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This document discusses database architecture and concepts. It covers the three-level database architecture including the external, conceptual, and internal levels. It describes data independence which provides immunity from changes between the different levels. The document also outlines the functions of a database management system including data processing, transaction support, concurrency control, and more. Different database environments are reviewed such as single-user, multi-user, client-server, and file server configurations.
The document discusses the architecture of a database management system (DBMS). It describes the three levels of DBMS architecture: the external, conceptual, and internal views. The external view represents how individual users see the data. The conceptual view presents a common view of data for all users. The internal view describes the physical storage and organization of data. This three-level architecture provides data independence, where each level is isolated from changes in the other levels.
The document discusses data abstraction and the three schema architecture in database design. It explains that data abstraction has three levels: physical, logical, and view. The physical level describes how data is stored, the logical level describes the data and relationships, and the view level allows applications to hide data types and information. It also describes instances, which are the current stored data, and schemas, which are the overall database design. Schemas are partitioned into physical, logical, and external schemas corresponding to the levels of abstraction. The three schema architecture provides data independence and allows separate management of the logical and physical designs.
The document discusses three levels of data abstraction - view level, logical level, and physical level. It also discusses three schema architecture - external schema, conceptual schema, and internal schema. The levels and schemas describe how data is represented and accessed at different levels of abstraction, hiding low-level implementation details from users.
This document discusses data independence in databases. It defines database schemas, including the internal, conceptual, and external schemas that make up the three-schema architecture. The database state and valid state are also defined. Logical data independence allows changes to the conceptual schema without changing external schemas or applications. Physical data independence allows changes to the internal schema without changing the conceptual schema. Both help ensure that changes to lower-level schemas do not require changes to higher-level schemas and applications.
The document discusses three levels of data abstraction defined by ANSI SPARC: external, conceptual, and internal. The external level represents the end user's view. The conceptual level integrates all external views into a global view of the entire database. The internal level maps the conceptual model to a specific DBMS and depends on the database software used.
There are three levels of data abstraction: the physical level describes how data is actually stored, the logical level describes what data is stored and the relationships between data, and the view level describes how users interact with the database. A database schema defines the logical structure of a database, including tables, fields, and relationships. An instance is the current state of data stored in the database at a given time. Physical data independence allows the physical schema to be modified without changing the logical schema. Data models include the relational model using tables, the entity-relationship model using entities and relationships, object-based models, and semi-structured models like XML.
This document provides an introduction to database management systems (DBMS). It defines key terminology related to databases and discusses problems with manual databases. It describes the functions and advantages of DBMS, including data representation, transaction management, data sharing, and increased security. Examples of popular DBMS are provided, such as Oracle, Microsoft SQL Server, and MySQL. Database system architecture, data models, and the relational model are overviewed. Finally, entity relationship (ER) modeling is explained as a way to conceptualize data needs and design the database logically before implementation.
This document discusses database architecture and concepts. It covers the three-level database architecture including the external, conceptual, and internal levels. It describes data independence which provides immunity from changes between the different levels. The document also outlines the functions of a database management system including data processing, transaction support, concurrency control, and more. Different database environments are reviewed such as single-user, multi-user, client-server, and file server configurations.
The document discusses the architecture of a database management system (DBMS). It describes the three levels of DBMS architecture: the external, conceptual, and internal views. The external view represents how individual users see the data. The conceptual view presents a common view of data for all users. The internal view describes the physical storage and organization of data. This three-level architecture provides data independence, where each level is isolated from changes in the other levels.
The document discusses data abstraction and the three schema architecture in database design. It explains that data abstraction has three levels: physical, logical, and view. The physical level describes how data is stored, the logical level describes the data and relationships, and the view level allows applications to hide data types and information. It also describes instances, which are the current stored data, and schemas, which are the overall database design. Schemas are partitioned into physical, logical, and external schemas corresponding to the levels of abstraction. The three schema architecture provides data independence and allows separate management of the logical and physical designs.
The document discusses three levels of data abstraction - view level, logical level, and physical level. It also discusses three schema architecture - external schema, conceptual schema, and internal schema. The levels and schemas describe how data is represented and accessed at different levels of abstraction, hiding low-level implementation details from users.
This document discusses data independence in databases. It defines database schemas, including the internal, conceptual, and external schemas that make up the three-schema architecture. The database state and valid state are also defined. Logical data independence allows changes to the conceptual schema without changing external schemas or applications. Physical data independence allows changes to the internal schema without changing the conceptual schema. Both help ensure that changes to lower-level schemas do not require changes to higher-level schemas and applications.
The document discusses three levels of data abstraction defined by ANSI SPARC: external, conceptual, and internal. The external level represents the end user's view. The conceptual level integrates all external views into a global view of the entire database. The internal level maps the conceptual model to a specific DBMS and depends on the database software used.
There are three levels of data abstraction: the physical level describes how data is actually stored, the logical level describes what data is stored and the relationships between data, and the view level describes how users interact with the database. A database schema defines the logical structure of a database, including tables, fields, and relationships. An instance is the current state of data stored in the database at a given time. Physical data independence allows the physical schema to be modified without changing the logical schema. Data models include the relational model using tables, the entity-relationship model using entities and relationships, object-based models, and semi-structured models like XML.
This document provides an introduction to database management systems (DBMS). It defines key terminology related to databases and discusses problems with manual databases. It describes the functions and advantages of DBMS, including data representation, transaction management, data sharing, and increased security. Examples of popular DBMS are provided, such as Oracle, Microsoft SQL Server, and MySQL. Database system architecture, data models, and the relational model are overviewed. Finally, entity relationship (ER) modeling is explained as a way to conceptualize data needs and design the database logically before implementation.
This document discusses data independence and the three-schema architecture in database systems. It explains that the schema is the overall structure or design of a database, while a subschema is a subset of the schema that inherits its properties and provides a window for users to view specific parts of the database. The three-schema architecture consists of the physical, logical, and view levels. The physical level deals with how data is stored, the logical level describes what data is stored and relationships, and the view level presents an external schema that users interact with. Data independence allows changes to schemas at one level without affecting higher levels, as seen through examples of logical and physical data independence.
The document summarizes key topics from a lecture on database systems, including:
1) Database languages have two parts - data definition languages (DDL) to define schemas and data manipulation languages (DML) to manipulate data.
2) A DBMS provides functions like data storage, retrieval, updating, security and integrity constraints.
3) A DBMS can operate in single-user or multi-user environments like teleprocessing, file-server, and client-server architectures.
The document discusses the objectives and components of the ANSI-SPARC three-level database architecture. The architecture includes an external, conceptual, and internal level. The external level defines users' views, the conceptual level defines entity relationships and constraints, and the internal level defines physical storage. Mappings allow translation between levels. The architecture aims to provide logical and physical data independence so changes to one level do not affect others.
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 provides an overview of the three level ANSI-SPARC architecture for database management systems. It describes the external, conceptual, and internal levels. The external level defines how users view the data, the conceptual level defines the overall data model, and the internal level defines the physical storage and implementation. The architecture provides data independence so changes to one level do not affect the others. It uses mappings between levels and multiple schemas to achieve this independence.
This document provides an overview of database systems and database management systems (DBMS). It discusses the limitations of file-based systems, how the database approach addresses these limitations, the typical components of a DBMS environment including hardware, software, data, procedures and personnel. A brief history of database systems is presented starting from the 1960s. The advantages of DBMSs like data consistency and sharing are outlined as well as some disadvantages such as complexity and costs.
The document discusses the three levels of abstraction in a database management system: the internal, conceptual, and external levels. The internal level describes the physical representation and storage of data. The conceptual level defines the logical structure and relationships of data in the database. The external level describes different views of the data that are relevant to users but hides implementation details.
The document discusses the three levels of database management system (DBMS) architecture: the internal level, conceptual level, and external level. The internal level defines how data is physically stored. The conceptual level describes the overall database structure and hides internal details. The external level presents different views of the database customized for specific user groups.
This document discusses database abstraction and users. It describes the three levels of abstraction in a database system according to the ANSI/SPARC standard: the external, conceptual, and internal levels. The external level includes user views, the conceptual level includes the overall database schema, and the internal level describes the physical storage structures. Mapping defines the correspondence between levels, and data independence means changes to lower levels do not affect higher levels. The document also lists different types of database users, including naive users, application programmers, sophisticated users, and the database administrator.
This document discusses data models and the three schema architecture of database management systems (DBMS). It describes the three levels of schemas in a DBMS - physical schema, conceptual/logical schema, and external schemas. The three schema architecture supports program-data independence and multiple user views of data by providing different levels of abstraction and independence between the schemas.
Data & Information, Drawbacks of File system, What is Database Management Systems, What is the need of DBMS, Examples of DBMS, Database Types, Applications of DBMS, Advantage of DBMS over file system, Disadvantages of DBMS, DBMS vs. File System
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 database models and database systems architecture. It describes hierarchical, network, relational, entity-relationship, and object-relational database models. It also discusses database management systems, how they are used to access and manipulate databases based on different data models, and how database systems are typically architected in mainframe, personal, and client-server configurations.
The document discusses key concepts related to databases and database management systems. It defines a database as a collection of organized data and a database management system as a computer program that allows for creating, accessing, managing and controlling databases. It describes three common data models - relational, network and hierarchical - and explains some fundamental database concepts like tables, keys, relations and normalization.
The document discusses database management systems (DBMS). It defines a database as a collection of related data and describes a DBMS as software that enables users to create, maintain and share databases. It provides an example of a university database with files for students, courses, grades and prerequisites. It outlines key characteristics of the database approach such as self-describing nature, insulation between programs and data, support of multiple views, and sharing of data.
The document discusses database management systems and their advantages over traditional file systems. It covers key concepts such as:
1) Databases organize data into tables with rows and columns to allow for easier querying and manipulation of data compared to file systems which store data in unstructured files.
2) Database management systems employ concepts like normalization, transactions, concurrency and security to maintain data integrity and consistency when multiple users are accessing the data simultaneously.
3) The logical design of a database is represented by its schema, while a database instance refers to the current state of the data stored in the database tables at a given time.
Week 2 Characteristics & Benefits of a Database & Types of Data Modelsoudesign
The document discusses characteristics and benefits of databases. It provides details on how databases can manipulate data through sorting, matching, linking, aggregating, skipping fields and calculating. It also describes common uses of databases such as storing data and metadata, supporting multiple users accessing the same data simultaneously, and managing access rights. Key characteristics of databases that are outlined include being self-describing through metadata, insulating data from programs, supporting multiple views, enabling data sharing, controlling redundancy, enforcing integrity constraints, restricting unauthorized access, and providing backup/recovery facilities.
Week 3 Classification of Database Management Systems & Data Modelingoudesign
The document discusses different types of database management systems and data models. It provides information on the following:
- The relational data model is the most commonly used model today and is supported by popular DBMS like Oracle, SQL Server, DB2, and MySQL.
- Other traditional models like hierarchical and network models are not commonly used now due to their complexity.
- The advantages of data models include increased effectiveness, reduced costs, simplicity, minimum redundancy, data integrity, independence, faster performance, reduced errors and risks.
- The types of data models discussed are hierarchical, network, relational, E-R and object oriented models. The characteristics and advantages/disadvantages of each model are described
The document defines key database concepts such as data, information, databases, data modeling, and database management systems (DBMS). It describes what a database is, the basic database structure, and the process of data modeling. It also discusses different types of DBMS software, database designs, and types of databases including relational, distributed, cloud, NoSQL, object-oriented, and graph databases. Additionally, it covers data manipulation using SQL and database advantages like redundancy control and disadvantages like costs.
The document provides an overview of database management systems and related concepts. It discusses database components like the data dictionary and data repository. It also covers different data models including hierarchical, network, and relational models. Key concepts covered include entities, attributes, relationships, schemas, and data abstraction which allows users to interact with data without knowing details of how it is structured and stored.
The document provides an overview of database systems concepts and architecture. It discusses three key topics: 1) modern DBMS packages use a client-server architecture with functionality distributed between client and server modules, 2) data models, schemas, and instances where a schema describes the database structure and an instance is the current data, and 3) the three-schema DBMS architecture with internal, conceptual, and external schemas to achieve data independence through mapping between levels.
This document discusses data independence and the three-schema architecture in database systems. It explains that the schema is the overall structure or design of a database, while a subschema is a subset of the schema that inherits its properties and provides a window for users to view specific parts of the database. The three-schema architecture consists of the physical, logical, and view levels. The physical level deals with how data is stored, the logical level describes what data is stored and relationships, and the view level presents an external schema that users interact with. Data independence allows changes to schemas at one level without affecting higher levels, as seen through examples of logical and physical data independence.
The document summarizes key topics from a lecture on database systems, including:
1) Database languages have two parts - data definition languages (DDL) to define schemas and data manipulation languages (DML) to manipulate data.
2) A DBMS provides functions like data storage, retrieval, updating, security and integrity constraints.
3) A DBMS can operate in single-user or multi-user environments like teleprocessing, file-server, and client-server architectures.
The document discusses the objectives and components of the ANSI-SPARC three-level database architecture. The architecture includes an external, conceptual, and internal level. The external level defines users' views, the conceptual level defines entity relationships and constraints, and the internal level defines physical storage. Mappings allow translation between levels. The architecture aims to provide logical and physical data independence so changes to one level do not affect others.
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 provides an overview of the three level ANSI-SPARC architecture for database management systems. It describes the external, conceptual, and internal levels. The external level defines how users view the data, the conceptual level defines the overall data model, and the internal level defines the physical storage and implementation. The architecture provides data independence so changes to one level do not affect the others. It uses mappings between levels and multiple schemas to achieve this independence.
This document provides an overview of database systems and database management systems (DBMS). It discusses the limitations of file-based systems, how the database approach addresses these limitations, the typical components of a DBMS environment including hardware, software, data, procedures and personnel. A brief history of database systems is presented starting from the 1960s. The advantages of DBMSs like data consistency and sharing are outlined as well as some disadvantages such as complexity and costs.
The document discusses the three levels of abstraction in a database management system: the internal, conceptual, and external levels. The internal level describes the physical representation and storage of data. The conceptual level defines the logical structure and relationships of data in the database. The external level describes different views of the data that are relevant to users but hides implementation details.
The document discusses the three levels of database management system (DBMS) architecture: the internal level, conceptual level, and external level. The internal level defines how data is physically stored. The conceptual level describes the overall database structure and hides internal details. The external level presents different views of the database customized for specific user groups.
This document discusses database abstraction and users. It describes the three levels of abstraction in a database system according to the ANSI/SPARC standard: the external, conceptual, and internal levels. The external level includes user views, the conceptual level includes the overall database schema, and the internal level describes the physical storage structures. Mapping defines the correspondence between levels, and data independence means changes to lower levels do not affect higher levels. The document also lists different types of database users, including naive users, application programmers, sophisticated users, and the database administrator.
This document discusses data models and the three schema architecture of database management systems (DBMS). It describes the three levels of schemas in a DBMS - physical schema, conceptual/logical schema, and external schemas. The three schema architecture supports program-data independence and multiple user views of data by providing different levels of abstraction and independence between the schemas.
Data & Information, Drawbacks of File system, What is Database Management Systems, What is the need of DBMS, Examples of DBMS, Database Types, Applications of DBMS, Advantage of DBMS over file system, Disadvantages of DBMS, DBMS vs. File System
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 database models and database systems architecture. It describes hierarchical, network, relational, entity-relationship, and object-relational database models. It also discusses database management systems, how they are used to access and manipulate databases based on different data models, and how database systems are typically architected in mainframe, personal, and client-server configurations.
The document discusses key concepts related to databases and database management systems. It defines a database as a collection of organized data and a database management system as a computer program that allows for creating, accessing, managing and controlling databases. It describes three common data models - relational, network and hierarchical - and explains some fundamental database concepts like tables, keys, relations and normalization.
The document discusses database management systems (DBMS). It defines a database as a collection of related data and describes a DBMS as software that enables users to create, maintain and share databases. It provides an example of a university database with files for students, courses, grades and prerequisites. It outlines key characteristics of the database approach such as self-describing nature, insulation between programs and data, support of multiple views, and sharing of data.
The document discusses database management systems and their advantages over traditional file systems. It covers key concepts such as:
1) Databases organize data into tables with rows and columns to allow for easier querying and manipulation of data compared to file systems which store data in unstructured files.
2) Database management systems employ concepts like normalization, transactions, concurrency and security to maintain data integrity and consistency when multiple users are accessing the data simultaneously.
3) The logical design of a database is represented by its schema, while a database instance refers to the current state of the data stored in the database tables at a given time.
Week 2 Characteristics & Benefits of a Database & Types of Data Modelsoudesign
The document discusses characteristics and benefits of databases. It provides details on how databases can manipulate data through sorting, matching, linking, aggregating, skipping fields and calculating. It also describes common uses of databases such as storing data and metadata, supporting multiple users accessing the same data simultaneously, and managing access rights. Key characteristics of databases that are outlined include being self-describing through metadata, insulating data from programs, supporting multiple views, enabling data sharing, controlling redundancy, enforcing integrity constraints, restricting unauthorized access, and providing backup/recovery facilities.
Week 3 Classification of Database Management Systems & Data Modelingoudesign
The document discusses different types of database management systems and data models. It provides information on the following:
- The relational data model is the most commonly used model today and is supported by popular DBMS like Oracle, SQL Server, DB2, and MySQL.
- Other traditional models like hierarchical and network models are not commonly used now due to their complexity.
- The advantages of data models include increased effectiveness, reduced costs, simplicity, minimum redundancy, data integrity, independence, faster performance, reduced errors and risks.
- The types of data models discussed are hierarchical, network, relational, E-R and object oriented models. The characteristics and advantages/disadvantages of each model are described
The document defines key database concepts such as data, information, databases, data modeling, and database management systems (DBMS). It describes what a database is, the basic database structure, and the process of data modeling. It also discusses different types of DBMS software, database designs, and types of databases including relational, distributed, cloud, NoSQL, object-oriented, and graph databases. Additionally, it covers data manipulation using SQL and database advantages like redundancy control and disadvantages like costs.
The document provides an overview of database management systems and related concepts. It discusses database components like the data dictionary and data repository. It also covers different data models including hierarchical, network, and relational models. Key concepts covered include entities, attributes, relationships, schemas, and data abstraction which allows users to interact with data without knowing details of how it is structured and stored.
The document provides an overview of database systems concepts and architecture. It discusses three key topics: 1) modern DBMS packages use a client-server architecture with functionality distributed between client and server modules, 2) data models, schemas, and instances where a schema describes the database structure and an instance is the current data, and 3) the three-schema DBMS architecture with internal, conceptual, and external schemas to achieve data independence through mapping between levels.
This document provides an overview of database systems and concepts. It discusses what a database is, common database uses, advantages of database systems over file-based systems, database management systems, data definition and manipulation languages, database architecture levels, relational database principles including entities, relationships, keys and normalization. It also covers database design processes such as requirements analysis, logical and conceptual data modeling, and entity-relationship modeling.
Database management system by Gursharan singhGursharan Singh
Database Management System (DBMS) organizes data into a database and provides tools to store, access, and analyze the data. It offers several advantages over traditional file-based data storage, including reduced data redundancy, improved data consistency, data sharing across users, and enhanced security. A typical DBMS uses a 3-tier architecture separating the user interface, application logic, and data storage tiers. It also employs standard data models like the entity-relationship and relational models to structure the database content.
A relational model of data for large shared data banksSammy Alvarez
This document introduces the relational model of data organization for large shared databases. It discusses inadequacies of existing tree-structured and network models, including ordering, indexing, and access path dependencies that impair data independence. The relational model represents data as mathematical n-ary relations and relationships between domains, providing independence from representation changes. It allows a clearer evaluation of existing systems and competing internal representations. The relational view forms a basis for treating issues like derivability, redundancy, and consistency in a sound way.
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.
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.
The document discusses fundamental database concepts including:
1) A database management system (DBMS) is software that maintains large amounts of structured data and allows secure, concurrent access by many users.
2) A DBMS provides capabilities like persistent data storage, concurrency control, redundancy control, and complex data relationships that are difficult to achieve without it.
3) Actors involved with databases include database administrators, designers, developers, and end users, as well as people who develop and maintain the underlying DBMS software.
The document describes a new graph-oriented database called the sones GraphDB. It enables efficient storage, management, and analysis of complex, highly interconnected data. Unlike relational databases, it can directly link different types of data without additional constructs. The database combines a high-performance graph-oriented data management system with an object-oriented storage solution to allow flexible, real-time analysis of structured, semi-structured, and unstructured data.
This document provides an overview of key concepts in database management systems including:
1. It discusses different data models including relational, entity-relationship, and object-oriented models.
2. It describes database system components like data definition language, data manipulation language, and transaction management.
3. It outlines different types of users that interact with database systems and roles like database administrators.
The document defines key concepts related to database management systems (DBMS) including what a DBMS is, the different levels of database architecture (external, conceptual, internal), data definition language (DDL), normalization, entity relationship (ER) modeling, and database normalization forms. It provides examples to illustrate database concepts and discusses the advantages of using a DBMS compared to traditional file management systems.
This document provides an overview of database management systems and related concepts. It discusses the three schema architecture including external, conceptual, and internal schemas. It also covers data models, data definition and manipulation languages, database administrators, keys such as primary keys and foreign keys, and integrity constraints including referential integrity, check constraints, and NOT NULL constraints. The goal of these concepts is to provide a structured and standardized way to define, manipulate, and manage database systems and data.
This document provides an overview of database management systems and the normalization process. It begins with definitions of data hierarchy and traditional file processing approaches. It then describes the benefits of a database approach using a DBMS, including features like querying, backup/replication, and security. Components of a DBMS are explained, including data definition languages, data manipulation languages, and the data dictionary. Common data models like hierarchical, network, relational, and object models are also summarized. The document concludes by defining key concepts in normalization like functional dependencies and normal forms, and providing an overview of the normalization process.
A database is a collection of related data organized and managed as a single unit. It provides logical and physical data independence through its layered architecture. The physical layer contains the data files, while the logical layer presents the data through common structures like tables. The external layer contains user views that access the database. The database management system handles data access and security across these layers.
This chapter introduces databases and database management systems (DBMS). It defines key concepts like data, database, and DBMS. It also provides examples of database applications and typical DBMS functionality like defining databases, loading data, and concurrent access. The chapter concludes by discussing the advantages and limitations of using a DBMS.
The document summarizes key concepts in distributed database systems including:
1) Distributed database architectures have external, conceptual, and internal views of data. Common architectures include client-server and peer-to-peer.
2) Distributed databases can be designed top-down using a global schema or bottom-up without a global schema.
3) Fragmentation and allocation distribute data across sites for performance and availability. Correct fragmentation follows completeness, reconstruction, and disjointness rules.
1. The document provides an overview of database management systems (DBMS), including their key characteristics, architecture, data models, schemas, and independence. A DBMS stores data in a way that makes it easier to retrieve, manipulate and generate information from it.
2. A typical 3-tier architecture separates a DBMS into 3 tiers - a database data tier, application middle tier, and user presentation tier. This makes the system highly modular and independent.
3. Common data models include the entity-relationship model and relational model. The entity-relationship model represents real-world entities and relationships, while the relational model stores data in tables and uses normalization.
The document provides an introduction to database management systems (DBMS) and database models. It defines key terms like data, database, DBMS, file system vs DBMS. It describes the evolution of DBMS from 1960 onwards and different database models like hierarchical, network and relational models. It also discusses the roles of different people who work with databases like database designers, administrators, application programmers and end users.
This document provides an overview of database management systems and related concepts. It discusses data hierarchy, traditional file processing, the database approach to data management, features and capabilities of database management systems, database schemas, components of database management systems, common data models including hierarchical, network, and relational models, and the process of data normalization.
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Computer Science Dissertation Literature Review Example
1. SAM
PLE
COMPUTER SCIENCE DISSERTATION LITERATURE REVIEW
Databases represent a high level of data work compared to classical programming
languages. It is about technology that was created with the intent to eliminate the
weaknesses of traditional "automatic data processing" from the 60s and 70s of the 20th
century. This technology has provided greater productivity, quality and reliability in
deploying applications that reduce storage and retrieval of data on the computer. The
database is a set of interconnected data stored in the external memory of the computer
(Date, 1999). Data is simultaneously available to various users and application programs.
Adding, changing, deleting, and retrieving data is performed through a common
software. Users and applications do not need to know the details of the physical display
of data, but are referring to the logical structure of the database. The Data Base
Management System (DBMS) is the server of the database. It shapes the physical display
of the database according to the requested logical structure. Also, it performs on behalf
of clients all data operations. Further, he is able to support various bases, each of which
can have his own logical structure, but in accordance with the same model. It also takes
care of data security and automates administrative tasks with the database. Database
data are logically organized according to some data model. The data model is a set of
rules that determine the logical structure of the database. The model is the basis for the
design, design and implementation of the base. The recent DBMSs have usually
supported one of the following models (Korth & Silberschatz, 2001): Relational model -
based on the mathematical notion of the relation. Both data and data links are displayed
in "rectangular" tables; Move model - the base is handled with a directed graph. The
nodes are types of records, and the arches define links between the types of records;
Hierarchical model - special case of network. The base is handled by a single tree or set
of trees. The nodes are types of records, and the hierarchical relationship "super-
subordinated" expresses links between the types of records; Object model - inspired by
DATABASES
2. object-oriented programming languages. The base is a set of permanently stored
objects that consist of their internal data and "methods" (operations) for handling these
data (Ramakrishnan, 1998). Each object belongs to a class. Between the classes, the
connections of inheritance, aggregation, or mutual use of operations are established.
Hierarchical and network model were mostly used in the midst of the 60s and 70s of
the 20th century. From the 1980s to the present day, the relational model prevails. The
expected transition to the object model has not happened so far, so today's database can
still mostly be identified with relational bases. We have mentioned that databases
represent a high level of data work compared to classical programming languages. This
higher level of work is perceived as the technology of the database seeks (and to a large
extent) succeeds in meeting the following goals (Abiteboul, Hull & Vianu, 1995): Physical
independence of data - the logical definition of the base of its real physical grade is
broken. So, if a physical city changes (for example, data is transcribed to other files on
other drives), it will not require any changes in existing apps; Logical independence of
data - a global logical definition of the entire database is extracted from the local logical
definition for one application. So, if the logical definition changes (for example, a new
record or link is introduced), it will not require any changes in existing apps. The local
logical definition is usually limited to the separation of some elements from the global
definition, with some simple transformation of these elements; Flexibility of access to
data - in older network and hierarchical databases, data access paths were pre-defined,
so the user could search the data only in the order that was envisaged at the time of
design and implementation of the database. Today, it is required that a user can freely
exchange data and establish links between data at their own discretion. This request
really only satisfies relational bases; Simultaneous access to data - the base must allow
most users to use at the same time same data. So these users should not interfere with
each other, and each of them should have the impression that I'm working with the
base; Protecting integrity - it is intended to automatically safeguard the accuracy and
consistency of the data, in situations where there are gaps in applications, and
controversial ongoing activities of the user; Possibility of recovery after failure - there
must be a reliable database protection in case of hardware failure or faults in system
software work; No protection from unauthorized use - there must be a possibility to
limit the user's right to use the base, so that each user is governed by the authority that
he or she cannot do with the data; Satisfying access speed - data operations must take
place quickly enough, depending on the needs of a particular application. Access speeds
can be leveraged by choosing suitable physical data structures and by selecting suitable
search algorithms; Possibility of adjustment and control - a large database requires
constant attention: performance monitoring, physical parameters change, routine
storage of backup copies, regulation of user privileges. Also, the purpose of the base
changes over time, and the logical structure needs to be periodically adjusted. Such jobs
must be centralized. The responsible person is called the database administrator.
Administrators should have various tools and aids available.
COMPUTER SCIENCE DISSERTATION LITERATURE REVIEW/ DATABASES
3. The database architecture consists of three "layers" and inter-layer interfaces (Van
der Lans, 1999). The word is about three levels of abstraction. Physical level refers to
physical display and data allocation on external memory units. This is an aspect seen
only by system developers (those who developed DBMS). The same physical level can
be further subdivided into more sub-levels of abstraction, from quite specific paths and
cylinders to the disk, to somewhat abstract terms of the files and records we meet in
classical programming languages. The Storage Schedule describes how elements of the
logical definition of the database are mapped to physical devices. The global logic level
refers to the logical structure of the entire base. This is an aspect that is seen by the base
designer or its administrator. A logical definition log is called schema (English also
schema). The schema is a text or diagram that defines the logical structure of the
database, and is consistent with the default model. Therefore, all types of data and
connections are defined and defined in the same way, according to the rules of the used
model. Also, the scheme introduces limitations that safeguard the integrity of the data.
The local logic level refers to the logical prediction of the part of the database used by
an individual application. This is an aspect seen by a user or an application developer.
The log of a local logical definition is called a view (English view) or a sub-scheme. It is
a text or diagram that names and defines all local types of data and links between these
types, again in accordance with the rules of the used model. Also, a view is a mapping
that takes global data and links out of the local.
COMPUTER SCIENCE DISSERTATION LITERATURE REVIEW/ DATABASES
REFERENCES
Date, C. J. (1999). An Introduction to Database Systems, 7th Edition. Reading MA:
Addison-Wesley.
Korth, H. F. & Silberschatz, A. (2001). Database System Concepts, 4th Edition. New
York: McGraw-Hill.
Ramakrishnan R. (1998). Database Management Systems. New York: McGraw-Hill.
Abiteboul S., Hull R., Vianu V. (1995). Foundations of Databases. Reading MA:
Addison-Wesley.
Van der Lans R. F (1999). Introduction to SQL. Reading MA: Addison-Wesley.