The document provides information on various topics related to database management systems including the entity-relationship (ER) model, ER diagram components and notations, relational keys, integrity constraints, generalization, specialization, aggregation, relation algebra, and joins. It describes the ER model and how an ER diagram visually represents the relationships between entities. It also discusses how to reduce an ER diagram to a set of tables and the different normalization forms to remove data redundancy and anomalies from database tables.
The document discusses database normalization and Codd's rules for relational database management systems (RDBMS). It covers several key points:
- Database normalization aims to reduce anomalies like inconsistencies that can occur during database operations by decomposing tables and removing redundant or dependent data.
- Codd proposed 13 rules for a database to be considered a true RDBMS, including that the data be structured relationally in tables, support query languages, and ensure physical and logical independence of data.
- The rules address requirements like how null values are handled, if views can be updated, independence from physical storage structure, and only accessing data via SQL. Following the rules helps ensure data integrity and reliability within an RDBMS
The document discusses database normalization, which is the process of organizing data in a database to reduce redundancy and dependency. It explains the different normal forms including 1NF, 2NF, 3NF, BCNF, 4NF and 5NF. Normalization is achieved by removing anomalies like insertion, deletion and update anomalies through decomposing tables and defining relationships between them.
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.
The document discusses the evolution of client-server architectures from centralized systems to modern multi-tier architectures. Early centralized systems had all components on a single mainframe computer, while file server architectures moved application logic to clients but kept data on a central file server. Client-server systems partitioned applications into separate client and server components communicating over a network. Modern architectures further separate concerns into multiple logical tiers or services for improved performance, manageability, and reuse across applications.
What is Normalization in Database Management System (DBMS) ?
What is the history of the system of normalization?
Types of Normalizations,
and why this is needed all details in the presentation.
The document provides an introduction to database management systems and related concepts. It defines key terms like data, information, database, and record. It describes the differences between manual and computerized data processing. It then discusses traditional file-based data storage approaches and their limitations. The document introduces database management systems and their applications. It provides a brief history of DBMS and discusses the data processing cycle and the roles of different database users. Finally, it covers various database models including hierarchical, network, relational, object-oriented, and object-relational models.
The document defines and provides examples of different types of keys used in database systems, including super keys, candidate keys, primary keys, alternate keys, composite keys, foreign keys, and unique keys. A super key can identify a tuple but contains extra attributes, while a candidate key is a minimal super key. The primary key is chosen by the administrator and must be unique. Alternate keys are other candidate keys, and composite keys comprise multiple attributes. Foreign keys link tables using primary keys, and unique keys are like primary keys but allow null values.
The document discusses database normalization and Codd's rules for relational database management systems (RDBMS). It covers several key points:
- Database normalization aims to reduce anomalies like inconsistencies that can occur during database operations by decomposing tables and removing redundant or dependent data.
- Codd proposed 13 rules for a database to be considered a true RDBMS, including that the data be structured relationally in tables, support query languages, and ensure physical and logical independence of data.
- The rules address requirements like how null values are handled, if views can be updated, independence from physical storage structure, and only accessing data via SQL. Following the rules helps ensure data integrity and reliability within an RDBMS
The document discusses database normalization, which is the process of organizing data in a database to reduce redundancy and dependency. It explains the different normal forms including 1NF, 2NF, 3NF, BCNF, 4NF and 5NF. Normalization is achieved by removing anomalies like insertion, deletion and update anomalies through decomposing tables and defining relationships between them.
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.
The document discusses the evolution of client-server architectures from centralized systems to modern multi-tier architectures. Early centralized systems had all components on a single mainframe computer, while file server architectures moved application logic to clients but kept data on a central file server. Client-server systems partitioned applications into separate client and server components communicating over a network. Modern architectures further separate concerns into multiple logical tiers or services for improved performance, manageability, and reuse across applications.
What is Normalization in Database Management System (DBMS) ?
What is the history of the system of normalization?
Types of Normalizations,
and why this is needed all details in the presentation.
The document provides an introduction to database management systems and related concepts. It defines key terms like data, information, database, and record. It describes the differences between manual and computerized data processing. It then discusses traditional file-based data storage approaches and their limitations. The document introduces database management systems and their applications. It provides a brief history of DBMS and discusses the data processing cycle and the roles of different database users. Finally, it covers various database models including hierarchical, network, relational, object-oriented, and object-relational models.
The document defines and provides examples of different types of keys used in database systems, including super keys, candidate keys, primary keys, alternate keys, composite keys, foreign keys, and unique keys. A super key can identify a tuple but contains extra attributes, while a candidate key is a minimal super key. The primary key is chosen by the administrator and must be unique. Alternate keys are other candidate keys, and composite keys comprise multiple attributes. Foreign keys link tables using primary keys, and unique keys are like primary keys but allow null values.
This document appears to be a student project report submitted to a secondary school. It includes an acknowledgements section thanking guidance received. It also includes a certificate section signed by a computer science faculty member. The bulk of the document is an index listing 25 C++ programs with brief descriptions and signatures. The programs cover topics like arrays, sorting, functions, classes, pointers and file handling. In total, this report submitted a series of C++ programs to fulfill a school programming assignment.
The document discusses database normalization. It defines normalization as organizing data to eliminate redundancy and ensure data dependencies. The document outlines several normal forms including 1NF, 2NF, 3NF and BCNF. It provides examples to demonstrate transforming a database from an unnormalized form to higher normal forms through removing anomalies and redundancies.
1) A friend function allows access to private and protected members of a class. It is declared inside the class using the keyword "friend".
2) A friend function is not a member function - it is defined outside of the class and does not have access to non-static members using the class object. However, it can access private and protected members of the class.
3) In the example, the Temperature class declares the temp function as a friend. This allows temp to directly access and modify the private celsius member, something that regular non-member functions cannot do. The friend declaration gives temp special access privileges.
Integrity constraints are rules used to maintain data quality and ensure accuracy in a relational database. The main types of integrity constraints are domain constraints, which define valid value sets for attributes; NOT NULL constraints, which enforce non-null values; UNIQUE constraints, which require unique values; and CHECK constraints, which specify value ranges. Referential integrity links data between tables through foreign keys, preventing orphaned records. Integrity constraints are enforced by the database to guard against accidental data damage.
The document discusses key concepts in database systems including data, information, databases, database management systems, and data redundancy, inconsistency, sharing, security, and integrity. It also covers levels of database implementation including the internal, conceptual, and external levels. Relational data models and basic terminology are defined. Relational algebra operators like selection, projection, Cartesian product, union, set difference, and set intersection are explained. Finally, some disadvantages of database systems are noted.
Integrity constraints are rules that help maintain data quality and consistency in a database. The main types of integrity constraints are:
1. Domain constraints specify valid values and data types for attributes to restrict what data can be entered.
2. Entity constraints require that each row have a unique identifier and prevent null values in primary keys.
3. Referential integrity constraints maintain relationships between tables by preventing actions that would invalidate links between foreign and primary keys.
4. Cascade rules extend referential integrity by automatically propagating updates or deletes from a primary table to its related tables.
The document discusses 2-tier and 3-tier architecture, with the 2-tier having direct communication between the client and database while the 3-tier separates the user interface, business logic, and data layers; it provides details on each layer including advantages like improved performance, scalability, and security for the 3-tier architecture over the 2-tier. The presentation was created by trainees of Baabtra as part of a mentoring program to explain different architecture types.
Data Abstraction and Independance (1).pptxnehasahuji
This document discusses data abstraction and data independence in database systems. It describes three levels of data abstraction: physical level, logical level, and view level. The physical level concerns how data is actually stored, the logical level comprises information stored in tables and relationships between entities, and the view level allows users to view data in rows and columns. Data independence means the ability to modify schemas without affecting other levels - physical level data independence allows changing the physical storage without impacting logical or view levels, while logical level data independence modifies the conceptual view without affecting external applications or user views.
This document discusses database anomalies that can occur when data is stored in a single, unnormalized table. It provides examples of insert, delete, and update anomalies and how normalization helps address these issues. The document also demonstrates how to model relationships between entities as relations and add foreign keys to represent those relationships without anomalies.
PL/SQL is a combination of SQL along with the procedural features of programming languages.
It provides specific syntax for this purpose and supports exactly the same datatypes as SQL.
An Entity–relationship model (ER model) describes the structure of a database with the help of a diagram, which is known as Entity Relationship Diagram (ER Diagram). An ER model is a design or blueprint of a database that can later be implemented as a database. The main components of E-R model are: entity set and relationship set
This document discusses classes and objects in C++. It defines a class as a user-defined data type that implements an abstract object by combining data members and member functions. Data members are called data fields and member functions are called methods. An abstract data type separates logical properties from implementation details and supports data abstraction, encapsulation, and hiding. Common examples of abstract data types include Boolean, integer, array, stack, queue, and tree structures. The document goes on to describe class definitions, access specifiers, static members, and how to define and access class members and methods.
Abstract Base Class and Polymorphism in C++Liju Thomas
Connect with me through Facebook and twitter for more details:http://www.facebook.com/lijuthomas24, http://www.twitter.com/lijuthomas24
This ppt explains the concept of abstract base class and Polymorphism in C++
This document discusses the object oriented data model (OODM). It defines the OODM and describes how it accommodates relationships like aggregation, generalization, and particularization. The OODM provides four types of data operations: defining schemas, creating databases, retrieving objects, and expanding objects. Key features of the OODM include object identity, abstraction, encapsulation, data hiding, inheritance, and classes. The document concludes that a prototype of the OODM has been implemented to model application domains and that menus can be created, accessed, and updated like data from the database schema in the OODM.
The document provides an overview of entity relationship diagrams (ERDs) including their basic components, different notations, and how to implement various relationship types in a relational database. ERDs depict entities, attributes, and relationships in a conceptual database design. Key points covered include the three main notations of ERDs, solving multi-valued attributes and many-to-many relationships, and how to implement one-to-one, one-to-many, and many-to-many relationships through primary and foreign key constraints.
The document discusses extended relational algebra operations including generalized projection, outer join, and aggregate functions. Generalized projection allows arithmetic functions in the projection list. Outer join computes a join and adds unmatched tuples using null values. Aggregate functions return a single value from a collection and can be used in aggregate operations to group and summarize data. Modification operations like deletion, insertion, and updating are also expressed using relational algebra.
This document discusses data members and member functions in C++ classes. It defines data members as variables declared inside a class that can be of any type. Member functions are functions declared inside a class that can access and perform operations on the class's data members. The document outlines how data members and member functions can be defined with public, private, or protected visibility and how they can be accessed from within and outside the class. It also provides syntax examples for defining member functions both inside and outside the class definition.
This document discusses database normalization. It defines normalization as the process of organizing data in a database to minimize redundancy and dependency. The goals are to eliminate storing the same data in multiple tables and to only store related data together. The document describes the first three normal forms - first normal form eliminates replicated data and creates separate tables, second normal form creates separate tables for values that apply to multiple records, and third normal form eliminates fields that do not depend on the primary key. While third normal form addresses some issues, further normalization is needed to fully remove redundancy from databases.
The document provides an overview of the relational model and relational algebra used in relational databases. It defines key concepts like relations, tuples, attributes, domains, schemas, instances, keys, and normal forms. It also explains the six basic relational algebra operations - select, project, union, difference, cartesian product, and rename - and how they can be composed to form complex queries. Examples of relations and queries involving operations like selection, projection, joins are provided to illustrate relational algebra.
The document discusses different types of data models used in database management systems including conceptual, logical, and physical data models. It describes how conceptual data models define what data the system contains, logical data models define how the system should be implemented, and physical data models describe how the system will be implemented using a specific DBMS. The document also discusses other database concepts like the entity-relationship model, relational model, keys, integrity constraints, and more.
Here are the key entities and relationships based on the information provided:
Entities:
- Department
- Employee
- Supervisor
- Project
Relationships:
- Department has one supervisor (1:1)
- Department has many employees (1:M)
- Employee works in one or more departments (M:N)
- Project has many employees assigned (1:M)
- Employee works on one or more projects (M:N)
The important attributes that uniquely identify each entity are also specified, such as employee number, department code, project number. This provides the foundation for modeling the database schema to represent these real world entities and relationships.
This document appears to be a student project report submitted to a secondary school. It includes an acknowledgements section thanking guidance received. It also includes a certificate section signed by a computer science faculty member. The bulk of the document is an index listing 25 C++ programs with brief descriptions and signatures. The programs cover topics like arrays, sorting, functions, classes, pointers and file handling. In total, this report submitted a series of C++ programs to fulfill a school programming assignment.
The document discusses database normalization. It defines normalization as organizing data to eliminate redundancy and ensure data dependencies. The document outlines several normal forms including 1NF, 2NF, 3NF and BCNF. It provides examples to demonstrate transforming a database from an unnormalized form to higher normal forms through removing anomalies and redundancies.
1) A friend function allows access to private and protected members of a class. It is declared inside the class using the keyword "friend".
2) A friend function is not a member function - it is defined outside of the class and does not have access to non-static members using the class object. However, it can access private and protected members of the class.
3) In the example, the Temperature class declares the temp function as a friend. This allows temp to directly access and modify the private celsius member, something that regular non-member functions cannot do. The friend declaration gives temp special access privileges.
Integrity constraints are rules used to maintain data quality and ensure accuracy in a relational database. The main types of integrity constraints are domain constraints, which define valid value sets for attributes; NOT NULL constraints, which enforce non-null values; UNIQUE constraints, which require unique values; and CHECK constraints, which specify value ranges. Referential integrity links data between tables through foreign keys, preventing orphaned records. Integrity constraints are enforced by the database to guard against accidental data damage.
The document discusses key concepts in database systems including data, information, databases, database management systems, and data redundancy, inconsistency, sharing, security, and integrity. It also covers levels of database implementation including the internal, conceptual, and external levels. Relational data models and basic terminology are defined. Relational algebra operators like selection, projection, Cartesian product, union, set difference, and set intersection are explained. Finally, some disadvantages of database systems are noted.
Integrity constraints are rules that help maintain data quality and consistency in a database. The main types of integrity constraints are:
1. Domain constraints specify valid values and data types for attributes to restrict what data can be entered.
2. Entity constraints require that each row have a unique identifier and prevent null values in primary keys.
3. Referential integrity constraints maintain relationships between tables by preventing actions that would invalidate links between foreign and primary keys.
4. Cascade rules extend referential integrity by automatically propagating updates or deletes from a primary table to its related tables.
The document discusses 2-tier and 3-tier architecture, with the 2-tier having direct communication between the client and database while the 3-tier separates the user interface, business logic, and data layers; it provides details on each layer including advantages like improved performance, scalability, and security for the 3-tier architecture over the 2-tier. The presentation was created by trainees of Baabtra as part of a mentoring program to explain different architecture types.
Data Abstraction and Independance (1).pptxnehasahuji
This document discusses data abstraction and data independence in database systems. It describes three levels of data abstraction: physical level, logical level, and view level. The physical level concerns how data is actually stored, the logical level comprises information stored in tables and relationships between entities, and the view level allows users to view data in rows and columns. Data independence means the ability to modify schemas without affecting other levels - physical level data independence allows changing the physical storage without impacting logical or view levels, while logical level data independence modifies the conceptual view without affecting external applications or user views.
This document discusses database anomalies that can occur when data is stored in a single, unnormalized table. It provides examples of insert, delete, and update anomalies and how normalization helps address these issues. The document also demonstrates how to model relationships between entities as relations and add foreign keys to represent those relationships without anomalies.
PL/SQL is a combination of SQL along with the procedural features of programming languages.
It provides specific syntax for this purpose and supports exactly the same datatypes as SQL.
An Entity–relationship model (ER model) describes the structure of a database with the help of a diagram, which is known as Entity Relationship Diagram (ER Diagram). An ER model is a design or blueprint of a database that can later be implemented as a database. The main components of E-R model are: entity set and relationship set
This document discusses classes and objects in C++. It defines a class as a user-defined data type that implements an abstract object by combining data members and member functions. Data members are called data fields and member functions are called methods. An abstract data type separates logical properties from implementation details and supports data abstraction, encapsulation, and hiding. Common examples of abstract data types include Boolean, integer, array, stack, queue, and tree structures. The document goes on to describe class definitions, access specifiers, static members, and how to define and access class members and methods.
Abstract Base Class and Polymorphism in C++Liju Thomas
Connect with me through Facebook and twitter for more details:http://www.facebook.com/lijuthomas24, http://www.twitter.com/lijuthomas24
This ppt explains the concept of abstract base class and Polymorphism in C++
This document discusses the object oriented data model (OODM). It defines the OODM and describes how it accommodates relationships like aggregation, generalization, and particularization. The OODM provides four types of data operations: defining schemas, creating databases, retrieving objects, and expanding objects. Key features of the OODM include object identity, abstraction, encapsulation, data hiding, inheritance, and classes. The document concludes that a prototype of the OODM has been implemented to model application domains and that menus can be created, accessed, and updated like data from the database schema in the OODM.
The document provides an overview of entity relationship diagrams (ERDs) including their basic components, different notations, and how to implement various relationship types in a relational database. ERDs depict entities, attributes, and relationships in a conceptual database design. Key points covered include the three main notations of ERDs, solving multi-valued attributes and many-to-many relationships, and how to implement one-to-one, one-to-many, and many-to-many relationships through primary and foreign key constraints.
The document discusses extended relational algebra operations including generalized projection, outer join, and aggregate functions. Generalized projection allows arithmetic functions in the projection list. Outer join computes a join and adds unmatched tuples using null values. Aggregate functions return a single value from a collection and can be used in aggregate operations to group and summarize data. Modification operations like deletion, insertion, and updating are also expressed using relational algebra.
This document discusses data members and member functions in C++ classes. It defines data members as variables declared inside a class that can be of any type. Member functions are functions declared inside a class that can access and perform operations on the class's data members. The document outlines how data members and member functions can be defined with public, private, or protected visibility and how they can be accessed from within and outside the class. It also provides syntax examples for defining member functions both inside and outside the class definition.
This document discusses database normalization. It defines normalization as the process of organizing data in a database to minimize redundancy and dependency. The goals are to eliminate storing the same data in multiple tables and to only store related data together. The document describes the first three normal forms - first normal form eliminates replicated data and creates separate tables, second normal form creates separate tables for values that apply to multiple records, and third normal form eliminates fields that do not depend on the primary key. While third normal form addresses some issues, further normalization is needed to fully remove redundancy from databases.
The document provides an overview of the relational model and relational algebra used in relational databases. It defines key concepts like relations, tuples, attributes, domains, schemas, instances, keys, and normal forms. It also explains the six basic relational algebra operations - select, project, union, difference, cartesian product, and rename - and how they can be composed to form complex queries. Examples of relations and queries involving operations like selection, projection, joins are provided to illustrate relational algebra.
The document discusses different types of data models used in database management systems including conceptual, logical, and physical data models. It describes how conceptual data models define what data the system contains, logical data models define how the system should be implemented, and physical data models describe how the system will be implemented using a specific DBMS. The document also discusses other database concepts like the entity-relationship model, relational model, keys, integrity constraints, and more.
Here are the key entities and relationships based on the information provided:
Entities:
- Department
- Employee
- Supervisor
- Project
Relationships:
- Department has one supervisor (1:1)
- Department has many employees (1:M)
- Employee works in one or more departments (M:N)
- Project has many employees assigned (1:M)
- Employee works on one or more projects (M:N)
The important attributes that uniquely identify each entity are also specified, such as employee number, department code, project number. This provides the foundation for modeling the database schema to represent these real world entities and relationships.
The document discusses different types of data models used in database management systems including conceptual, logical, and physical data models. It describes conceptual data models as defining what the system contains, logical data models as defining how the system should be implemented regardless of the DBMS, and physical data models as describing how the system will be implemented using a specific DBMS. The document also discusses entity-relationship models and diagrams, relational models, keys used in databases like primary keys and foreign keys, and integrity constraints to maintain data validity.
The document discusses different data models including hierarchical, network, relational, and object oriented models. It also provides details on entity-relationship (E-R) modeling. The E-R model defines entities and their attributes, and relationships between entities. Key concepts include entity sets, relationship sets, mapping cardinalities, participation constraints, keys, and designing E-R diagrams. An example E-R diagram for a university management system is presented to illustrate these concepts.
The document provides information on the key concepts of an entity-relationship (E-R) model, including:
1) Entities represent real-world objects like people, places, and things that are stored in a database. Attributes describe the properties of entities.
2) Relationships represent associations between entities. Relationships have properties like degree, cardinality, and existence.
3) Keys like primary keys and foreign keys uniquely identify entities and define relationships between entities.
4) Strong and weak entities differ in whether they have their own primary keys or rely on other entities.
5) E-R diagrams visually depict entities, attributes, relationships, keys and other concepts to model a database.
This document discusses relationships in database management systems. It begins by introducing relationships and how they are established through primary and foreign keys. It then describes different types of relationships: one-to-one, one-to-many, many-to-one, and many-to-many. For each relationship type, it provides examples and descriptions of how the relationships are implemented in tables. The document emphasizes that relationships are important for reducing data redundancy, organizing the database, and ensuring referential integrity. It concludes by reiterating the importance of properly defining relationships for effective database functioning.
The document discusses conceptual data modeling using the entity-relationship (ER) model. It begins by explaining how database designers interview users to understand data requirements and create a conceptual schema using a high-level ER model. This conceptual schema is then transformed into an implementation model using a commercial database system. The document also provides examples of an entity, attribute, relationship, and developing an ER diagram for a sample company database that tracks employees, departments, and projects.
DBMS stands for Database Management System. A DBMS allows for the storage and management of data in an organized manner. It uses tables to store data with rows and columns, where each row represents a record or tuple of data. Entities, attributes, keys, and relationships help define the structure and integrity of data within the database. The three schema architecture separates the physical storage, logical design, and external user views to provide data independence and abstraction between different levels.
The document discusses Relational Database Management Systems (RDBMS) and Entity-Relationship (ER) modeling. It describes the key components of an ER diagram including entities, attributes, relationships and relationship types. It provides examples of how to model real-world systems, such as modeling students and addresses in a school database. It also discusses entity keys like primary keys and foreign keys and how they are used to uniquely identify records and link tables in a relational database.
The document presents information on Entity Relationship (ER) modeling for database design. It discusses the key concepts of ER modeling including entities, attributes, relationships and cardinalities. It also explains how to create an Entity Relationship Diagram (ERD) using standard symbols and notations. Additional features like generalization, specialization and inheritance are covered which allow ERDs to represent hierarchical relationships between entities. The presentation aims to provide an overview of ER modeling and ERDs as an important technique for conceptual database design.
This document provides an overview of relational database concepts including the relational data model, ER diagrams, normalization, and database languages. It discusses how data is organized in tables with attributes, tuples, domains, and keys in the relational model. ER diagrams are used to conceptualize relationships between entities and attributes. Normalization is the process of structuring data to minimize redundancy through various normal forms up to 3NF. Common database languages are also summarized including DDL, DML, DCL, and TCL and their uses.
The document defines key concepts of an entity relationship (ER) model used for database design. It explains that an ER model uses entities, attributes, and relationships to conceptualize a database's structure and design. It provides examples of entity types like strong and weak entities, attribute types like primary keys and foreign keys, and relationship types like one-to-one, one-to-many, many-to-one, and many-to-many. The ER model develops a simple conceptual view of a database's data elements and how they relate to each other.
The document defines key concepts of an entity relationship (ER) model used for database design. It explains that an ER model uses entities, attributes, and relationships to conceptualize a database's structure and design. It provides examples of entity types like strong and weak entities, attribute types like primary keys and foreign keys, and relationship types like one-to-one, one-to-many, many-to-one, and many-to-many. The ER model develops a simple conceptual view of a database's data elements and how they relate to each other.
This document provides an overview of entity-relationship (ER) models, which allow specification of a database schema representing the logical structure of a database. It discusses key concepts including entity sets, relationship sets, attributes, and mapping constraints. Entity sets represent collections of real-world objects or concepts that share common properties. Relationship sets define associations between entity sets. Attributes provide additional information about entities. Mapping constraints specify cardinality ratios for relationships. The document also covers ER diagramming and the differences between weak and strong entities.
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.
The document presents an overview of entity-relationship (E-R) diagrams. It defines E-R diagrams as visual representations of entities and relationships within a system. The key components of E-R diagrams are described as entities, attributes, and relationships. Entities represent objects, attributes are properties of entities, and relationships show interactions between entities. The document also provides examples of different types of relationships, instructions for creating E-R diagrams, and applications of using E-R diagrams for database design and software engineering.
Download different material from slide sharefanta teferi
The document provides an overview of the relational data model concepts covered in Chapter 2, including:
- The relational model organizes data into tables of rows and columns called relations. A row is a tuple and a column is an attribute.
- Entities have attributes that describe their properties. Relationships associate entities and have a degree and cardinality.
- Relational integrity constraints include domain, entity, referential integrity. Key constraints like primary keys and foreign keys uniquely identify and relate tuples.
- Base relations are physically stored tables while views are virtual relations derived from queries on base relations. The schema defines a relation while the instance contains tuples of data.
The document discusses entity-relationship (ER) diagrams and database design. It defines key concepts in ER diagrams like entities, attributes, relationships and how they are represented. It explains how to start building an ER diagram by defining entities and relationships based on a narrative. Different types of relationships and how they are drawn are covered, along with cardinality, keys, and other symbols used in ER diagrams. The document provides an example of an ER diagram for a banking system and discusses how an ER diagram can be converted into a relational database with tables.
The importance of data models, Basic building blocks, Business rules, The evolution of data models, Degrees of data abstraction
Database design and Introduction to UML
DBMS-Keys , Attributes and Constraints.pptxsajinis5
keys uniquely identify records;Attributes represent data characteristics, classified as simple or composite, with associated data types. Constraints maintain data integrity
Software engineering is concerned with developing software using a systematic process and addressing factors like increasing demands and low expectations. It involves activities like specification, development, validation and evolution. Some key challenges are coping with diversity, reduced delivery times and developing trustworthy software. Different techniques are suitable depending on the type of system, and processes may incorporate elements of models like waterfall, incremental development and integration/configuration. Prototyping can help with requirements, design and testing.
The document provides an introduction to software engineering and discusses software, software engineering, the software development life cycle (SDLC), and SDLC models. It defines software and its components. It describes software engineering goals and challenges. It explains the SDLC phases including feasibility study, requirements analysis, design, development, testing, deployment, and maintenance. It discusses various SDLC models like waterfall, iterative, prototype, spiral, and agile models.
Software Engineering-Unit 2 "Requirement Engineering" by Adi.pdfProf. Dr. K. Adisesha
The document discusses requirement engineering and provides details on:
- Types of requirements including functional, non-functional, user, and system requirements
- The requirement engineering process including feasibility studies, elicitation, analysis, specification, validation, and management
- Software requirement specification (SRS) documents, their purpose, characteristics of a good SRS, and typical sections
- Functional and non-functional requirements in more depth
This document discusses system modeling. It defines system modeling as developing abstract models of a system from different perspectives. Common modeling techniques discussed include context models, interaction models, structural models, behavioral models, and model-driven engineering. Specific modeling languages covered are activity diagrams, use case diagrams, sequence diagrams, class diagrams, and state diagrams. The document provides examples and definitions for how to apply these modeling approaches and languages.
Architectural design establishes the framework for software development by examining requirements and designing a model that specifies system components, their inputs/outputs/functions, and interactions. It can be represented using structural, dynamic, process, functional, or framework models. The outputs are an architectural design document and various project plans. Architectural design decisions impact non-functional requirements and common decisions include architectural style and system decomposition.
The document discusses various types of software testing including unit testing, component testing, system testing, test-driven development, release testing, and user testing. It provides details on the goals and processes involved in each type of testing. Unit testing involves testing individual program units in isolation to check functionality. Component and system testing focus on interactions between units and components. Test-driven development interleaves writing tests before code. Release testing validates that software meets requirements before release. User testing involves customers providing input on a system under test.
This document discusses computer communication and networks. It defines data communication and its key characteristics of delivery, accuracy, timeliness and jitter. It describes the core components of a data communication system including the message, sender, receiver, transmission medium and protocols. It then discusses different types of computer networks including LANs, WANs, PANs and MANs. The key aspects covered are their definitions, examples, advantages and disadvantages.
Data communication involves the exchange of data between two devices via transmission media such as cables. It consists of five main components: a message, sender, receiver, transmission medium, and protocol. Data can be transmitted in three modes - simplex, half-duplex, and full-duplex. Transmission media can be guided (wired) such as twisted pair or coaxial cables, or unguided (wireless) such as radio waves. Networks are sets of connected devices that can be arranged in various topologies like bus, star, ring, or mesh. Switching techniques such as circuit, message, and packet switching determine how data is routed through a network.
The document discusses the data link layer. It covers the following key points:
- The data link layer has two sublayers: the logical link control (LLC) sublayer and the medium access control (MAC) sublayer.
- The LLC sublayer controls flow and performs error checking, while the MAC sublayer handles frame encapsulation and network addressing.
- The data link layer is responsible for framing, addressing, error control, flow control, and multi-access functionality. It takes packets and converts them to frames for transmission on the physical layer.
- Error detection techniques used include parity checks and cyclic redundancy checks to validate frames are transmitted accurately. Error correction can be done through retransmission
The document provides an overview of the network layer. It discusses key topics like the functions of the network layer such as logical addressing, routing, and internetworking. It describes different routing algorithms including distance vector, link state, and hierarchical routing. It also covers congestion control mechanisms like leaky bucket algorithm, token bucket algorithm, and admission control that are used to control congestion in the network layer.
The document discusses the transport and application layers of the OSI model. It begins by describing the transport layer, including its responsibilities of process-to-process delivery, end-to-end connections, multiplexing, congestion control, data integrity, error correction, and flow control. It then discusses the transport layer protocols TCP and UDP, comparing their key differences such as connection-oriented vs. connectionless and reliability. The document next covers application layer services and protocols, including DNS, HTTP, FTP, and email. It concludes by describing models like client-server and peer-to-peer that are used in application layer communication.
This document provides an introduction and overview of computer hardware components. It discusses input devices like keyboards, mice, scanners, and digital cameras. It also covers output devices such as monitors, printers, speakers. It describes different types of computers based on size and performance, such as microcomputers, minicomputers, and mainframes. The document then discusses computer memory, including primary memory technologies like RAM and ROM, as well as secondary magnetic storage.
This document provides an overview and introduction to the R programming language. It covers the history and development of R, which originated from the S language at Bell Labs in the 1970s. The document then outlines some key concepts in R including data structures, subsetting, control structures, functions, and debugging. It also discusses the design of the R system including its core functionality in base R and extensive library of additional packages.
The document discusses various government scholarship schemes in India and Karnataka for students. It outlines national schemes administered by ministries like Human Resource Development, Social Justice and Empowerment, Tribal Affairs and Minority Affairs. It also describes state-level schemes in Karnataka for SC/ST/OBC and minority students. Eligibility criteria include family income limits and minimum academic performance. The application process involves applying online through the National Scholarship Portal and State Scholarship Portal.
The document discusses various topics related to process management in operating systems, including:
1) A process is a program in execution that can be in different states like ready, running, waiting, or terminated. The OS uses a process control block to manage information for each process.
2) Processes communicate and synchronize access to shared resources using techniques like message passing and shared memory.
3) CPU scheduling algorithms like first-come first-served, shortest job next, priority, and round robin are used to allocate CPU time between ready processes.
This document provides an introduction to operating systems presented by Prof. K. Adisesha. It discusses key concepts of operating systems including definitions, functions, types, and properties. Specifically, it defines an operating system as an interface between the user and computer hardware. It describes functions such as processor management, memory management, and file management. It outlines different types of operating systems including batch, time-sharing, distributed, and real-time systems. Finally, it discusses properties like batch processing, multitasking, and distributed environments.
An operating system is an interface between a computer user and the computer hardware. The document discusses the key functions of operating systems including memory management, processor management, device management, file management, security, and more. It provides examples of popular operating systems like Linux, Windows, and describes different types of operating systems such as batch, time-sharing, distributed, network, and real-time operating systems.
This document provides an introduction to data structures using C. It discusses types of data structures like arrays, stacks, queues and linked lists. It explains that data structures allow for efficient organization and storage of data in memory based on relationships between elements. The document also covers topics like asymptotic analysis, best/worst/average case time complexities, big-O, omega and theta notations for analyzing algorithms. It provides characteristics of algorithms and data structures and examples of common data structure operations.
The document discusses object-oriented programming concepts in Java including classes, objects, inheritance, polymorphism, and more. It defines classes as templates for creating multiple object instances that share common properties. Objects are initialized through reference variables, methods, or constructors. The document also covers static methods, the this keyword, final keyword, arrays, strings, and other core OOP concepts in Java.
This document discusses Java graphics and input/output. It introduces the Graphics class in Java AWT which is used to draw on components. It describes various Graphics methods like drawString, drawRect. It also discusses AWT event handling and different event classes. Finally, it covers Java I/O streams like InputStream, OutputStream and file streams like FileInputStream and FileOutputStream along with methods to read and write from files.
বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
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তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
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How to Add Chatter in the odoo 17 ERP ModuleCeline George
In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
How to Setup Warehouse & Location in Odoo 17 InventoryCeline George
In this slide, we'll explore how to set up warehouses and locations in Odoo 17 Inventory. This will help us manage our stock effectively, track inventory levels, and streamline warehouse operations.
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LAND USE LAND COVER AND NDVI OF MIRZAPUR DISTRICT, UPRAHUL
This Dissertation explores the particular circumstances of Mirzapur, a region located in the
core of India. Mirzapur, with its varied terrains and abundant biodiversity, offers an optimal
environment for investigating the changes in vegetation cover dynamics. Our study utilizes
advanced technologies such as GIS (Geographic Information Systems) and Remote sensing to
analyze the transformations that have taken place over the course of a decade.
The complex relationship between human activities and the environment has been the focus
of extensive research and worry. As the global community grapples with swift urbanization,
population expansion, and economic progress, the effects on natural ecosystems are becoming
more evident. A crucial element of this impact is the alteration of vegetation cover, which plays a
significant role in maintaining the ecological equilibrium of our planet.Land serves as the foundation for all human activities and provides the necessary materials for
these activities. As the most crucial natural resource, its utilization by humans results in different
'Land uses,' which are determined by both human activities and the physical characteristics of the
land.
The utilization of land is impacted by human needs and environmental factors. In countries
like India, rapid population growth and the emphasis on extensive resource exploitation can lead
to significant land degradation, adversely affecting the region's land cover.
Therefore, human intervention has significantly influenced land use patterns over many
centuries, evolving its structure over time and space. In the present era, these changes have
accelerated due to factors such as agriculture and urbanization. Information regarding land use and
cover is essential for various planning and management tasks related to the Earth's surface,
providing crucial environmental data for scientific, resource management, policy purposes, and
diverse human activities.
Accurate understanding of land use and cover is imperative for the development planning
of any area. Consequently, a wide range of professionals, including earth system scientists, land
and water managers, and urban planners, are interested in obtaining data on land use and cover
changes, conversion trends, and other related patterns. The spatial dimensions of land use and
cover support policymakers and scientists in making well-informed decisions, as alterations in
these patterns indicate shifts in economic and social conditions. Monitoring such changes with the
help of Advanced technologies like Remote Sensing and Geographic Information Systems is
crucial for coordinated efforts across different administrative levels. Advanced technologies like
Remote Sensing and Geographic Information Systems
9
Changes in vegetation cover refer to variations in the distribution, composition, and overall
structure of plant communities across different temporal and spatial scales. These changes can
occur natural.
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
Certified as an ISO/IEC 27001: Information Security Management Systems (ISMS) Lead Implementer, Data Protection Officer, and Cyber Risks Analyst, Denis brings a heightened focus on data security, privacy, and cyber resilience to every endeavor.
His expertise extends across a diverse spectrum of reporting, database, and web development applications, underpinned by an exceptional grasp of data storage and virtualization technologies. His proficiency in application testing, database administration, and data cleansing ensures seamless execution of complex projects.
What sets Denis apart is his comprehensive understanding of Business and Systems Analysis technologies, honed through involvement in all phases of the Software Development Lifecycle (SDLC). From meticulous requirements gathering to precise analysis, innovative design, rigorous development, thorough testing, and successful implementation, he has consistently delivered exceptional results.
Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment.
Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
3. Introduction
Prof. K. Adisesha
3
ER model:
ER model stands for an Entity-Relationship model. It is a high-level data model.
➢ This model is used to define the data elements and relationship for a specified system.
➢ It develops a conceptual design for the database. It also develops a very simple and
easy to design view of data.
➢ In ER modeling, the database structure is portrayed as a diagram called an entity-
relationship diagram.
➢Example, Suppose we design a school database. In
this database, the student will be an entity with
attributes like address, name, id, age, etc.
4. E-R diagram
Prof. K. Adisesha
4
Components of E-R model:
ER-Diagram is a visual representation of data that describes how data is related to each
other.
➢ Entity
➢ Attribute
➢ Relationship
5. E-R diagram
Prof. K. Adisesha
5
Components of E-R model:
ER-Diagram is a visual representation of data that describes how data is related to each
other.
Entity:
✓ An Entity can be any object, place, person or class.
Attribute:
✓ An Attribute describes a property or characteristic of an entity.
✓ Example: Roll_No, Name and Birth date can be attributes of a student
Relationship:
✓ A relationship type is a meaningful association between entity types.
✓ Relationship types are represented on the E-R diagram by a series of lines.
6. E-R diagram
Prof. K. Adisesha
6
Different notations of E-R diagram:
ER-Diagram is a visual representation of data that describes how data is related to each
other.
➢ Different notations of E-R diagram:
❖ Entity: An entity is represented using rectangles.
❖ Attribute: Attributes are represented by means of eclipses.
❖ Relationship: Relationship is represented using diamonds shaped box.
7. E-R diagram
Prof. K. Adisesha
7
Different notations of E-R diagram:
Entity: An entity may be any object, class, person or place. In the ER diagram, an entity
can be represented as rectangles.
➢ Consider an organization as an example- manager, product, employee, department etc.
can be taken as an entity.
Weak Entity: An entity that depends on another entity called a weak entity. The weak
entity doesn't contain any key attribute of its own.
➢ The weak entity is represented by a double rectangle.
8. E-R diagram
Prof. K. Adisesha
8
Different notations of E-R diagram:
Attribute: The attribute is used to describe the property of an entity. Eclipse is used to
represent an attribute.
➢ For example, id, age, contact number, name, etc. can be attributes of a student.
➢ Different types of Attributes are:
❖ Key Attribute
❖ Composite Attribute
❖ Multivalued Attribute
❖ Derived Attribute
9. E-R diagram
Prof. K. Adisesha
9
Different notations of E-R diagram:
Key Attribute: The key attribute is used to represent the main characteristics of an entity. It
represents a primary key. The key attribute is represented by an ellipse with the text
underlined.
Composite Attribute: An attribute that composed of many other attributes is known as a
composite attribute. The composite attribute is represented by an ellipse, and those ellipses
are connected with an ellipse.
10. E-R diagram
Prof. K. Adisesha
10
Different notations of E-R diagram:
Multivalued Attribute: An attribute can have more than one value. These attributes are
known as a multivalued attribute. The double oval is used to represent multivalued
attribute.
➢ For example, a student can have more than one phone number.
Derived Attribute: An attribute that can be derived from other attribute is known as a
derived attribute. It can be represented by a dashed ellipse.
➢ For example, A person's age changes over time
and can be derived from another attribute like
Date of birth.
11. E-R diagram
Prof. K. Adisesha
11
Relationship:
A Relationship describes relations between entities. Relationship is represented using
diamonds shaped box.
➢ There are three types of relationship that exist between entities:
❖ Binary Relationship
❖ Recursive Relationship
❖ Ternary Relationship
12. E-R diagram
Prof. K. Adisesha
12
Binary Relationship:
It means relation between two entities.
➢ This is further divided into three types.
❖ One to One
❖ One to Many
❖ Many to Many
➢ One to One:
✓ This type of relationship is rarely seen in real world.
✓ The above example describes that one student can enroll only for one course and a
course will have only one Student. This is not what you will usually see in relationship.
13. E-R diagram
Prof. K. Adisesha
13
Binary Relationship:
➢ One to Many:
✓ It reflects business rule that one entity is associated with many number of same
entity.
✓ For example, Student enrolls for only one Course but a Course can have many
Students.
➢ Many to Many:
✓ It reflects business rule that many entity are associated with many number of same
entity.
✓ The above diagram represents that many students can enroll for more than one
course.
14. E-R diagram
Prof. K. Adisesha
14
Different notations of E-R diagram:
Database can be represented using the notations. In ER diagram, many notations are
used to express the cardinality.
➢ These notations are as follows:
15. Relational Keys
Prof. K. Adisesha
15
Keys used in database:
Keys play an important role in the relational database. It is used to uniquely identify any
record or row of data from the table.
➢ It is also used to establish and identify relationships between tables.
➢ Types of keys:
16. Relational Keys
Prof. K. Adisesha
16
Keys used in database:
➢ Primary key:
✓ It is a field in a table which uniquely identifies each row/record in a database table.
Primary keys must contain unique values.
✓ A primary key column cannot have NULL values.
✓ Ex: In the EMPLOYEE table, ID can be the primary key since it is unique for each
employee.
17. Relational Keys
Prof. K. Adisesha
17
Keys used in database:
➢ Candidate Key:
✓ When more than one or group of attributes serve as a unique identifier, they are
each called as candidate key.
✓ In the EMPLOYEE table, id is best suited for the primary key. The rest of the
attributes, like SSN, Passport_Number, License_Number, etc., are considered a
candidate key.
18. Relational Keys
Prof. K. Adisesha
18
Keys used in database:
➢ Super Key:
✓ Super key is an attribute set that can uniquely identify a tuple. A super key is a
superset of a candidate key.
✓ In the EMPLOYEE table, for(EMPLOEE_ID, EMPLOYEE_NAME), the name of
two employees can be the same, but their EMPLYEE_ID can't be the same. Hence,
this combination can also be a key.
19. Relational Keys
Prof. K. Adisesha
19
Keys used in database:
➢ Alternate Key:
✓ The alternate key of any table are those candidate keys, which are not currently
selected as the primary key. This is also known as secondary key.
✓ example, employee relation has two attributes, Employee_Id and PAN_No, that act
as candidate keys. In this relation, Employee_Id is chosen as the primary key, so the
other candidate key, PAN_No, acts as the Alternate key.
20. Relational Keys
Prof. K. Adisesha
20
Keys used in database:
➢ Foreign key:
✓ A key used to link two tables together is called a foreign key, also called as
referencing key.
✓ Foreign key is a field that matches the primary key column of another table.
✓ In the EMPLOYEE table, Department_Id is the foreign key, and both the tables are
related.
21. Relational Keys
Prof. K. Adisesha
21
Keys used in database:
➢ Composite key:
✓ Whenever a primary key consists of more than one attribute, it is known as a
composite key. This key is also known as Concatenated Key.
✓ in employee table, an employee may be assigned multiple roles, and an employee
may work on multiple projects simultaneously. So the primary key will be
composed of all three attributes, namely Emp_ID, Emp_role, and Proj_ID in
combination.
22. Integrity Constraints
Prof. K. Adisesha
22
Integrity Constraints:
Integrity constraints are pre-defined set of rules that are applied on the table
fields(columns) or relations to ensure that the overall validity, integrity, and consistency
of the data present in the database table is maintained.
➢ It is used to maintain the quality of information.
➢ It ensures that the data insertion, updating, and other processes have to be performed in
such a way that data integrity is not affected.
➢ Types of integrity constraints in relational data model:
❖ Domain Constraint
❖ Entity Constraint
❖ Referential Integrity Constraint
❖ Key Constraint
23. Integrity Constraints
Prof. K. Adisesha
23
Integrity Constraints Types:
Domain integrity constraint :
➢ Domain constraints can be defined as the definition of a valid set of values for an
attribute.
➢ The data type of domain includes string, character, integer, time, date, currency, etc.
The value of the attribute must be available in the corresponding domain.
ID NAME SEMESTER AGE
10001 PRAJWAL 2 19
10002 SUNNY 1 18
10003 SHAILU 3 A
24. Integrity Constraints
Prof. K. Adisesha
24
Integrity Constraints Types:
Entity integrity constraints:
➢ The entity integrity constraint states that primary key value can't be null.
➢ This is because the primary key value is used to identify individual rows in relation and
if the primary key has a null value, then we can't identify those rows.
➢ A table can contain a null value other than the primary key field.
ID NAME SEMESTER AGE
10001 PRAJWAL 2 19
10002 SUNNY 1 18
SHAILU 3 20
25. Integrity Constraints
Prof. K. Adisesha
25
Integrity Constraints Types:
Referential Integrity Constraints: A referential integrity constraint is specified between
two tables.
➢ In the Referential integrity constraints, if a foreign key in Table 1 refers to the Primary
Key of Table 2, then every value of the Foreign Key in Table 1 must be null or be
available in Table 2.
26. Integrity Constraints
Prof. K. Adisesha
26
Integrity Constraints Types:
Key constraints: Keys are the entity set that is used to identify an entity within its entity
set uniquely.
➢ An entity set can have multiple keys, but out of which one key will be the primary key.
A primary key can contain a unique and null value in the relational table..
ID NAME SEMESTER AGE
10001 PRAJWAL 2 19
10002 SUNNY 1 18
10002 SHAILU 3 20
27. Generalization
Prof. K. Adisesha
27
Generalization:
Generalization is a bottom-up approach in which two lower level entities combine to
form a higher level entity.
➢ In generalization, a number of entities are brought together into one generalized entity
based on their similar characteristics.
➢ For example, Student and Parent details can all be generalized as a group ‘Person’ as
Personal details.
28. Specialization
Prof. K. Adisesha
28
Specialization:
Specialization is a Top-down approach in which one higher level entity can be broken
down into two lower level entities.
➢ Specialization is the opposite of generalization.
➢ In specialization, a group of entities is divided into sub-groups based on their
characteristics.
➢ Take a group ‘Person’ for example. A person has name, date of birth, gender, etc.
Similarly, in a school database, persons can be specialized as teacher, student, or a staff,
based on what role they play in school as entities.
29. Aggregation
Prof. K. Adisesha
29
Aggregation:
In aggregation, the relation between two entities is treated as a single entity. In
aggregation, relationship with its corresponding entities is aggregated into a higher level
entity.
➢ Center entity offers the Course entity act as a single entity in the relationship which is in
a relationship with another entity visitor. If a visitor visits a coaching center then he will
enquiry about both Course and Center.
30. Aggregation
Prof. K. Adisesha
30
Aggregate function:
Aggregate functions in DBMS take multiple rows from the table and return a value
according to the query.
➢ Common aggregate functions include:
❖ Average (i.e., arithmetic mean)
❖ Count
❖ Maximum
❖ Median
❖ Minimum
❖ Mode
❖ Range
❖ Sum
31. ER diagram
Prof. K. Adisesha
31
Reduction of ER diagram to Table:
The database can be represented using the notations, and these notations can be reduced
to a collection of tables.
32. ER diagram
Prof. K. Adisesha
32
Reduction of ER diagram to Table:
Table structure for the given ER diagram is as below:
33. ER diagram
Prof. K. Adisesha
33
Reduction of ER diagram to Table:
Steps to convert Table structure from the given ER diagram is as below:
➢ Entity type becomes a table.
❖ In the given ER diagram, LECTURE, STUDENT, SUBJECT and COURSE forms
individual tables.
➢ All single-valued attribute becomes a column for the table.
❖ In the STUDENT entity, STUDENT_NAME and STUDENT_ID form the column of
STUDENT table. Similarly, COURSE_NAME and COURSE_ID form the column of
COURSE table and so on.
➢ A key attribute of the entity type represented by the primary key.
❖ In the given ER diagram, COURSE_ID, STUDENT_ID, SUBJECT_ID, and LECTURE_ID
are the key attribute of the entity.
34. ER diagram
Prof. K. Adisesha
34
Reduction of ER diagram to Table:
Steps to convert Table structure from the given ER diagram is as below:
➢ The multivalued attribute is represented by a separate table.
❖ In the student table, a hobby is a multivalued attribute. So it is not possible to represent
multiple values in a single column of STUDENT table. Hence we create a table
STUD_HOBBY with column name STUDENT_ID and HOBBY. Using both the column, we
create a composite key.
➢ Composite attribute represented by components.
❖ In the given ER diagram, student address is a composite attribute. It contains CITY, PIN,
DOOR#, STREET, and STATE. In the STUDENT table, these attributes can merge as an
individual column.
➢ Derived attributes are not considered in the table.
❖ In the STUDENT table, Age is the derived attribute. It can be calculated at any point of time
35. Relation Algebra
Prof. K. Adisesha
35
Relation Algebra:
Relational algebra is a procedural query language. It gives a step by step process to
obtain the result of the query. It uses operators to perform queries.
➢ Types of Relational operation:
36. Relation Algebra
Prof. K. Adisesha
36
Relation Algebra:
Relational algebra is a procedural query language that consists of a set of operations
that take one or more relations as input and result into a new relation as an output.
➢ The relational algebraic operations can be divided into:
❖ Basic set-oriented operations:
✓ Union, Set different, Cartesian product
❖ Relational-oriented operations:
✓ Selection, Projection, Division, Joins
37. Relation Algebra
Prof. K. Adisesha
37
Joins:
Joins in Database Management System are used in relational algebra and SQL to
join/combine more than one table to get some specific results out of those tables.
➢ A Join operation combines related tuples from different relations, if and only if a given
join condition is satisfied. It is denoted by ⋈.
➢ Different types of the JOINs in SQL:
❖ (INNER) JOIN
❖ LEFT (OUTER) JOIN
❖ RIGHT (OUTER) JOIN
❖ FULL (OUTER) JOIN
38. Relation Algebra
Prof. K. Adisesha
38
Joins:
Joins in Database Management System are used in relational algebra and SQL to
join/combine more than one table to get some specific results out of those tables.
➢ Different types of the JOINs in SQL:
❖ (INNER) JOIN: Returns records that have matching values in both tables
❖ LEFT (OUTER) JOIN: Returns all records from the left table, and the matched records from
the right table
❖ RIGHT (OUTER) JOIN: Returns all records from the right table, and the matched records
from the left table
❖ FULL (OUTER) JOIN: Returns all records when there is a match in either left or right table
39. Database Model
Prof. K. Adisesha
39
Normalization:
Normalization is a step by step process of removing the different kinds of redundancy
and anomaly one step at a time from the database.
➢ E.F Codd developed for the relation data model in 1970.
➢ Normalization rules are divided into following normal form:
40. Database Model
Prof. K. Adisesha
40
Normalization:
Normalization is a step by step process of removing the different kinds of redundancy
and anomaly one step at a time from the database.
41. Questions
Important Questions:
➢ Define the following database terms:
a. Data Model b. Tuple c. Domain d. Primary key e. Foreign key
➢ Write the difference between manual and electronic data processing.
➢ Explain any five applications of database.
➢ Briefly explain the data processing cycle.
➢ Write the difference between Hierarchical data model and network data model.
➢ What is normalization? Explain second normal form with an example.
➢ What is database model? Explain Hierarchical model.
➢ Explain 3-level DBMS architecture.
➢ .
Prof. K. Adisesha
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