This chapter discusses the fundamental concepts of DBMS like limitations of the traditional file processing systems, characteristics of the database approach, different types of databases and users, advantages and disadvantages of DBMS.
This document provides an overview of database management systems (DBMS). It defines a DBMS as a collection of data and applications used to access and manage that data. The document then briefly discusses the history of DBMS development from early hierarchical models to today's dominant relational model. It describes the key purposes of using a DBMS, including reducing data redundancy and improving data integrity, security and consistency. The document outlines the main components and architecture of a DBMS, including its internal, conceptual and external levels. It also covers the advantages and disadvantages of using a DBMS, as well as common DBMS languages like SQL.
The document provides an overview of database management systems (DBMS). It defines DBMS as software that creates, organizes, and manages databases. It discusses key DBMS concepts like data models, schemas, instances, and database languages. Components of a database system including users, software, hardware, and data are described. Popular DBMS examples like Oracle, SQL Server, and MS Access are listed along with common applications of DBMS in various industries.
This document discusses the interview process from both the interviewer and interviewee perspective. It covers interview preparation, types of interviews, stages of an interview, soft skills, appearance, frequently asked questions, dos and don'ts, and positive and negative approaches during an interview. The goal of an interview is to assess a candidate's qualifications, experience, and skills for a position through communication and interaction between the interviewer and interviewee. Proper preparation is key to making a good impression and highlighting one's strengths.
This document outlines topics related to data analytics including the definition of data analytics, the data analytics process, types of data analytics, steps of data analytics, tools used, trends in the field, techniques and methods, the importance of data analytics, skills required, and benefits. It defines data analytics as the science of analyzing raw data to make conclusions and explains that many analytics techniques and processes have been automated into algorithms. The importance of data analytics includes predicting customer trends, analyzing and interpreting data, increasing business productivity, and driving effective decision-making.
HTML is a markup language used to define the structure and layout of web pages. It uses tags like <h1> and <p> to mark headings and paragraphs. CSS is used to style and lay out HTML elements, using selectors, declarations, and properties to change things like colors and positioning. JavaScript can be added to HTML pages with <script> tags and is used to add interactive elements and dynamic behavior by manipulating HTML and responding to user input. It has data types like strings and numbers and control structures like if/else statements.
The document discusses the entity relationship (ER) model used for conceptual database design. It describes the key components of an ER diagram including entities represented as rectangles, attributes described as ovals, and relationships shown as diamonds. Different types of relationships are also defined such as one-to-one, one-to-many, many-to-one, and many-to-many. The ER model provides a way to design and visualize the entities, attributes, and relationships within a database in a simple diagram.
This document discusses algorithms and their analysis. It defines an algorithm as a step-by-step procedure to solve a problem or calculate a quantity. Algorithm analysis involves evaluating memory usage and time complexity. Asymptotics, such as Big-O notation, are used to formalize the growth rates of algorithms. Common sorting algorithms like insertion sort and quicksort are analyzed using recurrence relations to determine their time complexities as O(n^2) and O(nlogn), respectively.
Doubly linked lists allow navigation in both directions by linking each node to both the next and previous nodes. Each node contains data and pointers to the next and previous nodes. Operations like insertion and deletion are more complex than with singly linked lists since both next and previous pointers must be updated. However, elements can be easily accessed from either direction. Basic operations on doubly linked lists include insertion and deletion at the beginning, end, or at a specified position in the list by adjusting the relevant next and previous pointers.
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
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 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 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 active databases and how they differ from conventional passive databases. Active databases can monitor a database for predefined situations and trigger actions automatically in response. This is accomplished through the use of active rules embedded within the database. The document outlines the key components of active rules, including events, conditions, and actions. It also covers the execution model of active databases and how rules are evaluated and triggered at runtime. Examples are provided of how active databases and triggers can be used for tasks like maintaining derived data values and enforcing integrity constraints.
This document summarizes a student's research project on improving the performance of real-time distributed databases. It proposes a "user control distributed database model" to help manage overload transactions at runtime. The abstract introduces the topic and outlines the contents. The introduction provides background on distributed databases and the motivation for the student's work in developing an approach to reduce runtime errors during periods of high load. It summarizes some existing research on concurrency control in centralized databases.
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.
Normalization is a process used to organize data in a database. It involves breaking tables into smaller, more manageable pieces to reduce data redundancy and improve data integrity. There are several normal forms including 1NF, 2NF, 3NF, BCNF, 4NF and 5NF. The document provides examples of tables and how they can be decomposed into different normal forms to eliminate anomalies and redundancy through the creation of additional tables and establishing primary keys.
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.
Introduction to Database Management Systems: Structure, Applications, and Key...Mahmud Hasan Tanvir
Explore the essentials of Database Management Systems (DBMS), including fundamental concepts, key applications in various industries, and advantages like data integrity, security, and independence. This presentation delves into data models such as hierarchical, network, relational, and object-oriented models, with practical examples and a deep dive into the structure and functions of tables, records, fields, and keys.
A database management system (DBMS) is software that allows for the creation, management, and use of databases. A DBMS provides users and administrators with various tools and applications to store, organize, and access data. It allows for data to be easily retrieved, filtered, sorted, and updated efficiently. Some key components of a DBMS include the database users, the data itself, software and procedures, hardware, and database access languages. DBMSs are widely used in applications such as banking, universities, e-commerce, and more.
Database Management System IntroductionSmriti Jain
The document discusses key concepts in databases including:
- Data refers to raw facts and details, while entities are things that data describes with attributes.
- A record combines all details of an entity, files group related records, and a database collects logically related files and records.
- A database management system (DBMS) enables users to define, create and maintain databases and provides flexible data management.
- DBMS benefits include centralized data control, consistency, sharing, and independence from applications.
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 key concepts of the relational model and relational databases. It defines relations (tables) and their components like attributes, tuples, domains, and keys. It explains the properties of relations including distinct relation names, single values per cell, distinct attribute names, and domains. It describes the different types of keys like super keys, candidate keys, primary keys, foreign keys, and composite keys. It also covers integrity rules including entity integrity which requires each table to have a unique primary key, and referential integrity which requires foreign keys to match the primary keys in other tables they reference.
Whenever you make a list of anything – list of groceries to buy, books to borrow from the library, list of classmates, list of relatives or friends, list of phone numbers and so o – you are actually creating a database.
An example of a business manual database may consist of written records on a paper and stored in a filing cabinet. The documents usually organized in chronological order, alphabetical order and so on, for easier access, retrieval and use.
Computer database are those data or information stored in the computer. To arrange and organize records, computer databases rely on database software
Microsoft Access is an example of database software.
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.
1) The document discusses different types of database users and the role of the database administrator. There are four types of database users: naive users, application programmers, sophisticated users, and specialized users.
2) The database administrator is responsible for defining the database schema, storage structure, granting access authorizations, and performing routine maintenance like backups and monitoring performance.
3) The roles and responsibilities of each user type and the database administrator are outlined. Naive users interact through simple programs, application programmers create interfaces, sophisticated users use query languages, and specialized users build custom applications.
This document discusses association rule mining. Association rule mining finds frequent patterns, associations, correlations, or causal structures among items in transaction databases. The Apriori algorithm is commonly used to find frequent itemsets and generate association rules. It works by iteratively joining frequent itemsets from the previous pass to generate candidates, and then pruning the candidates that have infrequent subsets. Various techniques can improve the efficiency of Apriori, such as hashing to count itemsets and pruning transactions that don't contain frequent itemsets. Alternative approaches like FP-growth compress the database into a tree structure to avoid costly scans and candidate generation. The document also discusses mining multilevel, multidimensional, and quantitative association rules.
The document discusses databases and database management systems (DBMS). It defines a database as a collection of related data that can be processed to produce information. A DBMS stores data in a way that makes it easier to retrieve, manipulate, and generate information from the data. Some key characteristics of a DBMS include using real-world entities to design its architecture, storing data in relational tables, providing isolation of data from applications, supporting querying of data, and following ACID properties for transactions. A DBMS also allows for multi-user access, multiple views of data for different users, and security features to restrict data access. Typical users of a DBMS include administrators, designers, and end users.
The document discusses database management systems (DBMS). It defines key terms like database, DBMS, metadata, system catalog, data, and information. It explains the characteristics of the database approach, advantages of using a DBMS over traditional file systems, and implications of the database approach. It also outlines the roles of database administrators and other actors involved with databases. Finally, it discusses some disadvantages of DBMS and circumstances when a DBMS may not be necessary.
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
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 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 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 active databases and how they differ from conventional passive databases. Active databases can monitor a database for predefined situations and trigger actions automatically in response. This is accomplished through the use of active rules embedded within the database. The document outlines the key components of active rules, including events, conditions, and actions. It also covers the execution model of active databases and how rules are evaluated and triggered at runtime. Examples are provided of how active databases and triggers can be used for tasks like maintaining derived data values and enforcing integrity constraints.
This document summarizes a student's research project on improving the performance of real-time distributed databases. It proposes a "user control distributed database model" to help manage overload transactions at runtime. The abstract introduces the topic and outlines the contents. The introduction provides background on distributed databases and the motivation for the student's work in developing an approach to reduce runtime errors during periods of high load. It summarizes some existing research on concurrency control in centralized databases.
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.
Normalization is a process used to organize data in a database. It involves breaking tables into smaller, more manageable pieces to reduce data redundancy and improve data integrity. There are several normal forms including 1NF, 2NF, 3NF, BCNF, 4NF and 5NF. The document provides examples of tables and how they can be decomposed into different normal forms to eliminate anomalies and redundancy through the creation of additional tables and establishing primary keys.
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.
Introduction to Database Management Systems: Structure, Applications, and Key...Mahmud Hasan Tanvir
Explore the essentials of Database Management Systems (DBMS), including fundamental concepts, key applications in various industries, and advantages like data integrity, security, and independence. This presentation delves into data models such as hierarchical, network, relational, and object-oriented models, with practical examples and a deep dive into the structure and functions of tables, records, fields, and keys.
A database management system (DBMS) is software that allows for the creation, management, and use of databases. A DBMS provides users and administrators with various tools and applications to store, organize, and access data. It allows for data to be easily retrieved, filtered, sorted, and updated efficiently. Some key components of a DBMS include the database users, the data itself, software and procedures, hardware, and database access languages. DBMSs are widely used in applications such as banking, universities, e-commerce, and more.
Database Management System IntroductionSmriti Jain
The document discusses key concepts in databases including:
- Data refers to raw facts and details, while entities are things that data describes with attributes.
- A record combines all details of an entity, files group related records, and a database collects logically related files and records.
- A database management system (DBMS) enables users to define, create and maintain databases and provides flexible data management.
- DBMS benefits include centralized data control, consistency, sharing, and independence from applications.
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 key concepts of the relational model and relational databases. It defines relations (tables) and their components like attributes, tuples, domains, and keys. It explains the properties of relations including distinct relation names, single values per cell, distinct attribute names, and domains. It describes the different types of keys like super keys, candidate keys, primary keys, foreign keys, and composite keys. It also covers integrity rules including entity integrity which requires each table to have a unique primary key, and referential integrity which requires foreign keys to match the primary keys in other tables they reference.
Whenever you make a list of anything – list of groceries to buy, books to borrow from the library, list of classmates, list of relatives or friends, list of phone numbers and so o – you are actually creating a database.
An example of a business manual database may consist of written records on a paper and stored in a filing cabinet. The documents usually organized in chronological order, alphabetical order and so on, for easier access, retrieval and use.
Computer database are those data or information stored in the computer. To arrange and organize records, computer databases rely on database software
Microsoft Access is an example of database software.
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.
1) The document discusses different types of database users and the role of the database administrator. There are four types of database users: naive users, application programmers, sophisticated users, and specialized users.
2) The database administrator is responsible for defining the database schema, storage structure, granting access authorizations, and performing routine maintenance like backups and monitoring performance.
3) The roles and responsibilities of each user type and the database administrator are outlined. Naive users interact through simple programs, application programmers create interfaces, sophisticated users use query languages, and specialized users build custom applications.
This document discusses association rule mining. Association rule mining finds frequent patterns, associations, correlations, or causal structures among items in transaction databases. The Apriori algorithm is commonly used to find frequent itemsets and generate association rules. It works by iteratively joining frequent itemsets from the previous pass to generate candidates, and then pruning the candidates that have infrequent subsets. Various techniques can improve the efficiency of Apriori, such as hashing to count itemsets and pruning transactions that don't contain frequent itemsets. Alternative approaches like FP-growth compress the database into a tree structure to avoid costly scans and candidate generation. The document also discusses mining multilevel, multidimensional, and quantitative association rules.
The document discusses databases and database management systems (DBMS). It defines a database as a collection of related data that can be processed to produce information. A DBMS stores data in a way that makes it easier to retrieve, manipulate, and generate information from the data. Some key characteristics of a DBMS include using real-world entities to design its architecture, storing data in relational tables, providing isolation of data from applications, supporting querying of data, and following ACID properties for transactions. A DBMS also allows for multi-user access, multiple views of data for different users, and security features to restrict data access. Typical users of a DBMS include administrators, designers, and end users.
The document discusses database management systems (DBMS). It defines key terms like database, DBMS, metadata, system catalog, data, and information. It explains the characteristics of the database approach, advantages of using a DBMS over traditional file systems, and implications of the database approach. It also outlines the roles of database administrators and other actors involved with databases. Finally, it discusses some disadvantages of DBMS and circumstances when a DBMS may not be necessary.
The document provides an introduction to database management systems (DBMS). It discusses what a database is and how it differs from traditional file processing systems. Some key points include:
1) A DBMS includes a system catalog that describes the database structure and metadata, allowing for data abstraction and independence between programs and data.
2) A DBMS supports multiple views of the data to suit different user needs. It also allows for sharing and concurrent access to data through transaction processing.
3) Characteristics like data abstraction, independence of programs from data structure/storage details, and enforcement of standards make a DBMS more powerful than file processing systems for managing organizational data.
CS3270 - DATABASE SYSTEM - Lecture (1)Dilawar Khan
This document outlines the key topics to be covered in a database course, including: understanding database concepts and the relational model, learning SQL for data manipulation and definition, database design techniques like entity-relationship modeling and normalization, and hands-on experience with Microsoft SQL Server. The course objectives are to help students understand databases and DBMS systems, apply relational concepts and SQL, and be able to design database applications. The document also provides an introduction to databases by comparing traditional file-based systems with the database approach.
The document provides an introduction to databases and database management systems (DBMS). It discusses the limitations of traditional file-based data storage systems, including data duplication, separation, and incompatibility between files. It then describes how a DBMS addresses these issues through a centralized database that can be shared and accessed. Key components of a DBMS environment include hardware, software, data, procedures, and personnel to design, manage and use the database. Advantages of DBMS include data consistency and reduced redundancy, while disadvantages include increased complexity, costs and potential impact of failures.
The document discusses databases and database management systems. It provides examples of common database applications like banking, universities, sales, and airlines. It defines what a database is, the role of a database management system, and examples of DBMS software. It also compares the advantages and disadvantages of using a database system versus a traditional file system to store data. Key benefits of a DBMS include supporting complex queries, controlling redundancy and consistency, handling concurrent access from multiple users, and providing security and data recovery.
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.
Introduction to Database Management System.pdfbiswajit62002
This document discusses database management systems and business rules. It defines key terms like data, database, DBMS and describes their purposes. It explains different levels of data abstraction including physical, logical and view levels. It also defines business rules as statements that impose constraints on business processes. Examples of business rule types and characteristics of good rules are provided. Finally, sources of business rules and benefits of explicitly defining them are summarized.
This document provides an overview of database management systems (DBMS). It defines data and databases, and explains that a DBMS organizes data into tables and indexes to make it easily accessible. A DBMS offers advantages over file systems like reducing data redundancy, improving data sharing and concurrency, and enforcing data integrity. The document also describes the typical structure of a DBMS and roles of users like administrators, designers, and end users.
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.
CP 121 introduces database systems. The lecture covers file-based systems, the database approach, common database uses, users, DBMS components and functions, and advantages and disadvantages of databases. Key points include: File-based systems are limited but the database approach offers data sharing and consistency. A DBMS manages data storage, transactions, integrity, security and more. Database users include administrators, designers, developers and end users who access data through applications.
This document provides an outline for a course on databases and database users. It introduces key concepts about databases including what a database is, database properties, database management systems, actors involved with databases like administrators and designers, advantages of databases over file systems, and common database applications. The outline covers topics that will be taught like introduction to PHP and MySQL, how to code applications with databases, and how to perform common tasks with databases.
This document discusses database management systems (DBMS) and their components. It describes DBMS as a set of programs that allow for the storage and retrieval of data. It then discusses the key components of a DBMS including the physical, logical, and view levels of abstraction, data models, data independence, data definition and manipulation languages like SQL, and the roles of database administrators and users. The document provides an overview of the architecture and design of database systems.
This document provides information about a database management systems (DBMS) course offered by the Department of Computer Science & Engineering at Cambridge University. The course objectives are to provide a strong foundation in database concepts, practice SQL programming, demonstrate transactions and concurrency, and design database applications. Course outcomes include identifying and defining database objects, using SQL, designing simple databases, and developing applications. The course modules cover topics such as conceptual modeling, the relational model, SQL, normalization, transactions, and recovery protocols. Required textbooks are also listed.
The document provides an overview of databases and database management systems. It defines what a database is and provides examples. It discusses the objectives and purpose of databases, including controlling redundancy, ease of use, data independence, accuracy, recovery from failure, privacy and security. Key terms related to database design and structure are explained, such as tables, rows, indexes, primary keys and foreign keys. The document also covers data definition language, data manipulation language, SQL, users and types of databases. Factors to consider when selecting a database management system are outlined.
The document discusses database management systems (DBMS). It covers topics such as the introduction to databases, components of a DBMS, and applications of DBMS. It defines a DBMS as a system software used to create and manage databases. A DBMS provides users with tools to define, manipulate, retrieve, and manage data. It also discusses the different types of databases like hierarchical, network, relational, and object-oriented databases.
*What is DBMS
*Database System Applications
*The Evolution of a Database
*Drawbacks of File Management System / Purpose of Database Systems
*Advantages of DBMS
*Disadvantages of DBMS
*DBMS Architecture
*types of modules
*Three-Tier and n-Tier Architectures for Web Applications
*different level and types
*Data Abstraction
*Data Independence
*Database State or Snapshot
*Database Schema vs. Database State
*Categories of data models
*Different Users
*Database Languages
*Relational Model
*ER Model
*Object-based model
*Semi-structured data model
This document provides information on data base management systems and storage management. It defines key concepts such as data, databases, database systems, database management systems (DBMS), and storage. It describes different types of databases like operational databases and distributed databases. It also discusses database users such as administrators, designers, and end users. The document outlines important database concepts including transactions, ACID properties, storage management, and different types of storage.
Chapter-10 Transaction Processing and Error RecoveryKunal Anand
This chapter discusses the concept of concurrency in database systems. We talk about different concurrency control techniques along with error recovery.
This chapter deals with the importance of normalization in database management systems. We learn about the necessary criterion needed for normalization. We discuss different types of normal forms along with some sample examples.
In this chapter, we talk about basic concepts of relational database design. We talk about the concept of functional dependency, Armstrong's axioms, closures, and minimal cover.
Here, we talk about various relational algebra operations like select, project, union, intersection, minus, cartesian product, and join in database management systems.
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.
Introduction to ANN, McCulloch Pitts Neuron, Perceptron and its Learning
Algorithm, Sigmoid Neuron, Activation Functions: Tanh, ReLu Multi- layer Perceptron
Model – Introduction, learning parameters: Weight and Bias, Loss function: Mean
Square Error, Back Propagation Learning Convolutional Neural Network, Building
blocks of CNN, Transfer Learning, R-CNN,Auto encoders, LSTM Networks, Recent
Trends in Deep Learning.
PRIZ Academy - Functional Modeling In Action with PRIZ.pdfPRIZ Guru
This PRIZ Academy deck walks you step-by-step through Functional Modeling in Action, showing how Subject-Action-Object (SAO) analysis pinpoints critical functions, ranks harmful interactions, and guides fast, focused improvements. You’ll see:
Core SAO concepts and scoring logic
A wafer-breakage case study that turns theory into practice
A live PRIZ Platform demo that builds the model in minutes
Ideal for engineers, QA managers, and innovation leads who need clearer system insight and faster root-cause fixes. Dive in, map functions, and start improving what really matters.
Efficient Algorithms for Isogeny Computation on Hyperelliptic Curves: Their A...IJCNCJournal
We present efficient algorithms for computing isogenies between hyperelliptic curves, leveraging higher genus curves to enhance cryptographic protocols in the post-quantum context. Our algorithms reduce the computational complexity of isogeny computations from O(g4) to O(g3) operations for genus 2 curves, achieving significant efficiency gains over traditional elliptic curve methods. Detailed pseudocode and comprehensive complexity analyses demonstrate these improvements both theoretically and empirically. Additionally, we provide a thorough security analysis, including proofs of resistance to quantum attacks such as Shor's and Grover's algorithms. Our findings establish hyperelliptic isogeny-based cryptography as a promising candidate for secure and efficient post-quantum cryptographic systems.
This research is oriented towards exploring mode-wise corridor level travel-time estimation using Machine learning techniques such as Artificial Neural Network (ANN) and Support Vector Machine (SVM). Authors have considered buses (equipped with in-vehicle GPS) as the probe vehicles and attempted to calculate the travel-time of other modes such as cars along a stretch of arterial roads. The proposed study considers various influential factors that affect travel time such as road geometry, traffic parameters, location information from the GPS receiver and other spatiotemporal parameters that affect the travel-time. The study used a segment modeling method for segregating the data based on identified bus stop locations. A k-fold cross-validation technique was used for determining the optimum model parameters to be used in the ANN and SVM models. The developed models were tested on a study corridor of 59.48 km stretch in Mumbai, India. The data for this study were collected for a period of five days (Monday-Friday) during the morning peak period (from 8.00 am to 11.00 am). Evaluation scores such as MAPE (mean absolute percentage error), MAD (mean absolute deviation) and RMSE (root mean square error) were used for testing the performance of the models. The MAPE values for ANN and SVM models are 11.65 and 10.78 respectively. The developed model is further statistically validated using the Kolmogorov-Smirnov test. The results obtained from these tests proved that the proposed model is statistically valid.
Dear SICPA Team,
Please find attached a document outlining my professional background and experience.
I remain at your disposal should you have any questions or require further information.
Best regards,
Fabien Keller
In modern aerospace engineering, uncertainty is not an inconvenience — it is a defining feature. Lightweight structures, composite materials, and tight performance margins demand a deeper understanding of how variability in material properties, geometry, and boundary conditions affects dynamic response. This keynote presentation tackles the grand challenge: how can we model, quantify, and interpret uncertainty in structural dynamics while preserving physical insight?
This talk reflects over two decades of research at the intersection of structural mechanics, stochastic modelling, and computational dynamics. Rather than adopting black-box probabilistic methods that obscure interpretation, the approaches outlined here are rooted in engineering-first thinking — anchored in modal analysis, physical realism, and practical implementation within standard finite element frameworks.
The talk is structured around three major pillars:
1. Parametric Uncertainty via Random Eigenvalue Problems
* Analytical and asymptotic methods are introduced to compute statistics of natural frequencies and mode shapes.
* Key insight: eigenvalue sensitivity depends on spectral gaps — a critical factor for systems with clustered modes (e.g., turbine blades, panels).
2. Parametric Uncertainty in Dynamic Response using Modal Projection
* Spectral function-based representations are presented as a frequency-adaptive alternative to classical stochastic expansions.
* Efficient Galerkin projection techniques handle high-dimensional random fields while retaining mode-wise physical meaning.
3. Nonparametric Uncertainty using Random Matrix Theory
* When system parameters are unknown or unmeasurable, Wishart-distributed random matrices offer a principled way to encode uncertainty.
* A reduced-order implementation connects this theory to real-world systems — including experimental validations with vibrating plates and large-scale aerospace structures.
Across all topics, the focus is on reduced computational cost, physical interpretability, and direct applicability to aerospace problems.
The final section outlines current integration with FE tools (e.g., ANSYS, NASTRAN) and ongoing research into nonlinear extensions, digital twin frameworks, and uncertainty-informed design.
Whether you're a researcher, simulation engineer, or design analyst, this presentation offers a cohesive, physics-based roadmap to quantify what we don't know — and to do so responsibly.
Key words
Stochastic Dynamics, Structural Uncertainty, Aerospace Structures, Uncertainty Quantification, Random Matrix Theory, Modal Analysis, Spectral Methods, Engineering Mechanics, Finite Element Uncertainty, Wishart Distribution, Parametric Uncertainty, Nonparametric Modelling, Eigenvalue Problems, Reduced Order Modelling, ASME SSDM2025
Several studies have established that strength development in concrete is not only determined by the water/binder ratio, but it is also affected by the presence of other ingredients. With the increase in the number of concrete ingredients from the conventional four materials by addition of various types of admixtures (agricultural wastes, chemical, mineral and biological) to achieve a desired property, modelling its behavior has become more complex and challenging. Presented in this work is the possibility of adopting the Gene Expression Programming (GEP) algorithm to predict the compressive strength of concrete admixed with Ground Granulated Blast Furnace Slag (GGBFS) as Supplementary Cementitious Materials (SCMs). A set of data with satisfactory experimental results were obtained from literatures for the study. Result from the GEP algorithm was compared with that from stepwise regression analysis in order to appreciate the accuracy of GEP algorithm as compared to other data analysis program. With R-Square value and MSE of -0.94 and 5.15 respectively, The GEP algorithm proves to be more accurate in the modelling of concrete compressive strength.
2. 2
Chapter Outcome:
• After the completion of this chapter, the students
will be able to:
– Explain the limitations of traditional file processing
system.
– List out the characteristics of the database approach.
– Explain different types of database users.
– Classify different types of databases.
– Identify the advantages and disadvantages of DBMS.
– List the areas where DBMS should not be used.
3. 3
Organization of this Chapter:
• Introduction
• Data Processing
• Traditional data storage and its limitations
• Characteristics of the database approach
• Types of Database
• Database Users
• Advantages and Disadvantages of Database
approach
• When not to use a DBMS
4. Introduction
• Database and database systems are an essential part of life in a
modern society. Most of us encounter several activities on day
to day basis which involves database and database systems in
one or another way. Ex: Online shopping, Online ticket
booking, banking transactions, use of social media etc.
• The above examples are basically the traditional database
applications. However, with the rapid technological
advancements a range of exciting new database applications
have come into existence. For example, Geographical
Information System, multimedia databases like hotstar, netflix,
amazon prime, etc.
5. Data Processing
• Any raw or unprocessed fact can be referred to as “Data”.
Data in its raw form does not hold any importance.
• When the data is processed in order to extract some meaning
of any significance, it is referred to as “Information”.
• Data processing may involve several operations like data
collection, recording, sorting, classifying, retrieving,
calculating, summarizing, and communicating.
• Data Management focuses on generation, storage, and retrieval
of data.
6. Traditional Data Storage
• File processing system was an early attempt to computerize the
manual filing system that we are all familiar with.
• A file system is a method for storing and organizing computer
files and the data they contain, to make it easy to find and
access them.
• File systems may use a storage device such as a hard disk or
CD-ROM and involve maintaining the physical location of the
files.
• The manual filing system works well when the number of
items to be stored is small. It even works quite adequately
when there are large numbers of items and we have only to
store and retrieve them. However, the manual filing system
breaks down when we have to cross-reference or process the
information in the files.
7. Traditional File System
File System
Loan_Processing
(Application Program)
Fixed_Deposit_Processing
(Application Program)
Transaction_Processing
(Application Program)
Customer_Details.dat Customer_Loan.dat Customer_Fixed_Deposit.dat Customer_Transaction.dat
8. Limitations of Traditional File System
• Data Security
• Data Redundancy
• Data Isolation
• Data Inconsistency
• Program / Data Dependence
• Lack of Flexibility
• Incompatible file formats
• Concurrent Access Anomalies
9. Database Approach
Database (DB) :
• Computer based organized collection of interrelated data.
• Records & maintains end users data and meta data i.e. data
through which the end user data are integrated and managed.
• A database is designed, built and populated with data for a
specific purpose as it has an intended group of users.
• A database can be of any size and complexity based on the
requirement. For example, a database for a university, database
of e-commerce companies etc.
• A database may be generated and maintained manually, if the
size is small, or the same may be computerized.
10. Database Management System (DBMS)
• A Database Management System, DBMS, is a collection of
programs that enables user to create and maintain a database.
• It is an interface between end users and the DB.
• DBMS is a general purpose software system that facilitates the
process of defining, constructing, manipulating, and sharing
DB among various users and applications.
• How it works
– An application program accesses the DB by sending
queries to the DBMS.
– The query causes some data to be retrieved over which a
transaction will be performed.
– A transaction may cause some data to be read and some
data to be written into the DB.
12. An Example
• UNIVERSITY is a DB that maintains information concerned
to students, course, and grades in a university environment.
• Now, this DB can be organized in following files that stores
data records of same type.
– STUDENT file stores data on each student,
– COURSE file stores data on each course,
– SECTION file stores data on each section,
– GRADE file stores the grade that student receives.
• To define this DB, we must specify the structure of the records
of each file by specifying the different types of data element to
be stored in each record.
• Now, to create the UNIVERSITY database, we store data to
represent each student, course, section, and grade as a record
in the appropriate file.
13. Characteristics of DB Approach
• The main characteristics of the DB approach is as
below:
• Self describing:
• A DB also contains a complete definition along with the
database.
• This definition is stored in the DBMS catalogue which
contains information like structure of each file, its type,
storage format of each data item, and various constraints.
• This catalogue is known as “Meta-data”.
14. contd..
• Insulation between program and data, and data
abstraction:
• In traditional file system, since the structure of data file is
embedded in the application program, so any changes to
the structure of a file may require changing all programs
that access that file.
• By contrast, DBMS access programs do not require such
changes because the structure of the data file is stored in
the meta-data which is separate from the access programs.
This is known as program-data independence.
15. contd..
• Support of multiple views of data:
– A DB typically has many users, each of whom may require
a different view of DB. A multi user DBMS facilitates for
defining multiple views for variety of users.
• Sharing of data and multiuser transaction
processing:
– A multiuser DBMS must allow multiple users to access the
DB at the same time. This is essential if data for multiple
applications is to be integrated and maintained in a single
DB.
– DBMS must include concurrency control software to
ensure that several users trying to update the same data do
so in a controlled manner so that the result of the updates is
correct. Ex: Ticket booking system.
16. Types of Database
• Depending on the number of users accessing the DB,
it may be classified as below:
– Single-user:
• Supports only one user at a time.
• When used on a personal computer it is known as
“Desktop” DB system.
– Multi-user:
• Supports multiple user at the same time.
• When used by a relatively small group of users, it is
known as “Workgroup” DB system.
• When used by many users across globe, it is known as
“Enterprise” DB system
17. contd..
• Depending on the location of the DB, it may be
classified as below:
– Centralized:
• In this DB system, the data is located at one single
location.
– Distributed:
• It supports data located at several different sites.
• Here, the same DB is located at different servers at
different locations so that even if the original server
goes down; the data can be available to users from
another server.
18. Actors on the scene
– DB Administrators (DBA):
• In a DB environment, the primary resource is the DB
itself and the secondary resource is the DBMS and the
related software.
• Administring these resources is the responsibility of the
database administrator.
• The DBA is responsible for authorizing access to the DB,
coordinating and montitoring its use and acquiring
software and hardware as needed.
• DBA is also responsible for breach of security or poor
system response time.
• In large organizations, DBA is assisted by a team of
individuals in managing these responsibilities.
19. contd..
• DB Designers:
– The DB designers are responsible for identifying the data to
be stored in the database and also for choosing appropriate
structures to represent and store the data.
– They interact with all perspective users of DB in order to
understand their requirements so that they can create a
design that meets these requirements.
– DB designers may also be assigned some administration
related jobs after the design work is over.
20. contd..
• End Users: People who access the database for querying,
updating and generating reports are known as end users. End
users may be categorized as below:
– Casual end user: Occassional user with different
requirements every time. These include middle or high
level managers or occasional browsers.
– Naive end user: Sizeable portion of DB end users. Their
job includes constantly querying and updating the DB
using standard types of queries and updates, known as
canned transactions that have been carefully programmed
and tested.
21. contd..
– Sophisticated end user: It include engineers, scientists,
business analysts who thoroughly familiarize themselves
with the facilities of DBMS in order to implement their
application to meet their complex requirement.
– Standalone users: They maintain personal DB by using
ready made packages that provide easy to use menu based
or graphics based interfaces.
• Software Engineers:
– They determine the requirements of the end users,
especially naive end users and develop specifications for
canned transactions to meet these requirements.
– Application programmers implement these specifications as
program, then they test, debug, document and maintain
these canned transactions.
22. Workers behind the Scene
• In addition to the actors, others are associated with the design,
development, and operation of of DBMS software and system
environment. They are known as workers behind the scene.
– DBMS system developers and implementers
– Tool developers
– Operators and maintenance personnal.
23. Advantages of DBMS
• A DBMS have some significant advantages as mentioned
below:
– Controls redundancy
– Restricts unauthorized access
– Allows data sharing
– provides storage structure and search techniques for
efficient query processing
– provides backup and recovery
– supports multiple user interface
– Availability of up-to-date information
– Represents complex relationship among data.
24. Disadvantage of DBMS
• Increased cost and complexity
• Technical staff requirement
• Database failure
• Extra cost of hardware
• Large operational size
• Currency maintenance
25. When not to use DBMS
• Simple well defined database applications that are not
expected to change very frequently.
• Real time requirements for some program may not meet
because of DBMS overhead due to its high investment, for
providing security, concurrency control, recovery functions etc.
• No need of multiple user interface.
• Embedded system with limited storage capacity and its not
enough to get DBMS fit in.
• Small organizations