This document discusses different types of data models, including hierarchical, network, relational, and object-oriented models. It focuses on explaining the relational model. The relational model organizes data into tables with rows and columns and handles relationships using keys. It allows for simple and symmetric data retrieval and integrity through mechanisms like normalization. The relational model is well-suited for the database assignment scenario because it supports linking data across multiple tables using primary and foreign keys, and provides query capabilities through SQL.
This document outlines a course on advances in database management systems. The course covers object and object-relational databases over 9 hours. Topics include object database concepts, object extensions to SQL, the ODMG object model and ODL language, object database design, and the OQL query language. The course is taught by Dr. M.K. Jayanthi Kannan at JAIN Deemed To-Be University.
Data Models In Database Management SystemAmad Ahmad
This document discusses different types of data models used in database management systems (DBMS), including record-based, relational, network, hierarchical, and entity-relationship (ER) models. It provides an overview of key concepts like data, information, databases, and data models. For each model type, it describes how data is organized and represented. For example, it explains that the relational model organizes data into two-dimensional tables with attributes and tuples, while the hierarchical model structures data in a tree configuration. The ER model views data as entities and relationships between entities.
This document provides an overview of data modeling concepts. It discusses the importance of data modeling, the basic building blocks of data models including entities, attributes, and relationships. It also covers different types of data models such as conceptual, logical, and physical models. The document discusses relational and non-relational data models as well as emerging models like object-oriented, XML, and big data models. Business rules and their role in database design are also summarized.
This document discusses data modeling and different data models. It covers the evolution of data models from hierarchical to network to relational models. It also discusses object-oriented and XML data models. Key aspects of data modeling include entities, attributes, relationships, and constraints. Different abstraction levels for data modeling include external, conceptual, and internal views.
This document provides an overview of an introductory database course, including information about the instructors, schedule, topics to be covered, expectations for student conduct, and how to succeed in the course. The topics that will be covered include database fundamentals, the database development process, conceptual and logical data modeling, physical database design, implementation with SQL, and an advanced topic. Students are expected to attend lectures and labs, be punctual, not distract others, and are advised to attend lectures, read the textbook, review materials, and ask questions.
This document defines database and DBMS, describes their advantages over file-based systems like data independence and integrity. It explains database system components and architecture including physical and logical data models. Key aspects covered are data definition language to create schemas, data manipulation language to query data, and transaction management to handle concurrent access and recovery. It also provides a brief history of database systems and discusses database users and the critical role of database administrators.
Advance Database Management Systems -Object Oriented Principles In DatabaseSonali Parab
This document provides an overview of object-oriented database management systems (OODBMS), which combine object-oriented programming principles with database management. It discusses how OODBMSs support encapsulation, polymorphism, inheritance and ACID properties while allowing for complex objects, relationships, and queries of large amounts of data. The document also lists advantages and disadvantages of OODBMSs compared to relational database systems and examples of both proprietary and open-source OODBMSs.
This document discusses different types of data models, including hierarchical, network, relational, and object-oriented models. It focuses on explaining the relational model. The relational model organizes data into tables with rows and columns and handles relationships using keys. It allows for simple and symmetric data retrieval and integrity through mechanisms like normalization. The relational model is well-suited for the database assignment scenario because it supports linking data across multiple tables using primary and foreign keys, and provides query capabilities through SQL.
This document outlines a course on advances in database management systems. The course covers object and object-relational databases over 9 hours. Topics include object database concepts, object extensions to SQL, the ODMG object model and ODL language, object database design, and the OQL query language. The course is taught by Dr. M.K. Jayanthi Kannan at JAIN Deemed To-Be University.
Data Models In Database Management SystemAmad Ahmad
This document discusses different types of data models used in database management systems (DBMS), including record-based, relational, network, hierarchical, and entity-relationship (ER) models. It provides an overview of key concepts like data, information, databases, and data models. For each model type, it describes how data is organized and represented. For example, it explains that the relational model organizes data into two-dimensional tables with attributes and tuples, while the hierarchical model structures data in a tree configuration. The ER model views data as entities and relationships between entities.
This document provides an overview of data modeling concepts. It discusses the importance of data modeling, the basic building blocks of data models including entities, attributes, and relationships. It also covers different types of data models such as conceptual, logical, and physical models. The document discusses relational and non-relational data models as well as emerging models like object-oriented, XML, and big data models. Business rules and their role in database design are also summarized.
This document discusses data modeling and different data models. It covers the evolution of data models from hierarchical to network to relational models. It also discusses object-oriented and XML data models. Key aspects of data modeling include entities, attributes, relationships, and constraints. Different abstraction levels for data modeling include external, conceptual, and internal views.
This document provides an overview of an introductory database course, including information about the instructors, schedule, topics to be covered, expectations for student conduct, and how to succeed in the course. The topics that will be covered include database fundamentals, the database development process, conceptual and logical data modeling, physical database design, implementation with SQL, and an advanced topic. Students are expected to attend lectures and labs, be punctual, not distract others, and are advised to attend lectures, read the textbook, review materials, and ask questions.
This document defines database and DBMS, describes their advantages over file-based systems like data independence and integrity. It explains database system components and architecture including physical and logical data models. Key aspects covered are data definition language to create schemas, data manipulation language to query data, and transaction management to handle concurrent access and recovery. It also provides a brief history of database systems and discusses database users and the critical role of database administrators.
Advance Database Management Systems -Object Oriented Principles In DatabaseSonali Parab
This document provides an overview of object-oriented database management systems (OODBMS), which combine object-oriented programming principles with database management. It discusses how OODBMSs support encapsulation, polymorphism, inheritance and ACID properties while allowing for complex objects, relationships, and queries of large amounts of data. The document also lists advantages and disadvantages of OODBMSs compared to relational database systems and examples of both proprietary and open-source OODBMSs.
This document provides an overview of database concepts and terminology. It discusses different types of databases based on number of users (single, multi, workgroup, enterprise), number of computers used (centralized, distributed), and how up-to-date the data is (production, data warehouse). It also covers database categorizations, the relational model, entity types and occurrences, relationship types and occurrences, attributes, keys, and E.F. Codd's 12 rules for relational databases.
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.
This chapter introduces database systems and their advantages over traditional file systems. It discusses the components of a database system including the database, database management system (DBMS), and their roles in data storage and access. Databases have evolved from file systems to address issues like data redundancy, inconsistency, and dependence on structure and storage characteristics. The chapter outlines different types of databases and the importance of database design. It provides examples of problems in traditional file system data management to illustrate improvements made by modern database systems.
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.
Normalisation is a process that structures data in a relational database to minimize duplication and redundancy while preserving information. It aims to ensure data is structured efficiently and consistently through multiple forms. The stages of normalization include first normal form (1NF), second normal form (2NF), third normal form (3NF), Boyce-Codd normal form (BCNF), fourth normal form (4NF) and fifth normal form (5NF). Higher normal forms eliminate more types of dependencies to optimize the database structure.
The document discusses database normalization. It begins with a brief history of normalization, introduced by Edgar Codd in 1970. It then defines database normalization as removing redundant data to improve storage efficiency, data integrity, and scalability. The document provides examples to illustrate the concepts of first, second, and third normal forms. It shows how a book database can be normalized by separating data into separate tables for authors, subjects, and books and defining relationships between the tables using primary and foreign keys. This normalization process addresses issues like redundant data, data integrity, and scalability.
The document discusses the key components and functions of database systems. It begins by explaining the difference between data and information and how databases evolved from file systems to address issues like data redundancy and lack of integrity. The main components of a database system are described as hardware, software, people, procedures, and data. Key functions of a database management system (DBMS) include data storage management, security management, and ensuring data integrity. Overall, the document provides a high-level overview of databases, their history and structure.
This document discusses different data models used in database management systems including record-based, relational, network, hierarchical, and entity-relationship models. It provides details on each model such as how data is organized. A record-based model uses fixed-length records and fields. The relational model organizes data into tables with rows and columns. The network model links entities through multiple paths in a graph structure. The hierarchical model arranges data in a tree structure. Finally, the entity-relationship model views the real world as entities and relationships between entities.
The document compares file systems and database management systems (DBMS) for storing a company's 500GB of employee, department, product, and sales data. It notes several drawbacks of using a file system, including data redundancy, integrity issues, restricted concurrent access, and lack of flexibility. It then outlines key advantages of using a DBMS instead, such as data sharing, enforcement of security and integrity, reduction of redundancy, and support for concurrent access and crash recovery.
A database management system (DBMS) is a collection of programs that enables users to create and maintain databases and control all access to them. The primary goal of a DBMS is to provide an environment that is both convenient and efficient for users to retrieve and store information.
This document provides an overview of database system concepts and architecture. It discusses different data models including conceptual, physical and implementation models. It also covers database languages, interfaces, utilities and centralized versus distributed (client-server) architectures. Specifically, it describes hierarchical and network data models, the three schema architecture, data independence, DBMS languages like DDL and DML, and different DBMS classifications including relational, object-oriented and distributed systems.
This document discusses mobile computing and mobile databases. It begins by defining mobile computing as allowing users to access network services from anywhere using portable computers connected via wireless networks. It then discusses challenges of mobile computing like limited bandwidth, intermittent connectivity, and changing locations. The document outlines the general architecture of mobile computing including mobile units, base stations, and wireless communication. It describes key aspects of mobile databases like being located on mobile devices and communicating with central databases. Finally, it discusses characteristics of mobile environments like high latency, limited battery life, and unreliable connectivity that must be addressed in mobile applications and databases.
This document discusses different types of data models, including object based models like entity relationship and object oriented models, physical models that describe how data is stored, and record based logical models. It specifically mentions hierarchical, network, and relational models as examples of record based logical data models. The purpose of data models is to represent and make data understandable by specifying rules for database construction, allowed data operations, and integrity.
This document discusses denormalization, which refers to modifying a relational schema to be less normalized by combining relations or duplicating attributes. It describes 7 common denormalization techniques: 1) combining one-to-one relations, 2) duplicating attributes in one-to-many relations, 3) duplicating foreign keys, 4) duplicating attributes in many-to-many relations, 5) introducing repeating groups, 6) creating extract tables, and 7) partitioning relations. While denormalization can improve performance, it can also increase complexity, reduce flexibility, and slow down updates. Data integrity must be maintained when denormalizing.
This chapter discusses the relational database model and its basic components. It explains that the relational model provides a logical view of data organized into tables composed of rows and columns. Each row must be uniquely identifiable through a primary key. Tables can be linked together through common attributes, and relationships between entities can be modeled as one-to-one, one-to-many, or many-to-many. The chapter also covers relational operators, keys, data integrity rules, and how to handle data redundancy and indexing in a relational database.
The document discusses different database models including hierarchical, network, relational, entity-relationship, object-oriented, object-relational, and semi-structured models. It provides details on the characteristics, structures, advantages and disadvantages of each model. It also includes examples and diagrams to illustrate concepts like hierarchical structure, network structure, relational schema, entity relationship diagrams, object oriented diagrams, and XML schema. The document appears to be teaching materials for a database management course that provides an overview of various database models.
The document provides an introduction to database management systems (DBMS). It discusses the components of a DBMS environment including hardware, software, data, and procedures. It also outlines the roles in a database environment, the history of database systems, and the functions of a DBMS. Advantages include data control and consistency, while disadvantages include complexity, size, and costs.
An Introduction to Architecture of Object Oriented Database Management System and how it differs from RDBMS means Relational Database Management System
A column-oriented database stores data tables as columns rather than rows. This improves the speed of queries that aggregate data over large numbers of records by only reading the necessary columns from disk. Column databases compress data well and avoid reading unnecessary columns. However, they have slower insert speeds and incremental loads compared to row-oriented databases, which store each row together and are faster for queries needing entire rows.
1. The document discusses the components and overall structure of a database management system (DBMS). It describes the various levels of database architecture including the physical, logical, and external levels.
2. The key components of a DBMS include users, a query processor, storage manager, and data structures. The query processor consists of a DML compiler, DDL interpreter, and query evaluation engine. The storage manager includes modules for authorization, transactions, file management, and buffering.
3. Data models help represent the design of a database and describe entities, attributes, relationships, and constraints. Common models include the entity-relationship model and object-oriented model.
Database development life cycle unit 2 part 1Ram Paliwal
The document discusses the database development life cycle (DDLC), which is a six-phase process for designing, implementing, and maintaining a database system to meet an organization's information needs. The six phases are: 1) database initial study, 2) database design, 3) implementation and loading, 4) testing and evaluation, 5) operation, and 6) maintenance and evolution. Each phase is described in detail, from analyzing requirements in the initial study to ongoing maintenance activities once the database is operational.
This document provides an overview of database concepts and terminology. It discusses different types of databases based on number of users (single, multi, workgroup, enterprise), number of computers used (centralized, distributed), and how up-to-date the data is (production, data warehouse). It also covers database categorizations, the relational model, entity types and occurrences, relationship types and occurrences, attributes, keys, and E.F. Codd's 12 rules for relational databases.
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.
This chapter introduces database systems and their advantages over traditional file systems. It discusses the components of a database system including the database, database management system (DBMS), and their roles in data storage and access. Databases have evolved from file systems to address issues like data redundancy, inconsistency, and dependence on structure and storage characteristics. The chapter outlines different types of databases and the importance of database design. It provides examples of problems in traditional file system data management to illustrate improvements made by modern database systems.
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.
Normalisation is a process that structures data in a relational database to minimize duplication and redundancy while preserving information. It aims to ensure data is structured efficiently and consistently through multiple forms. The stages of normalization include first normal form (1NF), second normal form (2NF), third normal form (3NF), Boyce-Codd normal form (BCNF), fourth normal form (4NF) and fifth normal form (5NF). Higher normal forms eliminate more types of dependencies to optimize the database structure.
The document discusses database normalization. It begins with a brief history of normalization, introduced by Edgar Codd in 1970. It then defines database normalization as removing redundant data to improve storage efficiency, data integrity, and scalability. The document provides examples to illustrate the concepts of first, second, and third normal forms. It shows how a book database can be normalized by separating data into separate tables for authors, subjects, and books and defining relationships between the tables using primary and foreign keys. This normalization process addresses issues like redundant data, data integrity, and scalability.
The document discusses the key components and functions of database systems. It begins by explaining the difference between data and information and how databases evolved from file systems to address issues like data redundancy and lack of integrity. The main components of a database system are described as hardware, software, people, procedures, and data. Key functions of a database management system (DBMS) include data storage management, security management, and ensuring data integrity. Overall, the document provides a high-level overview of databases, their history and structure.
This document discusses different data models used in database management systems including record-based, relational, network, hierarchical, and entity-relationship models. It provides details on each model such as how data is organized. A record-based model uses fixed-length records and fields. The relational model organizes data into tables with rows and columns. The network model links entities through multiple paths in a graph structure. The hierarchical model arranges data in a tree structure. Finally, the entity-relationship model views the real world as entities and relationships between entities.
The document compares file systems and database management systems (DBMS) for storing a company's 500GB of employee, department, product, and sales data. It notes several drawbacks of using a file system, including data redundancy, integrity issues, restricted concurrent access, and lack of flexibility. It then outlines key advantages of using a DBMS instead, such as data sharing, enforcement of security and integrity, reduction of redundancy, and support for concurrent access and crash recovery.
A database management system (DBMS) is a collection of programs that enables users to create and maintain databases and control all access to them. The primary goal of a DBMS is to provide an environment that is both convenient and efficient for users to retrieve and store information.
This document provides an overview of database system concepts and architecture. It discusses different data models including conceptual, physical and implementation models. It also covers database languages, interfaces, utilities and centralized versus distributed (client-server) architectures. Specifically, it describes hierarchical and network data models, the three schema architecture, data independence, DBMS languages like DDL and DML, and different DBMS classifications including relational, object-oriented and distributed systems.
This document discusses mobile computing and mobile databases. It begins by defining mobile computing as allowing users to access network services from anywhere using portable computers connected via wireless networks. It then discusses challenges of mobile computing like limited bandwidth, intermittent connectivity, and changing locations. The document outlines the general architecture of mobile computing including mobile units, base stations, and wireless communication. It describes key aspects of mobile databases like being located on mobile devices and communicating with central databases. Finally, it discusses characteristics of mobile environments like high latency, limited battery life, and unreliable connectivity that must be addressed in mobile applications and databases.
This document discusses different types of data models, including object based models like entity relationship and object oriented models, physical models that describe how data is stored, and record based logical models. It specifically mentions hierarchical, network, and relational models as examples of record based logical data models. The purpose of data models is to represent and make data understandable by specifying rules for database construction, allowed data operations, and integrity.
This document discusses denormalization, which refers to modifying a relational schema to be less normalized by combining relations or duplicating attributes. It describes 7 common denormalization techniques: 1) combining one-to-one relations, 2) duplicating attributes in one-to-many relations, 3) duplicating foreign keys, 4) duplicating attributes in many-to-many relations, 5) introducing repeating groups, 6) creating extract tables, and 7) partitioning relations. While denormalization can improve performance, it can also increase complexity, reduce flexibility, and slow down updates. Data integrity must be maintained when denormalizing.
This chapter discusses the relational database model and its basic components. It explains that the relational model provides a logical view of data organized into tables composed of rows and columns. Each row must be uniquely identifiable through a primary key. Tables can be linked together through common attributes, and relationships between entities can be modeled as one-to-one, one-to-many, or many-to-many. The chapter also covers relational operators, keys, data integrity rules, and how to handle data redundancy and indexing in a relational database.
The document discusses different database models including hierarchical, network, relational, entity-relationship, object-oriented, object-relational, and semi-structured models. It provides details on the characteristics, structures, advantages and disadvantages of each model. It also includes examples and diagrams to illustrate concepts like hierarchical structure, network structure, relational schema, entity relationship diagrams, object oriented diagrams, and XML schema. The document appears to be teaching materials for a database management course that provides an overview of various database models.
The document provides an introduction to database management systems (DBMS). It discusses the components of a DBMS environment including hardware, software, data, and procedures. It also outlines the roles in a database environment, the history of database systems, and the functions of a DBMS. Advantages include data control and consistency, while disadvantages include complexity, size, and costs.
An Introduction to Architecture of Object Oriented Database Management System and how it differs from RDBMS means Relational Database Management System
A column-oriented database stores data tables as columns rather than rows. This improves the speed of queries that aggregate data over large numbers of records by only reading the necessary columns from disk. Column databases compress data well and avoid reading unnecessary columns. However, they have slower insert speeds and incremental loads compared to row-oriented databases, which store each row together and are faster for queries needing entire rows.
1. The document discusses the components and overall structure of a database management system (DBMS). It describes the various levels of database architecture including the physical, logical, and external levels.
2. The key components of a DBMS include users, a query processor, storage manager, and data structures. The query processor consists of a DML compiler, DDL interpreter, and query evaluation engine. The storage manager includes modules for authorization, transactions, file management, and buffering.
3. Data models help represent the design of a database and describe entities, attributes, relationships, and constraints. Common models include the entity-relationship model and object-oriented model.
Database development life cycle unit 2 part 1Ram Paliwal
The document discusses the database development life cycle (DDLC), which is a six-phase process for designing, implementing, and maintaining a database system to meet an organization's information needs. The six phases are: 1) database initial study, 2) database design, 3) implementation and loading, 4) testing and evaluation, 5) operation, and 6) maintenance and evolution. Each phase is described in detail, from analyzing requirements in the initial study to ongoing maintenance activities once the database is operational.
Database development life cycle unit 2 part 1Ram Paliwal
The database development life cycle (DDLC) is a six-phase process for designing, implementing, and maintaining a database system to meet an organization's information needs. The six phases are: 1) initial study, 2) design, 3) implementation and loading, 4) testing and evaluation, 5) operation, and 6) maintenance and evolution. In the initial study phase, the current system is examined to analyze problems, define objectives and scope. The design phase focuses on creating the database model. In implementation, the design is executed by installing the DBMS, creating databases, and loading data. Testing and evaluation ensures the database performs as expected. During operation, the completed system is used. Maintenance involves routine activities like backups
The document discusses the architecture and components of database management systems (DBMS). It describes how DBMS packages have evolved from monolithic to modular client-server systems. It also discusses the three schema architecture comprising the internal, conceptual, and external schemas which enables data independence. The key components of a DBMS include the data definition language, data manipulation language, and various interfaces. DBMSs can be classified based on their data model, number of users, distribution, and purpose.
The document provides an introduction to database systems, including:
- Key components of a database system including the database, DBMS, schemas, instances, and three-schema architecture.
- Data models used to represent data at different levels of abstraction.
- Roles of different users who interact with the database such as administrators, designers, and end users.
- Architectures for DBMS including centralized, client-server, and multi-tier architectures.
- Concepts of data independence which allows changes at one level without affecting other levels.
The document discusses the database development life cycle (DBLC), which follows a similar process to the systems development life cycle (SDLC). The DBLC involves gathering requirements, database analysis, design, implementation, testing and evaluation, and maintenance. It describes each stage in detail, including conceptual, logical, and physical data modeling during the design stage. The goal is to systematically plan and develop a database to meet requirements while ensuring completeness, integrity, flexibility, and usability.
The document provides an overview of databases and data modeling. It introduces key concepts such as database management systems (DBMS), database design phases, database actors and workers, and advantages of the DBMS approach over traditional file processing. Some key points covered include the self-describing nature of databases, program-data independence, multiple views of data, transaction processing, roles of database administrators and designers, and how DBMSs provide controlled data redundancy and security. An example university database structure is also presented.
Attributes are properties or characteristics that describe entities. In the EMPLOYEE entity example, attributes could include:
- Employee ID
- Name
- Date of birth
- Address
- Salary
These attributes describe and provide information about each employee entity instance. Attributes help define and differentiate entity instances from each other.
This document provides an introduction to database management systems (DBMS). It defines key DBMS concepts like databases, data, schemas, and instances. It describes typical DBMS functionality like defining databases, loading data, querying data, and concurrent access. It introduces data models, DBMS languages, database users, and advantages of the database approach. It also discusses the hierarchical and network data models. The document aims to give an overview of fundamental DBMS concepts and components.
The document discusses physical database requirements and defines three stages of database design: conceptual, logical, and physical. It provides details on each stage, including that physical database design implements the logical data model in a DBMS and involves selecting file storage and ensuring efficient access. The document also covers database architectures, noting that a three-tier architecture separates the user applications from the physical database.
This document provides an introduction and overview of database management systems (DBMS). It discusses key concepts like data models, schemas, instances, and the three-schema architecture. The three-schema architecture separates a DBMS into three logical levels: internal, conceptual, and external. This architecture provides data independence and allows changes to one level without affecting the others. The document also covers topics like the entity-relationship model, relational model, and distributed data processing.
Chapter-2 Database System Concepts and ArchitectureKunal Anand
This document provides an overview of database management systems concepts and architecture. It discusses different data models including hierarchical, network, relational, entity-relationship, object-oriented, and object-relational models. It also describes the 3-schema architecture with external, conceptual, and internal schemas and explains components of a DBMS including users, storage and query managers. Finally, it covers database languages like DDL, DML, and interfaces like menu-based, form-based and graphical user interfaces.
Lecture 09 - Migration to the Architected Environmentphanleson
The chapter discusses the process of migrating to an architected data warehouse environment. It describes developing a migration plan starting with a corporate data model and defining a system of record. The plan also includes designing the data warehouse, building interfaces to load data, and populating the first subject area. An iterative development approach is used where the data architect gets feedback from analysts to continually improve the data warehouse over time. Strategic considerations include addressing both operational and decision support needs.
Unit 1: Introduction to DBMS Unit 1 CompleteRaj vardhan
This document discusses database management systems (DBMS) and their advantages over traditional file-based data storage. It describes the key components of a DBMS, including the hardware, software, data, procedures, and users. It also explains the three levels of abstraction in a DBMS - the physical level, logical level, and view level - and how they provide data independence. Finally, it provides an overview of different data models like hierarchical, network, and relational models.
The document provides information about DBMS (Database Management System). It defines key concepts like data, database, DBMS and discusses their advantages over traditional file processing systems. It also describes different DBMS architectures including 1-tier, 2-tier and 3-tier architectures. Finally, it explains different database models like hierarchical, network, entity-relationship and relational models.
The document discusses the architecture and components of a database management system (DBMS). It describes the three levels of abstraction in a DBMS - physical, logical, and view levels. It also explains the roles of different types of database users and the responsibilities of a database administrator. The key components of a DBMS discussed include the storage manager, query processor, and functions like data storage, security management, and database access.
The document discusses three types of data models: conceptual, logical, and physical. A conceptual data model defines business concepts and rules and is created by business stakeholders. A logical data model defines how the system should be implemented regardless of the specific database and is created by data architects and analysts. A physical data model describes how the system will be implemented using a specific database management system and is created by database administrators and developers.
This document provides an overview of database management systems (DBMS). It discusses what a DBMS is, the main types of DBMS models including hierarchical, network and relational models, and the architecture of a DBMS including external, conceptual and internal levels. Advantages of DBMS include controlling redundancy, sharing data, data consistency and integration. Disadvantages include costs of hardware, software, staff training and potential for database damage. The document concludes that a DBMS allows users to create, read, update and delete database data consistently.
Similar to Database design (conceptual, logical and physical design) unit 2 part 2 (20)
The document categorizes information systems as either operations support systems or management support systems. Operations support systems process transactional data to support daily business operations, including transaction processing systems, process control systems, and office automation systems. Management support systems provide information and decision support, including management information systems, decision support systems, executive support systems, and enterprise systems which integrate business functions across an organization.
Management inofrmation system basics by ram k paliwalRam Paliwal
This document defines information systems and describes their key components. It provides several definitions of information systems that focus on the technological components (hardware, software, data) that make up information systems and their role in supporting organizational processes and decision-making. The document outlines the five core components of information systems: hardware, software, data, people, and processes. It provides a brief description of each component, emphasizing that while technology is important, people and processes are what truly define information systems.
Database design (entity attribute and its types) unit 2 part 4Ram Paliwal
This document discusses database design and different types of attributes. It explains that each entity is described by a set of attributes. There are several types of attributes: simple attributes which are single-valued, composite attributes which are hierarchies of other attributes, multivalued attributes which can have multiple values per entity, and derived attributes which are calculated from other stored attributes. The document provides examples of each type of attribute from an employee entity to illustrate the different attribute types.
Database design (entity, entity set and entity type) unit 2 part 3Ram Paliwal
The document discusses database design concepts including entities, entity sets, and entity types. An entity is an object in the real world that can be differentiated from other objects. An entity set is a collection of similar entities at a point in time. The document also describes different types of entities such as independent entities, dependent entities, and characteristic entities. Independent entities are the core tables in a database, while dependent entities rely on other tables and characteristic entities provide additional details about other entities.
System component and system calls unit 1 by ram k paliwalRam Paliwal
The document discusses the components and system calls of the Windows operating system. It describes the main layers as the hardware abstraction layer, kernel, and executive which run in kernel mode. User-mode subsystems include environmental and protection subsystems. The main system call types are process control, file manipulation, device manipulation, information maintenance, and communications. Process control calls include creating and terminating processes while file manipulation calls involve opening, reading and writing files.
Sdlc spiral model in software engineering basics by ram k paliwalRam Paliwal
The document discusses software process models and the spiral model in particular. It notes that prescriptive process models brought order to software development but work remains complex. The spiral model is an evolutionary model that combines iterative prototyping with controlled aspects of waterfall. With spiral, software is developed through a series of evolutionary releases from initial prototypes to more complete versions. Each pass through the planning phase allows for adjustments to the project plan based on customer feedback.
Types of operating system unit 1 by Ram K PaliwalRam Paliwal
The document discusses the main types of operating systems: serial processing, batch processing, time-sharing, real-time, and multi-user/multi-tasking network operating systems. Serial processing operating systems execute instructions sequentially without user interaction. Batch processing groups similar jobs into batches to be processed when the computer is idle. Time-sharing operating systems allow multiple users or programs to share resources by rapidly switching between tasks. Real-time operating systems are used for systems like robots where response time is critical. Network operating systems manage shared resources, users, security, and applications over a private network.
Srs (software requirement specification) in software engineering basics by ra...Ram Paliwal
The document discusses software requirement specification (SRS), which defines the necessary functional and non-functional requirements for a software system from the user's perspective. An SRS is developed through an agreement between the customer and contractors. It should have characteristics like correctness, completeness, consistency, unambiguity, modifiability, verifiability and testability. The SRS is used to guide software development and testing.
Sdlc process models in software engineering basics by ram k paliwalRam Paliwal
1) Prescriptive process models were proposed to structure software development but software engineering remains complex.
2) Different process models apply different emphases to core framework activities and define different process flows.
3) The waterfall model is a sequential approach dividing the lifecycle into phases that do not overlap. It is simple but inflexible to changes.
Operating system basics function of os unit 1 by ram k paliwal part 1Ram Paliwal
The document discusses the basics of operating systems and computer systems. It defines an operating system as a program that manages a computer's hardware and acts as an intermediary between the user and computer. A computer system consists of hardware components like the CPU and memory, an operating system, application programs, and users. The operating system controls hardware usage and coordinates application programs for users. It describes functions of the operating system like memory management, device management, processor management, file management, and security.
Software and software engineering basics by ram k paliwalRam Paliwal
Software, software Engineering, Software Engineering Layered Technology, These slides provide the details about software and Software Engineering basics.
E-commerce involves the exchange of goods and services over electronic systems like the internet. It requires products or services to sell, a way to accept orders and payments, fulfillment of orders, and customer service. There are four main categories of e-commerce: business to business, business to consumer, consumer to consumer, and consumer to business. Key drivers include technology, policies, skills, economics, and competition. Benefits include lower costs, larger markets, and improved customer interactions, while limitations relate to security, access, standards, and lack of human interaction.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Low power architecture of logic gates using adiabatic techniquesnooriasukmaningtyas
The growing significance of portable systems to limit power consumption in ultra-large-scale-integration chips of very high density, has recently led to rapid and inventive progresses in low-power design. The most effective technique is adiabatic logic circuit design in energy-efficient hardware. This paper presents two adiabatic approaches for the design of low power circuits, modified positive feedback adiabatic logic (modified PFAL) and the other is direct current diode based positive feedback adiabatic logic (DC-DB PFAL). Logic gates are the preliminary components in any digital circuit design. By improving the performance of basic gates, one can improvise the whole system performance. In this paper proposed circuit design of the low power architecture of OR/NOR, AND/NAND, and XOR/XNOR gates are presented using the said approaches and their results are analyzed for powerdissipation, delay, power-delay-product and rise time and compared with the other adiabatic techniques along with the conventional complementary metal oxide semiconductor (CMOS) designs reported in the literature. It has been found that the designs with DC-DB PFAL technique outperform with the percentage improvement of 65% for NOR gate and 7% for NAND gate and 34% for XNOR gate over the modified PFAL techniques at 10 MHz respectively.
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
ML Based Model for NIDS MSc Updated Presentation.v2.pptx
Database design (conceptual, logical and physical design) unit 2 part 2
1. Unit -2
DATABASE DESIGN AND MODELS CHARACTERISTICS - PART 2
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2. Database Design
Data modelling is the first step in the process of database design.
This step is sometimes considered to be a high-level and abstract
design phase, also referred to as conceptual design. The aim of this
phase is to describe:
◦ The data contained in the database
(e.g., entities: students, lecturers, courses, subjects)
◦ The relationships between data items
(e.g., students are supervised by lecturers; lecturers teach
courses)
◦ The constraints on data
(e.g., student number has exactly eight digits; a subject has
four or six units of credit only)
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3. Database Design
In the second step
◦ The data items
◦ The relationships
◦ The constraints
are all expressed using the concepts provided by the high-level data model.
Because these concepts do not include the
◦ Implementation details,
◦ The result of the data modelling process is a (semi) formal representation of the database
structure.
This result is quite easy to understand so it is used as reference to make sure
that all the user’s requirements are met.
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4. Database Design
The third step is database design. During this step, we might
have two sub-steps:
◦ Database logical design, which defines a database in a data model
of a specific DBMS,
◦ Database physical design, which defines the internal database
storage structure, file organization or indexing techniques.
These two sub-steps are database implementation and
operations/user interfaces building steps
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5. Database Design
In the database design phases, data are represented using a
certain data model.
The data model is a collection of concepts or notations for
◦ Describing data
◦ Data relationships
◦ Data semantics
◦ Data constraints.
Most data models also include a set of basic operations for
manipulating data in the database.
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6. Database Design
The database design is very much like that.
◦ It starts with users identifying the business rules;
◦ then the database designers and analysts create the database
design;
◦ and then the database administrator implements the design using
a DBMS.
The following subsections summarize the models in order of
decreasing level of abstraction
◦ External Model
◦ Conceptual Model
◦ Internal Model
◦ Physical Model
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7. Database Design
External models
◦ Represent the user’s view of the database
◦ Contain multiple different external views
◦ Are closely related to the real world as perceived by each user
Conceptual models
◦ Provide flexible data-structuring capabilities
◦ Present a “community view”: the logical structure of the entire
database
◦ Contain data stored in the database
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8. Database Design
◦ Show relationships among data including:
◦ Constraints
◦ Semantic information (e.g., business rules)
◦ Security and integrity information
◦ Consider a database as a collection of entities (objects) of various
kinds
◦ Are the basis for identification and high-level description of main
data objects; they avoid details
◦ Are database independent regardless of the database you will be
using
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9. Database Design
Internal models
The three best-known models of this kind are the relational data
model, the network data model and the hierarchical data model.
These internal models:
◦ Consider a database as a collection of fixed-size records
◦ Are closer to the physical level or file structure
◦ Are a representation of the database as seen by the DBMS.
◦ Require the designer to match the conceptual model’s characteristics and
constraints to those of the selected implementation model
◦ Involve mapping the entities in the conceptual model to the tables in the
relational model
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10. Database Design
Physical models
◦ Are the physical representation of the database
◦ Have the lowest level of abstractions
◦ Are how the data is stored; they deal with
◦ Run-time performance
◦ Storage utilization and compression
◦ File organization and access methods
◦ Data encryption
◦ Are the physical level – managed by the operating system (OS)
◦ Provide concepts that describe the details of how data are stored
in the computer’s memory
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