link data across tables and ensure changes are propagated properly.
This document provides an overview of nested queries in SQL, including examples and explanations of:
- What nested queries are and how they are structured using subqueries
- How to write nested queries using operators like IN, EXISTS, and correlated subqueries
- Examples of nested queries for SELECT, UPDATE, DELETE, and the FROM clause using data on country fertility rates
- Advantages of nested queries like readability and ability to isolate parts of statements
The document discusses database system concepts and architecture. It covers topics such as data models, schemas and instances; DBMS architecture and data independence; database languages and interfaces; the database system environment; and classification of database management systems. Specifically, it describes the three-schema architecture used to support data independence, different types of database languages, interfaces for users and programmers, components of a DBMS, and utilities used in database systems.
Functional dependency defines a relationship between attributes in a table where a set of attributes determine another attribute. There are different types of functional dependencies including trivial, non-trivial, multivalued, and transitive. An example given is a student table with attributes Stu_Id, Stu_Name, Stu_Age which has the functional dependency of Stu_Id->Stu_Name since the student ID uniquely identifies the student name.
Fundamentals of database system - Data Modeling Using the Entity-Relationshi...Mustafa Kamel Mohammadi
In this chapter you will learn
Relational data model concepts
What is entity?
What is attribute and it’s types
What is relationship?
What is an Entity-Relationship data model?
Relational data model constraints
Characteristics of relation
The document discusses data modeling and the entity-relationship model. It defines key concepts like entities, attributes, relationships, and cardinalities. Entities have attributes and can be connected through relationships. Relationships can be one-to-one, one-to-many, many-to-one, or many-to-many depending on how many entities can be associated with each other. The entity-relationship model is useful for conceptual database design and represents these concepts visually in diagrams.
Dbms ii mca-ch5-ch6-relational algebra-2013Prosanta Ghosh
The document discusses relational algebra, which defines a set of operations for the relational model. The relational algebra operations can be divided into two groups: set operations from mathematical set theory including UNION, INTERSECTION, and SET DIFFERENCE; and operations developed specifically for relational databases including SELECT, PROJECT, and JOIN. The six basic relational algebra operators are SELECT, PROJECT, UNION, INTERSECTION, SET DIFFERENCE, and CARTESIAN PRODUCT. RELATIONAL expressions allow sequences of these operations to be combined to retrieve and manipulate data from relations.
The document discusses SQL data manipulation topics including retrieving data using SELECT statements, filtering rows with WHERE clauses, sorting results with ORDER BY, grouping data with GROUP BY, restricting groups with HAVING, and using subqueries. It provides examples of each concept and rules for writing SQL statements and using different clauses.
This document provides an overview of SQL programming. It covers the history of SQL and SQL Server, SQL fundamentals including database design principles like normalization, and key SQL statements like SELECT, JOIN, UNION and stored procedures. It also discusses database objects, transactions, and SQL Server architecture concepts like connections. The document is intended as a training guide, walking through concepts and providing examples to explain SQL programming techniques.
This document summarizes a seminar presentation on database triggers. It defines a database trigger as procedural code that is automatically executed in response to certain events on a table or view. It discusses the types of events that can fire a trigger, including DML, DDL, system, and user events. It also outlines the need for triggers to enforce business rules, audit changes, and enhance performance. The document provides details on the major features of triggers, including the different types of triggers based on timing (before and after), scope (row and statement), and triggering event (DML, DDL, system, user). It concludes with an example of the syntax for creating a database trigger.
This week's session is on SQL Views: what they are, how to create them, how to insert, update and delete data through them along with other key details to know!
Watch the video at:
http://www.aaronbuma.com/2016/01/views/
This document discusses the entity-relationship (ER) model for data modeling. It provides an overview of the database design process and introduces an example database schema for a company. The key concepts of the ER model are explained, including entities, attributes, entity types, keys, relationships, relationship types, and ER diagrams. For the example company database, initial entity types and relationships are identified from the requirements. The design is then refined by introducing additional relationships. Constraints for relationships and weak entity types are also covered.
This document provides an overview of entity-relationship (ER) modeling and its application to conceptual database design. It discusses key ER concepts like entities, attributes, relationships and relationship types. An example database application for a company is used to demonstrate how these concepts are identified and modeled. The initial ER design for this example captures entity types for departments, projects, employees and dependents along with some of their attributes. The design is then refined by introducing relationship types to fully represent the requirements.
This document discusses conceptual database design using the Entity-Relationship (ER) model. It provides an overview of the database design process and introduces an example database application for a company. The key concepts of the ER model are explained, including entities, attributes, relationships and relationship types. Finally, an ER diagram is shown modeling the entity types and relationships for the example company database application.
The document discusses entity-relationship (ER) modeling concepts including:
- Entity types such as EMPLOYEE, DEPARTMENT, PROJECT, and DEPENDENT that will be part of the example COMPANY database.
- Relationship types such as WORKS_FOR, MANAGES, WORKS_ON, CONTROLS, SUPERVISION, and DEPENDENTS_OF that relate the entity types.
- ER diagram notation used to visually represent the entities, attributes, and relationships between entities for the COMPANY schema.
This chapter discusses data modeling using the Entity-Relationship (ER) model. It covers key concepts such as entities, attributes, relationships, and relationship types. It presents an example database application for a company and develops its ER diagram. The chapter also discusses ER diagram notation for representing various model constructs including weak entities, recursive relationships, and structural constraints. Finally, it briefly mentions tools for data modeling and limitations of current tools.
Chapter-3 Data Modeling Using the Entity-Relationship ModelRaj vardhan
The document describes conceptual database design using the entity-relationship (ER) model. It discusses key concepts of the ER model including entities, attributes, relationships, and relationship constraints. An example ER diagram is presented for a COMPANY database with entities for employees, departments, and projects. Relationships include employees working for departments and departments controlling projects. The summary provides an overview of the important concepts and examples covered in the document related to conceptual database design using the ER model.
The document provides an overview of entity-relationship (ER) modeling concepts including entities, attributes, relationships, and ER diagram notation. It then presents an example database application for a company (COMPANY) and defines the entity types, relationship types, and attributes that would be included in an ER diagram for the COMPANY database schema. Key concepts covered include entities, attributes, relationships, cardinalities, participation constraints, and weak entity types.
This document provides an overview of entity-relationship (ER) modeling concepts for database design. It defines key ER modeling concepts like entities, attributes, entity types, relationships, relationship types, weak entities, and constraints. It also explains how to represent these concepts in ER diagrams. As an example, it analyzes the requirements for a sample COMPANY database and designs the initial entity types and relationship types that would be represented in an ER diagram for this database.
This document provides an overview of the key concepts in entity-relationship modeling including the three main elements - entity sets, attributes, and relationships. It defines these elements and provides examples like entities for departments, professors, students. It also describes other ER modeling concepts such as keys, single and multi-valued attributes, mapping cardinalities, participation constraints, weak entity sets, and identifying weak entity types. The document is presented as a lecture on ER modeling with examples to illustrate each concept.
The document provides an overview of conceptual database design using the Entity-Relationship (ER) model. It describes the basic constructs of the ER model including entities, relationships, attributes, and additional features like weak entities, inheritance hierarchies, and aggregation. It also discusses modeling choices like representing concepts as entities or attributes, binary vs n-ary relationships. Constraints that can be expressed in the ER model are covered, along with the subjective nature of ER design.
The document discusses the relational data model and ER model for conceptual database design. It covers key concepts such as entities, attributes, relationships, constraints, and ER diagrams. The relational data model uses tables made up of rows and columns to store data, with each table representing an entity. Relationships between entities can be one-to-one, one-to-many, many-to-one, or many-to-many. The ER model is used to design the conceptual schema and represent entities, attributes, and relationships visually using diagrams. The conceptual schema is later transformed into a logical schema for a specific database implementation.
The document describes concepts related to entity relationship modeling including:
- Entity types represent real world objects like employees, departments, etc. and have attributes.
- Relationship types define relationships between entity types like works_for between employees and departments.
- Keys uniquely identify entities and attributes can be single/multi-valued, simple/composite.
- The example models a company database with entities for departments, projects, employees and dependents along with their attributes and relationships.
The document describes concepts related to entity relationship modeling including:
- Entity types represent real world objects like employees, departments, etc. and have attributes.
- Relationship types define relationships between entity types like works_for between employees and departments.
- An example database schema for a company is presented with entity types for departments, projects, employees, and dependents along with attributes and relationships.
- Additional concepts covered include keys, cardinality, participation constraints, and weak entity types.
The document discusses the Entity-Relationship (E-R) model, which was proposed by Dr. Peter Chen in the 1970s as a way to model real-world entities and their relationships. The E-R model uses entities, attributes, and relationships, and allows these concepts to be visually represented in E-R diagrams using basic graphical symbols like rectangles, ellipses, and diamonds. The document also covers E-R modeling concepts like keys, entity types, relationship types, participation constraints, and weak entity sets.
The document discusses concepts related to entity relationship (ER) modeling, including:
- It provides an example database application for a company to illustrate ER concepts.
- It describes key ER modeling concepts such as entities, attributes, relationships, relationship types, and weak entities.
- It explains ER diagram notation for representing entities, attributes, relationships, and cardinalities.
- It shows an ER diagram for the example company database schema.
This document discusses key concepts of the relational data model including relations, tuples, attributes, domains, relation schemas, and relation states. It defines these concepts formally and provides examples. Key constraints that must hold for relations are covered, including superkeys, candidate keys, and primary keys. The document is part of a lecture on the relational data model and relational database constraints.
The document discusses database design and normalization. It covers entity relationship modeling including entities, attributes, relationships and cardinality. It also discusses various normal forms including 1NF, 2NF, 3NF and decomposition of tables to eliminate anomalies and redundancy. The purpose of normalization is to organize data to avoid inconsistencies and improve performance when making changes to the database.
The document discusses database design and entity relationship modeling. It defines key concepts such as entities, attributes, relationships and cardinality. It also covers entity relationship diagrams, data types, keys and normalization. The key points covered are:
- Entities can be defined as objects that can be uniquely identified and have attributes.
- Relationships define how entities are connected or related to each other.
- An entity relationship diagram visually represents these entities, attributes and relationships.
- Different types of keys like primary keys and foreign keys are used to link and identify entities.
- Normalization aims to reduce data redundancy and optimize database design.
RDBMS.ppt What is RDBMS RDBMS stands for Relational Database Management System.SHAKIR325211
What is RDBMS RDBMS stands for Relational Database Management System. RDBMS stands for Relational Database Management System.
All modern database management systems like SQL, MS SQL Server, IBM DB2, ORACLE, My-SQL, and Microsoft Access are based on RDBMS.
It is called Relational Database Management System (RDBMS) because it is based on the relational model introduced by E.F. Codd.Brief History of RDBMS
From 1970 to 1972, E.F. Codd published a paper to propose using a relational database model.
RDBMS is originally based on E.F. Codd's relational model invention.A relational database is the most commonly used database. It contains several tables, and each table has its primary key.
Due to a collection of an organized set of tables, data can be accessed easily in RDBMS.Everything in a relational database is stored in the form of relations. The RDBMS database uses tables to store data. A table is a collection of related data entries and contains rows and columns to store data. Each table represents some real-world objects such as person, place, or event about which information is collected. The organized collection of data into a relational table is known as the logical view of the database.
A row of a table is also called a record or tuple. It contains the specific information of each entry in the table. It is a horizontal entity in the table. For example, The above table contains 5 records.
Properties of a row:
No two tuples are identical to each other in all their entries.
All tuples of the relation have the same format and the same number of entries.
The order of the tuple is irrelevant. They are identified by their content, not by their position.The domain refers to the possible values each attribute can contain. It can be specified using standard data types such as integers, floating numbers, etc. For example, An attribute entitled Marital_Status may be limited to married or unmarried values.
NULL Values
The NULL value of the table specifies that the field has been left blank during record creation. It is different from the value filled with zero or a field that contains space.
Data Integrity
There are the following categories of data integrity exist with each RDBMS:Entity integrity: It specifies that there should be no duplicate rows in a table.
Domain integrity: It enforces valid entries for a given column by restricting the type, the format, or the range of values.
Referential integrity specifies that rows cannot be deleted, which are used by other records.
User-defined integrity: It enforces some specific business rules defined by users. These rules are different from the entity, domain, or referential integrity.Generalization is like a bottom-up approach in which two or more entities of lower level combine to form a higher level entity if they have some attributes in common.
In generalization, an entity of a higher level can also combine with the entities of the lower level to form a further higher level entity.
Generalization
The document discusses database design concepts including the entity-relationship model, normalization, and functional dependencies. It provides descriptions of key concepts such as entities, attributes, relationships, and mapping approaches from ER diagrams to relational schemas. It also covers normal forms up to BCNF and the goals of normalization to reduce data redundancy and anomalies.
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The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
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