What is Normalization in Database Management System (DBMS) ?
What is the history of the system of normalization?
Types of Normalizations,
and why this is needed all details in the presentation.
The document discusses database normalization. It begins with a brief history of normalization, introduced by Edgar Codd in 1970. It then defines database normalization as removing redundant data to improve storage efficiency, data integrity, and scalability. The document provides examples to illustrate the concepts of first, second, and third normal forms. It shows how a book database can be normalized by separating data into separate tables for authors, subjects, and books and defining relationships between the tables using primary and foreign keys. This normalization process addresses issues like redundant data, data integrity, and scalability.
Normalisation is a process that structures data in a relational database to minimize duplication and redundancy while preserving information. It aims to ensure data is structured efficiently and consistently through multiple forms. The stages of normalization include first normal form (1NF), second normal form (2NF), third normal form (3NF), Boyce-Codd normal form (BCNF), fourth normal form (4NF) and fifth normal form (5NF). Higher normal forms eliminate more types of dependencies to optimize the database structure.
The document discusses normalization in database design. Normalization is the process of organizing data to avoid redundancy and dependency. It involves splitting tables and restructuring relationships between tables. The document outlines various normal forms including 1NF, 2NF, 3NF, BCNF, 4NF and 5NF and provides examples to illustrate how to normalize tables to conform to each form.
Normalization is the process of removing redundant data from your tables to improve storage efficiency, data integrity, and scalability.
Normalization generally involves splitting existing tables into multiple ones, which must be re-joined or linked each time a query is issued.
Why normalization?
The relation derived from the user view or data store will most likely be unnormalized.
The problem usually happens when an existing system uses unstructured file, e.g. in MS Excel.
Database normalization is the process of refining the data in accordance with a series of normal forms. This is done to reduce data redundancy and improve data integrity. This process divides large tables into small tables and links them using relationships.
Here is the link of full article: https://www.support.dbagenesis.com/post/database-normalization
The document discusses normalization, which is the process of converting complex data structures into simple structures to avoid data duplication. It describes the three main steps of normalization: first normal form (1NF), second normal form (2NF), and third normal form (3NF). The document provides examples of tables and explains how to normalize them by removing anomalies like repeating groups and partial/transitive dependencies between attributes. While there are several normal forms, 3NF is sufficient for most use cases and removes all transitive dependencies. Functional dependencies, which define relationships between attributes, are also discussed.
The document discusses database normalization. It begins with a brief history of normalization, introduced by Edgar Codd in 1970. It then defines database normalization as removing redundant data to improve storage efficiency, data integrity, and scalability. The document provides examples to illustrate the concepts of first, second, and third normal forms. It shows how a book database can be normalized by separating data into separate tables for authors, subjects, and books and defining relationships between the tables using primary and foreign keys. This normalization process addresses issues like redundant data, data integrity, and scalability.
Normalisation is a process that structures data in a relational database to minimize duplication and redundancy while preserving information. It aims to ensure data is structured efficiently and consistently through multiple forms. The stages of normalization include first normal form (1NF), second normal form (2NF), third normal form (3NF), Boyce-Codd normal form (BCNF), fourth normal form (4NF) and fifth normal form (5NF). Higher normal forms eliminate more types of dependencies to optimize the database structure.
The document discusses normalization in database design. Normalization is the process of organizing data to avoid redundancy and dependency. It involves splitting tables and restructuring relationships between tables. The document outlines various normal forms including 1NF, 2NF, 3NF, BCNF, 4NF and 5NF and provides examples to illustrate how to normalize tables to conform to each form.
Normalization is the process of removing redundant data from your tables to improve storage efficiency, data integrity, and scalability.
Normalization generally involves splitting existing tables into multiple ones, which must be re-joined or linked each time a query is issued.
Why normalization?
The relation derived from the user view or data store will most likely be unnormalized.
The problem usually happens when an existing system uses unstructured file, e.g. in MS Excel.
Database normalization is the process of refining the data in accordance with a series of normal forms. This is done to reduce data redundancy and improve data integrity. This process divides large tables into small tables and links them using relationships.
Here is the link of full article: https://www.support.dbagenesis.com/post/database-normalization
The document discusses normalization, which is the process of converting complex data structures into simple structures to avoid data duplication. It describes the three main steps of normalization: first normal form (1NF), second normal form (2NF), and third normal form (3NF). The document provides examples of tables and explains how to normalize them by removing anomalies like repeating groups and partial/transitive dependencies between attributes. While there are several normal forms, 3NF is sufficient for most use cases and removes all transitive dependencies. Functional dependencies, which define relationships between attributes, are also discussed.
The document discusses database normalization and different normal forms. It defines normalization as removing redundant data to improve storage efficiency and integrity. It outlines Edgar Codd's introduction of normalization and the first three normal forms he proposed: 1NF, 2NF, 3NF. It also discusses Boyce-Codd Normal Form and defines the differences between 3NF and BCNF. Examples are provided to illustrate the different normal forms.
The document provides an overview of databases and database design. It defines what a database is, what databases do, and the components of database systems and applications. It discusses the database design process, including identifying fields, tables, keys, and relationships between tables. The document also covers database modeling techniques, normalization to eliminate redundant or inefficient data storage, and functional dependencies as constraints on attribute values.
Database normalization is the process of structuring a relational database in accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity. It was first proposed by Edgar F. Codd as part of his relational model.
Agenda
What Is Normalization?
Why We Use Normalization?
Various Levels Of Normalization
Any Tools For Generate Normalization?
By Harsiddhi Thakkar
If you have any query
Contact me on : harsiddhithakkar94@gmail.com
Functional dependencies play a key role in database design and normalization. A functional dependency (FD) is a constraint that one attribute determines another. FDs have various definitions but generally mean that given the value of one attribute (left side), the value of another attribute (right side) is determined. Armstrong's axioms are used to derive implied FDs from a set of FDs. The closure of an attribute set or set of FDs finds all attributes/FDs logically implied. Normalization aims to eliminate anomalies and is assessed using normal forms like 1NF, 2NF, 3NF, BCNF which impose additional constraints on table designs.
This document discusses database normalization. It defines normalization as the process of organizing data in a database to minimize redundancy and dependency. The goals are to eliminate storing the same data in multiple tables and to only store related data together. The document describes the first three normal forms - first normal form eliminates replicated data and creates separate tables, second normal form creates separate tables for values that apply to multiple records, and third normal form eliminates fields that do not depend on the primary key. While third normal form addresses some issues, further normalization is needed to fully remove redundancy from databases.
Normalization is the process of organizing data in a database to minimize redundancy and dependency. It involves arranging the data into tables and establishing relationships between those tables according to certain forms. The three normal forms - first, second, and third normal form (1NF, 2NF, 3NF) - aim to eliminate different types of structural flaws and anomalies that can occur within the database design. Higher normal forms like BCNF and 4NF further reduce structural problems by removing non-key attributes and multi-valued dependencies.
Normalization is a process that organizes data to minimize redundancy and dependency. It divides tables to relate data without duplicating information. There are three common normal forms. The first normal form structures data into tables without repeating groups. The second normal form removes attributes not dependent on the primary key. The third normal form removes transitive dependencies so each non-key attribute depends directly on the primary key. Examples show how data can be normalized through multiple forms to eliminate anomalies and inconsistencies.
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.
The normal forms (NF) of relational database theory provide criteria for determining a table’s degree of vulnerability to logical inconsistencies and anomalies.
This document discusses database normalization through various normal forms. It defines key concepts like functional dependencies and full functional dependencies. It explains the objectives and rules of first, second, third normal forms and BCNF. First normal form requires each field to contain a single value. Second normal form requires fields to depend on the whole primary key. Third normal form and BCNF further eliminate transitive dependencies. The document provides examples to illustrate normalization and resolving anomalies through decomposition. It also introduces multi-valued dependencies and fourth normal form.
The document discusses database normalization. It defines normalization as a process of evaluating and correcting table structures to minimize data redundancies and anomalies. The normalization process involves converting tables to first, second, and third normal forms through removing partial and transitive dependencies. Higher normal forms like 3NF are better than 2NF and 1NF as they restrict relation formats and reduce vulnerabilities to update, delete, and insert anomalies.
The document discusses techniques used by a database management system (DBMS) to process, optimize, and execute high-level queries. It describes the phases of query processing which include syntax checking, translating the SQL query into an algebraic expression, optimization to choose an efficient execution plan, and running the optimized plan. Query optimization aims to minimize resources like disk I/O and CPU time by selecting the best execution strategy. Techniques for optimization include heuristic rules, cost-based methods, and semantic query optimization using constraints.
This document discusses database normalization and different normal forms including 1NF, 2NF, 3NF, and BCNF. It defines anomalies like insertion, update, and deletion anomalies that can occur when data is not normalized. Examples are provided to illustrate the different normal forms and how denormalizing data can lead to anomalies. The key aspects of each normal form like removing repeating groups (1NF), removing functional dependencies on non-prime attributes (2NF), and removing transitive dependencies (3NF, BCNF) are explained.
The document discusses normalization of database tables. It covers normal forms including 1NF, 2NF, 3NF, BCNF and 4NF. The process of normalization reduces data redundancies and helps eliminate data anomalies. Normalization is done concurrently with entity-relationship modeling to produce an effective database design. In some cases, denormalization may be needed to generate information more efficiently.
YouTube Link: https://youtu.be/ABwD8IYByfk
** MySQL DBA Certification Training: https://www.edureka.co/mysql-dba **
This Edureka PPT on 'What is Normalization' will help you understand the basic concepts of Normalization in SQL and Databases and how it helps in organizing data and data redundancy in SQL with examples.
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The document defines functional dependencies and describes how they constrain relationships between attributes in a database relation. A functional dependency X → Y means the Y attribute is functionally determined by the X attribute(s). The closure of a set of functional dependencies includes all dependencies that can be logically derived. Normalization aims to eliminate anomalies by decomposing relations based on their functional dependencies until a desired normal form is reached.
This chapter discusses advanced SQL features including relational set operators like UNION and INTERSECT, different types of joins, subqueries, functions, views, triggers, stored procedures, cursors, and embedded SQL. It covers topics like using subqueries in the SELECT, WHERE, HAVING and FROM clauses, correlated subqueries, date/string/numeric functions, updatable views, procedural language features in PL/SQL including triggers and stored procedures, and static versus dynamic embedded SQL.
The document discusses query optimization by describing how a database system estimates the cost of different query evaluation plans using statistical information about relations. It covers topics like estimating the size of selections, joins, aggregations and other operations to choose the lowest cost plan using transformations and equivalence rules.
Joins in SQL are used to combine data from two or more tables based on common columns between them. There are several types of joins, including inner joins, outer joins, and cross joins. Inner joins return rows that match between tables, outer joins return all rows including non-matching rows, and cross joins return the cartesian product between tables.
Normalization is the process of structuring a database to minimize duplicate data and reduce data anomalies. It involves breaking tables into smaller, more specific tables and linking them together. The goals of normalization are to minimize duplicate data, ensure data dependencies make logical sense, and simplify table designs to make the database more flexible, easier to maintain and less prone to anomalies. There are several normal forms that are commonly used including first normal form, second normal form, third normal form and Boyce-Codd normal form.
1) Database normalization is the process of organizing data in a database to minimize redundancy and dependency. It involves creating tables and relationships between tables according to specific rules.
2) There are five normal forms - first, second, third, fourth, and fifth normal form - that each aim to eliminate a particular type of undesirable dependency or redundancy. Achieving each subsequent normal form results in a better organized database structure.
3) The goals of normalization include removing duplication, reducing storage needs, simplifying data retrieval and queries, and defining more efficient and flexible data structures. It helps produce a higher quality, better designed database.
The document discusses database normalization and different normal forms. It defines normalization as removing redundant data to improve storage efficiency and integrity. It outlines Edgar Codd's introduction of normalization and the first three normal forms he proposed: 1NF, 2NF, 3NF. It also discusses Boyce-Codd Normal Form and defines the differences between 3NF and BCNF. Examples are provided to illustrate the different normal forms.
The document provides an overview of databases and database design. It defines what a database is, what databases do, and the components of database systems and applications. It discusses the database design process, including identifying fields, tables, keys, and relationships between tables. The document also covers database modeling techniques, normalization to eliminate redundant or inefficient data storage, and functional dependencies as constraints on attribute values.
Database normalization is the process of structuring a relational database in accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity. It was first proposed by Edgar F. Codd as part of his relational model.
Agenda
What Is Normalization?
Why We Use Normalization?
Various Levels Of Normalization
Any Tools For Generate Normalization?
By Harsiddhi Thakkar
If you have any query
Contact me on : harsiddhithakkar94@gmail.com
Functional dependencies play a key role in database design and normalization. A functional dependency (FD) is a constraint that one attribute determines another. FDs have various definitions but generally mean that given the value of one attribute (left side), the value of another attribute (right side) is determined. Armstrong's axioms are used to derive implied FDs from a set of FDs. The closure of an attribute set or set of FDs finds all attributes/FDs logically implied. Normalization aims to eliminate anomalies and is assessed using normal forms like 1NF, 2NF, 3NF, BCNF which impose additional constraints on table designs.
This document discusses database normalization. It defines normalization as the process of organizing data in a database to minimize redundancy and dependency. The goals are to eliminate storing the same data in multiple tables and to only store related data together. The document describes the first three normal forms - first normal form eliminates replicated data and creates separate tables, second normal form creates separate tables for values that apply to multiple records, and third normal form eliminates fields that do not depend on the primary key. While third normal form addresses some issues, further normalization is needed to fully remove redundancy from databases.
Normalization is the process of organizing data in a database to minimize redundancy and dependency. It involves arranging the data into tables and establishing relationships between those tables according to certain forms. The three normal forms - first, second, and third normal form (1NF, 2NF, 3NF) - aim to eliminate different types of structural flaws and anomalies that can occur within the database design. Higher normal forms like BCNF and 4NF further reduce structural problems by removing non-key attributes and multi-valued dependencies.
Normalization is a process that organizes data to minimize redundancy and dependency. It divides tables to relate data without duplicating information. There are three common normal forms. The first normal form structures data into tables without repeating groups. The second normal form removes attributes not dependent on the primary key. The third normal form removes transitive dependencies so each non-key attribute depends directly on the primary key. Examples show how data can be normalized through multiple forms to eliminate anomalies and inconsistencies.
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.
The normal forms (NF) of relational database theory provide criteria for determining a table’s degree of vulnerability to logical inconsistencies and anomalies.
This document discusses database normalization through various normal forms. It defines key concepts like functional dependencies and full functional dependencies. It explains the objectives and rules of first, second, third normal forms and BCNF. First normal form requires each field to contain a single value. Second normal form requires fields to depend on the whole primary key. Third normal form and BCNF further eliminate transitive dependencies. The document provides examples to illustrate normalization and resolving anomalies through decomposition. It also introduces multi-valued dependencies and fourth normal form.
The document discusses database normalization. It defines normalization as a process of evaluating and correcting table structures to minimize data redundancies and anomalies. The normalization process involves converting tables to first, second, and third normal forms through removing partial and transitive dependencies. Higher normal forms like 3NF are better than 2NF and 1NF as they restrict relation formats and reduce vulnerabilities to update, delete, and insert anomalies.
The document discusses techniques used by a database management system (DBMS) to process, optimize, and execute high-level queries. It describes the phases of query processing which include syntax checking, translating the SQL query into an algebraic expression, optimization to choose an efficient execution plan, and running the optimized plan. Query optimization aims to minimize resources like disk I/O and CPU time by selecting the best execution strategy. Techniques for optimization include heuristic rules, cost-based methods, and semantic query optimization using constraints.
This document discusses database normalization and different normal forms including 1NF, 2NF, 3NF, and BCNF. It defines anomalies like insertion, update, and deletion anomalies that can occur when data is not normalized. Examples are provided to illustrate the different normal forms and how denormalizing data can lead to anomalies. The key aspects of each normal form like removing repeating groups (1NF), removing functional dependencies on non-prime attributes (2NF), and removing transitive dependencies (3NF, BCNF) are explained.
The document discusses normalization of database tables. It covers normal forms including 1NF, 2NF, 3NF, BCNF and 4NF. The process of normalization reduces data redundancies and helps eliminate data anomalies. Normalization is done concurrently with entity-relationship modeling to produce an effective database design. In some cases, denormalization may be needed to generate information more efficiently.
YouTube Link: https://youtu.be/ABwD8IYByfk
** MySQL DBA Certification Training: https://www.edureka.co/mysql-dba **
This Edureka PPT on 'What is Normalization' will help you understand the basic concepts of Normalization in SQL and Databases and how it helps in organizing data and data redundancy in SQL with examples.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
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Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
The document defines functional dependencies and describes how they constrain relationships between attributes in a database relation. A functional dependency X → Y means the Y attribute is functionally determined by the X attribute(s). The closure of a set of functional dependencies includes all dependencies that can be logically derived. Normalization aims to eliminate anomalies by decomposing relations based on their functional dependencies until a desired normal form is reached.
This chapter discusses advanced SQL features including relational set operators like UNION and INTERSECT, different types of joins, subqueries, functions, views, triggers, stored procedures, cursors, and embedded SQL. It covers topics like using subqueries in the SELECT, WHERE, HAVING and FROM clauses, correlated subqueries, date/string/numeric functions, updatable views, procedural language features in PL/SQL including triggers and stored procedures, and static versus dynamic embedded SQL.
The document discusses query optimization by describing how a database system estimates the cost of different query evaluation plans using statistical information about relations. It covers topics like estimating the size of selections, joins, aggregations and other operations to choose the lowest cost plan using transformations and equivalence rules.
Joins in SQL are used to combine data from two or more tables based on common columns between them. There are several types of joins, including inner joins, outer joins, and cross joins. Inner joins return rows that match between tables, outer joins return all rows including non-matching rows, and cross joins return the cartesian product between tables.
Normalization is the process of structuring a database to minimize duplicate data and reduce data anomalies. It involves breaking tables into smaller, more specific tables and linking them together. The goals of normalization are to minimize duplicate data, ensure data dependencies make logical sense, and simplify table designs to make the database more flexible, easier to maintain and less prone to anomalies. There are several normal forms that are commonly used including first normal form, second normal form, third normal form and Boyce-Codd normal form.
1) Database normalization is the process of organizing data in a database to minimize redundancy and dependency. It involves creating tables and relationships between tables according to specific rules.
2) There are five normal forms - first, second, third, fourth, and fifth normal form - that each aim to eliminate a particular type of undesirable dependency or redundancy. Achieving each subsequent normal form results in a better organized database structure.
3) The goals of normalization include removing duplication, reducing storage needs, simplifying data retrieval and queries, and defining more efficient and flexible data structures. It helps produce a higher quality, better designed database.
Normalization presentation in Database Management System Km Anik
This document discusses database normalization. It begins by defining normalization as the process of removing redundant data from tables to improve storage efficiency, data integrity, and scalability. It then discusses the various normal forms (1NF, 2NF, 3NF, BCNF) and how normalization involves splitting tables into multiple tables linked by primary and foreign keys. As an example, it shows how to normalize a book database from a single table violating 1NF into separate tables for books, authors, and subjects linked with relationships.
Normalization is the process of organizing data in a database to minimize redundancy and dependency. It involves removing repeating groups, splitting tables to remove partial and transitive dependencies, and linking tables with primary and foreign keys. The three main steps are first normal form, which removes repeating groups; second normal form, which removes partial dependencies; and third normal form, which removes transitive dependencies. Normalization improves data storage and access, reduces anomalies, and helps maintain data integrity.
Dependencies in various topics like normalisation and its typesnsrChowdary1
This document discusses database normalization and its goals. It defines various normal forms including 1NF, 2NF, 3NF, BCNF, 4NF and 5NF. The key points are:
- Normalization aims to reduce data redundancy, improve consistency, and make a database easier to manage and update.
- BCNF requires that every determinant is a candidate key.
- Examples of normalization include splitting student enrollment data across multiple tables and moving employee address to a separate table.
- Self-assessment questions test the understanding of normalization goals and identifying BCNF.
Normalization is the process of organizing data in a database to minimize redundancy and dependency. It involves splitting tables and establishing relationships between them through primary and foreign keys. There are various normal forms that represent increasing levels of normalization, from 1NF to 3NF and BCNF. Normalizing data improves storage efficiency, data integrity, and scalability.
Third normal form (3NF) requires that there are no functional dependencies of non-key attributes on something other than a candidate key.
A table is in 3NF if all of the non-primary key attributes are mutually independent
That is, there are NO transitive dependencies
Normalization is the process of organizing data in a database to minimize redundancy and dependency. It involves separating large tables into smaller tables and linking them together through relationships. There are various normal forms that organize data in increasingly efficient ways, starting with first normal form, which structures data into tables without repeating groups. Higher normal forms like second and third further reduce redundancy between tables through techniques like separating one-to-many relationships.
Hamming Distance and Data Compression of 1-D CAcsitconf
This document summarizes an analysis of using Hamming distance to classify one-dimensional cellular automata rules and improve the statistical properties of certain rules for use in pseudo-random number generation. The analysis showed that Hamming distance can effectively distinguish between Wolfram's categories of rules and identify chaotic rules suitable for cryptographic applications. Applying von Neumann density correction and combining the output of two rules was found to significantly improve statistical test results, with one combination passing all Diehard tests.
Hamming Distance and Data Compression of 1-D CAcscpconf
In this paper an application of von Neumann correction technique to the output string of some chaotic rules of 1-D Cellular Automata that are unsuitable for cryptographic pseudo random number generation due to their non uniform distribution of the binary elements is presented.The one dimensional (1-D) Cellular Automata (CA) Rule space will be classified by the time run of Hamming Distance (HD). This has the advantage of determining the rules that have short cycle lengths and therefore deemed to be unsuitable for cryptographic pseudo random number generation. The data collected from evolution of chaotic rules that have long cycles are subjected to the original von Neumann density correction scheme as well as a new generalized scheme presented in this paper and tested for statistical testing fitness using Diehard battery of tests. Results show that significant improvement in the statistical tests are obtained when the output of a balanced chaotic rule are mutually exclusive ORed with the output of unbalanced
chaotic rule that have undergone von Neumann density correction.
The document discusses database normalization through 1st, 2nd, and 3rd normal forms. It defines database normalization as restructuring a database to eliminate redundancy, organize data efficiently, and reduce anomalies. The 1st normal form requires each table have a primary key and atomic values. The 2nd normal form removes redundant data across rows into separate tables linked by foreign keys. The 3rd normal form eliminates fields dependent on non-primary keys by moving them to other tables. Implementing these normal forms can decrease redundancy and increase database efficiency.
The document discusses database normalization through various normal forms including 1NF, 2NF, 3NF and BCNF. It provides examples of tables that violate different normal forms and how to convert them into the appropriate normal form by removing data redundancies and anomalies through decomposition. The goal of normalization is to organize data to avoid issues with data integrity like insertion, deletion and update anomalies.
A relational database management system (RDBMS) is a database management system that is based on the relational model. An RDBMS makes it possible for end users to create, read, update and delete data in a database systematically. Normalization is a technique used to organize data in a database to eliminate redundancy and improve data integrity. It involves decomposing tables and relations to their lowest sets of attributes. Some common types of normalization forms are first normal form, second normal form, third normal form and Boyce-Codd normal form.
The document provides an overview of the relational model for databases. The key points are:
- The relational model represents data in two-dimensional tables and organizes data into relational tables, presenting a logical view to users.
- Relational tables have properties like atomic values, unique rows, and insignificant column/row order. Relationships between tables are represented through primary and foreign keys.
- The relational model introduces concepts like normalization, relationships, keys, and operations that can be performed on relational tables and sets.
Relational Theory for Budding Einsteins -- LonestarPHP 2016Dave Stokes
This document provides an overview of relational database theory and normalization for developers. It defines key terms like relational databases, logical and physical data models, database schemas, and data normalization. It explains the concepts of first, second, third and Boyce-Codd normal forms and how to normalize data to these forms by removing redundant and unnecessary data through a multi-step process. The goal of normalization is to organize data to minimize duplication and ensure integrity. An example demonstrates normalizing a dog owner database from first to third normal form.
The document discusses database normalization and its goals of minimizing redundancy and reducing data anomalies. Normalization involves decomposing tables to eliminate non-key attributes that are dependent on only part of a table's candidate key. This involves putting data in first normal form, then second normal form by removing non-key attributes dependent on part of a candidate key, and third normal form by removing transitively dependent non-key attributes. The examples show how data can be normalized from non-normalized tables into tables in 1NF, 2NF and 3NF.
Data and functionality are two primary aspects of systems. Unfortunately, there is a mental gap between these two aspects. Therefore, nowadays many are looking for the corresponding research and development fields as quite distinct with different terminology, tools, problems, processes,methods and best practices. D. Gokila | S. BalaSubramani "Impact of Normalization in Future" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25128.pdfPaper URL: https://www.ijtsrd.com/engineering/computer-engineering/25128/impact-of-normalization-in-future/d-gokila
The document discusses database normalization. Normalization is the process of removing redundant data from tables to improve storage efficiency, data integrity, and scalability. Edgar Codd originally established three normal forms - 1NF, 2NF, and 3NF. The document uses an example book database table to demonstrate how it violates 1NF and 2NF, and how it can be normalized by splitting it into multiple tables for books, authors, subjects, and publishers to satisfy the normal forms.
The document discusses database normalization. It introduces the concept and defines normalization as organizing data to minimize duplication by isolating data across multiple tables and defining relationships between them. It also covers the different normal forms (1st, 2nd, 3rd, and Boyce-Codd), when to normalize data, and provides a real-world school data example to demonstrate normalization concepts.
This document summarizes a seminar presentation on the Internet of Things (IoT). It defines IoT as a system of interconnected computing devices, objects, and people that can collect and transfer data over a network without human interaction. It then describes how IoT works by using sensors to collect data, sharing it via the cloud and software to process it for users. Some key applications of IoT discussed are smart cities, agriculture, automation, and smart homes. Challenges of IoT include security issues, lack of regulations, and device compatibility. The future of IoT is predicted to include growth in new uses and more connected devices enabling digital transformation.
This project is intended for construction of a Smart Fingerprint based Door Lock System, by using R307 finger print reader optical sensor module attendance scanner. The project based on the Arduino Uno/Node MCU is used for the desired purpose. A standalone module is a machine which can automatically perform tasks. 12C OLED Display Module set in front of the gate and shows the data about who is check-in with a proper ID. The fingerprint sensor detects the finger ID and give access to the 12V Solenoid lock to open the door.
The project also includes Blynk IoT app which provides the remotely controlled accessed for the whole project using Wi-Fi connectivity.
The Internet of Things (IoT) is a network of interconnected physical devices that can communicate and share data without the need for human involvement.
It has been explicitly defined as a “Information Society Infrastructure” because IoT enables us to collect data from various mediums such as humans, animals, vehicles, and kitchen equipment Thus, any physical object that can be assigned an IP address to permit data transfer over a network can be integrated into an IoT system by integrating it with electronic hardware such as sensors, software, and networking gear.
Binary Search is a searching algorithm used in a sorted array by repeatedly dividing the search interval in half. The idea of binary search is to use the information that the array is sorted and reduce the time complexity to O(Log n).
Inter-process communication (IPC) is a mechanism that allows processes to communicate with each other and synchronize their actions. The communication between these processes can be seen as a method of co-operation between them. Processes can communicate with each other through both: Shared Memory.
The document discusses the Intel 8085 microprocessor. It provides details on the various components and functional units that make up the 8085 microprocessor, including the register section, arithmetic logic unit (ALU), and timing and control unit. It also includes block diagrams of the 8085 microprocessor and describes the functions of key components like the program counter, stack pointer, and temporary registers.
It's the 2nd part of our 'Device & Hardware' category presentations. In 1st part we're uploaded the slides about Samsung Galaxy S8+ and now we are uploading the brand new model of S series; it's S9+
In this short and simple presentation you will learn about the new features of Galaxy S9+, what's new in this model or which things make it to better than others?
This document provides an introduction to manufacturing processes. It defines manufacturing as the process of converting raw materials into products. There are two main types of manufacturing - based on technology, which involves machinery and labor, and based on economics, which adds value through processing. Manufacturing industries are divided into primary, secondary, and tertiary. The main types of manufacturing operations are project-based, job shop, batch, and mass production. Just-in-time manufacturing aims to deliver materials and parts just when needed to reduce waste. The kanban system uses cards to authorize and track production and movement of parts in a just-in-time system.
Information about Robotic Science, what is it, history of this invention, types of this science everything included here. Hope you like this presentation. Press like, and if you have any types of question the Comment please. Thank you!
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In this slide, we'll explore how to set up warehouses and locations in Odoo 17 Inventory. This will help us manage our stock effectively, track inventory levels, and streamline warehouse operations.
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বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
আমাদের সবার জন্য খুব খুব গুরুত্বপূর্ণ একটি বই ..বিসিএস, ব্যাংক, ইউনিভার্সিটি ভর্তি ও যে কোন প্রতিযোগিতা মূলক পরীক্ষার জন্য এর খুব ইম্পরট্যান্ট একটি বিষয় ...তাছাড়া বাংলাদেশের সাম্প্রতিক যে কোন ডাটা বা তথ্য এই বইতে পাবেন ...
তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
বিসিএস ও ব্যাংক এর লিখিত পরীক্ষা ...+এছাড়া মাধ্যমিক ও উচ্চমাধ্যমিকের স্টুডেন্টদের জন্য অনেক কাজে আসবে ...
Communicating effectively and consistently with students can help them feel at ease during their learning experience and provide the instructor with a communication trail to track the course's progress. This workshop will take you through constructing an engaging course container to facilitate effective communication.
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(𝐓𝐋𝐄 𝟏𝟎𝟎) (𝐋𝐞𝐬𝐬𝐨𝐧 𝟏)-𝐏𝐫𝐞𝐥𝐢𝐦𝐬
𝐃𝐢𝐬𝐜𝐮𝐬𝐬 𝐭𝐡𝐞 𝐄𝐏𝐏 𝐂𝐮𝐫𝐫𝐢𝐜𝐮𝐥𝐮𝐦 𝐢𝐧 𝐭𝐡𝐞 𝐏𝐡𝐢𝐥𝐢𝐩𝐩𝐢𝐧𝐞𝐬:
- Understand the goals and objectives of the Edukasyong Pantahanan at Pangkabuhayan (EPP) curriculum, recognizing its importance in fostering practical life skills and values among students. Students will also be able to identify the key components and subjects covered, such as agriculture, home economics, industrial arts, and information and communication technology.
𝐄𝐱𝐩𝐥𝐚𝐢𝐧 𝐭𝐡𝐞 𝐍𝐚𝐭𝐮𝐫𝐞 𝐚𝐧𝐝 𝐒𝐜𝐨𝐩𝐞 𝐨𝐟 𝐚𝐧 𝐄𝐧𝐭𝐫𝐞𝐩𝐫𝐞𝐧𝐞𝐮𝐫:
-Define entrepreneurship, distinguishing it from general business activities by emphasizing its focus on innovation, risk-taking, and value creation. Students will describe the characteristics and traits of successful entrepreneurs, including their roles and responsibilities, and discuss the broader economic and social impacts of entrepreneurial activities on both local and global scales.
3. DATABASE NORMALIZATION
Database normalization is the process of removing data
from your tables in to improve storage efficiency, data
integrity, and scalability.
Normalization generally involves splitting existing tables
into multiple ones, which must be re-joined or linked
each time a query is issued.
4. HISTORY
Edgar F. Codd first proposed the process of normalization
and what came to be known as the 1st normal form in his
paper A Relational Model of Data for Large Shared Data
Banks Code stated:
“There is, in fact, a very simple elimination procedure
which we shall call normalization. Through decomposition
non-simple domains are replaced by ‘domains whose
elements are atomic (non-decomposable) values’.”
5. TYPES OF NORMALIZATIONS
Edgar F. Codd originally established three normal forms:
1NF, 2NF and 3NF. There are now others that are
generally accepted, but 3NF is widely considered to be
sufficient for most applications.
6. Un-Normalized Relation:
Let's consider the STUDENT table with his ID, Name address and 2
subjects that he has opted for.
STUDENT
STUDENT_ID
STUDENT_NAME
ADDRESS
SUBJECT1
SUBJECT 2
STUDENT_ID STUDENT_NAME ADDRESS SUBJECT1 SUBJECT2
100 Rajat Guma History Geography
101 Raunak Barasat Mathematics Chemistry
102 Rishav Barasat Physics Biology
103 Tamal Habra English Computer
7. FIRST NORMAL FORM (1NF)
A table is said to be in First Normal Form (1NF) if and only
if each attribute of the relation is atomic. That is,
Each row in a table should be identified by primary key (a
unique column value or group of unique column values)
No rows of data should have repeating group of column
values.
8. Example of 1NF:
STUDENT
STUDENT_ID
STUDENT_NAME
ADDRESS
SUBJECT
STUDENT_ID STUDENT_NAME ADDRESS SUBJECT
100 Rajat Guma History
100 Rajat Guma Geography
101 Raunak Barasat Mathematics
101 Raunak Barasat Chemistry
102 Rishav Barasat Physics
103 Tamal Habra Computer
1NF
9. SECOND NORMAL FORM (2NF)
A table is said to be in 2NF if both the following conditions hold:
Table is in 1NF (First normal form)
No non-prime attribute is dependent on the proper subset of any
candidate key of table.
An attribute that is not part of any candidate key is known as non-
prime attribute.
10. Example of 2NF: STUDENT_ID ADDRESS
100 Guma
101 Barasat
102 Barasat
103 Habra
STUDENT_ID STUDENT_NAME SUBJECT
100 Rajat History
100 Rajat Geography
101 Raunak Mathematics
101 Raunak Chemistry
102 Rishav Physics
102 Rishav Biology
103 Tamal English
103 Tamal Computer
STUDENT_ADDRESS Table
STUDENTS_DETAILSTable
2NF
11. THIRD NORMAL FORM (3NF)
A table is said to be in the Third Normal Form when:
It is in the Second Normal form.
And, it doesn't have Transitive Dependency.
12. Example of 3NF:
STUDENT_ID STUDENT_NAME
100 Rajat
101 Raunak
102 Rishav
103 Tamal
STUDENT_ID SUBJECT
100 History
100 Geography
101 Mathematics
101 Chemistry
102 Physics
102 Biology
103 English
103 Computer
Student Table
SubjectTable
3NF
13. BOYCE CODD NORMAL FORM (BCNF)
It is an advance version of 3NF that’s why it is also referred
as 3.5NF.
BCNF is stricter than 3NF. A table complies with BCNF if it is
in 3NF and for every functional dependency X->Y, X should be
the super key of the table.
14. Example of BCNF: STUDENT_ID ADDRESS
100 Guma
101 Barasat
102 Barasat
103 HabraSTUDENT_ID STUDENT_NAME
100 Rajat
101 Raunak
102 Rishav
103 Tamal
STUDENT_ID SUBJECT
100 History
100 Geography
101 Mathematics
101 Chemistry
102 Physics
102 Biology
103 English
103 Computer
ADDRESS Table
STUDENT Table
SUBJECTTable
BCNF
15. OBJECTIVE OF NORMALIZATION
To free the collection of relations from undesirable
insertion, update and deletion dependencies.
To make the relational model more informative to users.
To make the collection of relations neutral to the query
statistics.