Database Management & Models

These slides cover the following concepts: ~ RDBMS vs DBMS ~ RDBMS structure ~ RDBMS basics for beginners ~ RELATIONAL DATABASE MANAGEMENT SYSTEM ~ DATA, SCHEMA, AND DATABASE ~ WHAT IS RDBMS? ~ FEATURES OF RDBMS ~ RELATIONSHIPS IN DATABASE ~ RULES OF RDBMS ~ ELEMENTS OF RDBMS ~ SQL COMMANDS ~ SQL CONSTRAINTS ~ COMMON SQL CONSTRAINTS ~ DATA DEFINITION LANGUAGE SCRIPT (DDL) ~ DATA MANIPULATION LANGUAGE SCRIPT (DML) ~ DATA CONTROL LANGUAGE SCRIPT (DCL) ~ PRIMARY KEY, FOREIGN KEY ~ EXAMPLE OF PRIMARY AND FOREIGN KEY ~ DBMS VS RDBMS ~ RDBMS NORMALIZATION ~ BENEFITS OF NORMALIZING ~ SQL JOINS ~ INNER JOIN ~ LEFT OUTER JOIN ~ RIGHT OUTER JOIN ~ FULL OUTER JOIN ~ CROSS JOIN ~ SELF JOIN

The document discusses deductive databases and how they differ from conventional databases. Deductive databases contain facts and rules that allow implicit facts to be deduced from the stored information. This reduces the amount of storage needed compared to explicitly storing all facts. Deductive databases use logic programming through languages like Datalog to specify rules that define virtual relations. The rules allow new facts to be inferred through an inference engine even if they are not explicitly represented.

Active databases' rules, it architectures, advantages and disadvantages along with applications have been covered in this presentation

Dbms architecture Three level architecture is also called ANSI/SPARC architecture or three schema architecture This framework is used for describing the structure of specific database systems (small systems may not support all aspects of the architecture) In this architecture the database schemas can be defined at three levels explained in next slide

This document provides an overview of relational database management systems (RDBMS). It defines key terms like database, database management system, and data models. It describes the characteristics of a modern DBMS like using real-world entities, normalization to reduce redundancy, and query languages. The document also outlines the components of a database system including users, applications, the DBMS software, and the database itself. It explains common database architectures like single-tier, two-tier, and three-tier designs. Finally, it introduces some historical data models used in database design like the entity-relationship model, relational model, hierarchical model, and network model.

A data model is a set of concepts that define the structure of data in a database. The three main types of data models are the hierarchical model, network model, and relational model. The hierarchical model uses a tree structure with parent-child relationships, while the network model allows many-to-many relationships but is more complex. The relational model - which underlies most modern databases - uses tables with rows and columns to represent data, and relationships are represented by values in columns.

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 describes the three level architecture of a database management system (DBMS): the external, conceptual, and internal levels. The external level defines different views of the database for users. The conceptual level defines the logical structure and relationships of the entire database. The internal level defines the physical storage and implementation of the data. The document also discusses logical and physical data independence, which refer to the ability to modify schemas at different levels without affecting higher levels.

The document provides an overview of database systems, including their purpose, components, and architecture. It describes how database systems offer solutions to problems with using file systems to store data by providing data independence, concurrency control, recovery from failures, and more. It also defines key concepts like data models, data definition and manipulation languages, transactions, storage management, database users, administrators, and the roles they play in overall database system structure.

The document discusses database management systems and data modeling. It begins by defining key terms like data, databases, database management systems, and data models. It then provides a brief history of database development from the 1960s to the 1980s. The rest of the document discusses database concepts in more detail, including components of a DBMS, types of database users, database administration responsibilities, data modeling techniques, and the evolution of different data models.

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 discusses XML databases and effective search engines. It describes how XML is a self-describing format that can store data in a portable way. While XML lacks features of traditional databases like efficient storage and indexing, XML databases address these issues. The document outlines how XML databases can store, search, retrieve and display XML documents and compares them to relational databases. It also provides examples of technologies and modules that can be used to parse, insert, query and synchronize XML documents with databases.

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.

The document discusses various aspects of database integrity and security including domain constraints, referential integrity, triggers, assertions, and authorization. Domain constraints ensure values inserted are valid. Referential integrity ensures relationships between relations are maintained. Triggers allow automatic execution of actions on data modifications. Assertions specify conditions that should always be true. Authorization controls user access to data and modifications. Views can provide secure access to restricted data.

Integrity constraints are rules that help maintain data quality and consistency in a database. The main types of integrity constraints are: 1. Domain constraints specify valid values and data types for attributes to restrict what data can be entered. 2. Entity constraints require that each row have a unique identifier and prevent null values in primary keys. 3. Referential integrity constraints maintain relationships between tables by preventing actions that would invalidate links between foreign and primary keys. 4. Cascade rules extend referential integrity by automatically propagating updates or deletes from a primary table to its related tables.

The document discusses 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.

This document provides an overview of object-oriented databases. It introduces object-oriented programming concepts like encapsulation, polymorphism and inheritance. It then discusses how object-oriented databases combine these concepts with database principles like ACID properties. Advantages include being integrated with programming languages and automatic method storage. Disadvantages include requiring object-oriented programming and high costs to convert data. The document also discusses the Object Query Language and provides an example query in OQL.

The document discusses several data models: hierarchical, network, relational, object-oriented, object-relational, deductive, and ER models. It provides descriptions of each model, including their key features, advantages, and disadvantages. The relational model is highlighted as the most popular currently due to its structural independence, conceptual simplicity, and powerful query capabilities using SQL. The ER model is also discussed as defining the conceptual view of databases through modeling real-world entities and relationships.

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 key database concepts, including: - Types of databases and database management systems (DBMS) functions - Data models like relational, hierarchical, and object-oriented - The three-schema architecture with conceptual, internal, and external schemas - Languages used to define and manipulate database structures and data - Centralized and client-server database system architectures

What is dimension modeling? , Difference between ER modeling and dimension modeling, What is a Dimension? , What is a Fact? Start Schema , Snow Flake Schema , Difference between Star and snow flake schema , Fact Table , Different types of facts Dimensional Tables, Fact less Fact Table , Confirmed Dimensions , Unconfirmed Dimensions , Junk Dimensions , Monster Dimensions , Degenerative Dimensions , What are slowly changing Dimensions? , Different types of SCD's,