The document describes setting up PostgreSQL database tables to store flight, fare, and seat data. It creates tables with the appropriate columns and constraints, and populates the flight table with randomly generated number, airline, and weekday values. It then performs sample queries on the flight table.
This document discusses database systems and normal forms, referencing examples from the textbook "Fundamentals of Database Systems" by R. Elmasri and S. B. Navathe. It covers topics related to database systems, including normal forms, functional dependencies, and transitive dependencies based on examples and explanations from the referenced textbook.
Assignment 1 of Database (MySQL & Sqlite3) Aey Unthika
Â
â Map your ER diagram to relations
â Create relations in sqlite
â Insert data ( >4GB? )
â Query ( > 30 sec?)
â Use the same data for your selected DBMS
The document discusses setting up database tables to track books being checked out from a library. It determines that there is a many-to-many relationship between customers and books, since a customer can check out multiple books and a single book can be checked out by multiple customers. To track which customer checks out each book, it recommends creating separate tables for checkouts and checkout_books, with the latter serving as a bridge table between books and checkouts.
This document describes a database project to create a student information system for Prajapathi Gothami Girls' College. A team of 8 students will build an ER diagram and database using MS SQL to store details of Grade 1 students like name, DOB, address, parent details, selected category. They will create views and an interface using C# for data entry and retrieval. The system aims to improve over the current manual process and can be used by other schools. It provides conceptual and physical database designs along with interface screenshots and download link for the project files.
The document discusses entity relationship diagrams and their components. An entity represents a category of data, and an attribute contains a subgroup of information within an entity. Relationship types in ER diagrams include mandatory, optional, many-to-one, one-to-many, and recursive. Many-to-many relationships should be avoided by dividing them into two one-to-many relationships using a joining table. Examples of different relationship types and resolving many-to-many relationships are provided.
Vanson Bourne Data Summary: Shadow IT - BDMsVanson Bourne
Â
The document provides an overview of the prevalence and reasons for 'shadow IT' among business decision-makers. Key findings indicate that 52% of departments source application software and 47% source servers outside of the IT department, with 71% expecting increased involvement in the next two years. Reasons cited for engaging in shadow IT include quicker procurement, better alignment with departmental needs, and enhanced productivity.
The document discusses the concept of data and databases, defining a database as an organized collection of data modeled to support information processes. It highlights the role of a Database Management System (DBMS) in storing, modifying, and extracting information, along with its advantages such as reduced redundancies and increased security. However, the document also addresses disadvantages including high costs and potential issues related to centralization.
The document describes a 7-step process for mapping an entity-relationship (ER) schema to a relational database schema. The steps include: 1) creating relations for regular entity types, 2) creating relations for weak entity types, 3) handling 1:1 relationships, 4) handling 1:N relationships, 5) handling M:N relationships, 6) handling multivalued attributes, and 7) handling n-ary relationships. An example company schema is used to illustrate the mapping.
This document provides an overview of entity-relationship (ER) modeling concepts for database design. It defines key ER modeling concepts like entities, attributes, entity types, relationships, relationship types, weak entities, and constraints. It also explains how to represent these concepts in ER diagrams. As an example, it analyzes the requirements for a sample COMPANY database and designs the initial entity types and relationship types that would be represented in an ER diagram for this database.
This document provides an overview of key concepts in entity-relationship modeling including entities, attributes, relationships, constraints, weak entities, and class hierarchies. It defines entities as objects in the real world that can be uniquely identified by a set of attributes. Relationships associate entities and can be one-to-one, one-to-many, many-to-one, or many-to-many. Constraints specify how entities can participate in relationships. Weak entities cannot be uniquely identified without attributes from a related strong entity. Class hierarchies allow entities to be classified into subclasses that inherit attributes.
The document discusses entity-relationship (ER) diagrams, detailing entities, attributes, relationships, and their types, including cardinality and constraints. It explains how to represent ER models and convert them into a relational data model, covering concepts like primary keys, foreign keys, and the distinction between weak and strong entities. The document serves as a comprehensive guide for understanding and implementing ER models in database design.
Unilever was formed in 1930 through the merger of Margarine Unie and Lever Brothers. It is now one of the world's largest suppliers of consumer goods, selling products in over 190 countries. The company's vision is to help people feel good, look good and get more out of life while inspiring small actions that benefit the world. Unilever has over 163,000 employees worldwide and generates sales through brands in home, personal care, and food/beverage products. The company focuses on innovation, people, marketplace performance, and continuous improvement to achieve sustainable profitable growth.
The document discusses how to transform an entity-relationship (ER) diagram into a set of relational tables by representing entities as tables, relationships as links between tables, and enforcing constraints like primary keys and foreign keys. Key steps include representing entities as tables with a primary key, relationships as links between tables with foreign keys, normalizing the tables, and merging the results. Constraints like primary keys must be unique and non-redundant, while foreign keys enforce referential integrity by linking to primary keys.
The document discusses how to convert ER diagrams to relational databases. It explains that each entity set maps to a table, while relationship sets can map to tables or be represented within other tables by adding attributes. It also covers handling special cases like one-to-one/many relationships, composite attributes, and specialization/aggregation. The document provides SQL commands for creating tables, adding constraints, and altering or dropping tables during the conversion process.
The document discusses various concepts for modeling entity-relationship diagrams and mapping them to relational database schemas. It covers modeling entities, relationships, attributes, keys, and converting specialized and generalized entity types. Specifically, it describes four approaches to mapping specialized entity types to relational schemas: (1) separate relations for supertype and subtypes, (2) separate relations only for subtypes, (3) a single relation with a type attribute, and (4) a single relation with multiple type attributes. It also discusses mapping categories and handling cases where supertypes have different keys.
The document discusses the concept of Entity Relationship (ER) diagrams, introduced by Peter Chen in 1976, which are used in database design to represent entities and their relationships. It covers topics such as entity sets, attributes, relationships, cardinality, weak entities, and self-relationships, offering examples and guidelines for designing ER diagrams for various applications. It also emphasizes best practices for creating efficient and effective ER diagrams in different scenarios.
This document discusses statistical learning approaches, including Naive Bayes classification. It provides an example of predicting the flavor of candy from different bags based on prior probabilities. It explains how Bayesian learning uses all hypotheses weighted by their probabilities to make predictions. The document also discusses Naive Bayes, which makes a strong independence assumption to simplify probability calculations for diagnosis problems using symptoms. It provides an example of using symptom probabilities learned from training data to determine the most likely diagnosis.
The document discusses enhanced entity-relationship (EER) modeling concepts used to more completely represent requirements of complex database applications. It introduces subclasses/superclasses to represent subgroupings of entities, with subclasses inheriting attributes and relationships from superclasses. Specialization defines subclasses of a superclass based on distinguishing characteristics, while generalization combines entity sets with common features into a higher-level superclass. Constraints on specialization/generalization include predicate-defined subclasses with membership conditions and attribute-defined specializations.
This document discusses the enhanced entity-relationship (EER) model. The EER model extends the basic ER model to represent more complex business data through the addition of supertypes and subtypes, generalization and specialization, constraints on supertype-subtype relationships, subtype discriminators, and entity clustering. Supertypes represent generic entity types that have subtypes as subgroups with both shared and distinct attributes. The EER model allows for more flexible modeling of real-world data.
Entity Relationship Diagram Templates by CreatelyCreately
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The document provides a list of entity relationship diagram templates for various systems including management, reservation, and enrollment. It suggests visiting specific websites for more templates and diagrams. The document aims to assist users in creating visual representations of database structures.
Assignment 1 of Database (MySQL & Sqlite3) Aey Unthika
Â
â Map your ER diagram to relations
â Create relations in sqlite
â Insert data ( >4GB? )
â Query ( > 30 sec?)
â Use the same data for your selected DBMS
The document discusses setting up database tables to track books being checked out from a library. It determines that there is a many-to-many relationship between customers and books, since a customer can check out multiple books and a single book can be checked out by multiple customers. To track which customer checks out each book, it recommends creating separate tables for checkouts and checkout_books, with the latter serving as a bridge table between books and checkouts.
This document describes a database project to create a student information system for Prajapathi Gothami Girls' College. A team of 8 students will build an ER diagram and database using MS SQL to store details of Grade 1 students like name, DOB, address, parent details, selected category. They will create views and an interface using C# for data entry and retrieval. The system aims to improve over the current manual process and can be used by other schools. It provides conceptual and physical database designs along with interface screenshots and download link for the project files.
The document discusses entity relationship diagrams and their components. An entity represents a category of data, and an attribute contains a subgroup of information within an entity. Relationship types in ER diagrams include mandatory, optional, many-to-one, one-to-many, and recursive. Many-to-many relationships should be avoided by dividing them into two one-to-many relationships using a joining table. Examples of different relationship types and resolving many-to-many relationships are provided.
Vanson Bourne Data Summary: Shadow IT - BDMsVanson Bourne
Â
The document provides an overview of the prevalence and reasons for 'shadow IT' among business decision-makers. Key findings indicate that 52% of departments source application software and 47% source servers outside of the IT department, with 71% expecting increased involvement in the next two years. Reasons cited for engaging in shadow IT include quicker procurement, better alignment with departmental needs, and enhanced productivity.
The document discusses the concept of data and databases, defining a database as an organized collection of data modeled to support information processes. It highlights the role of a Database Management System (DBMS) in storing, modifying, and extracting information, along with its advantages such as reduced redundancies and increased security. However, the document also addresses disadvantages including high costs and potential issues related to centralization.
The document describes a 7-step process for mapping an entity-relationship (ER) schema to a relational database schema. The steps include: 1) creating relations for regular entity types, 2) creating relations for weak entity types, 3) handling 1:1 relationships, 4) handling 1:N relationships, 5) handling M:N relationships, 6) handling multivalued attributes, and 7) handling n-ary relationships. An example company schema is used to illustrate the mapping.
This document provides an overview of entity-relationship (ER) modeling concepts for database design. It defines key ER modeling concepts like entities, attributes, entity types, relationships, relationship types, weak entities, and constraints. It also explains how to represent these concepts in ER diagrams. As an example, it analyzes the requirements for a sample COMPANY database and designs the initial entity types and relationship types that would be represented in an ER diagram for this database.
This document provides an overview of key concepts in entity-relationship modeling including entities, attributes, relationships, constraints, weak entities, and class hierarchies. It defines entities as objects in the real world that can be uniquely identified by a set of attributes. Relationships associate entities and can be one-to-one, one-to-many, many-to-one, or many-to-many. Constraints specify how entities can participate in relationships. Weak entities cannot be uniquely identified without attributes from a related strong entity. Class hierarchies allow entities to be classified into subclasses that inherit attributes.
The document discusses entity-relationship (ER) diagrams, detailing entities, attributes, relationships, and their types, including cardinality and constraints. It explains how to represent ER models and convert them into a relational data model, covering concepts like primary keys, foreign keys, and the distinction between weak and strong entities. The document serves as a comprehensive guide for understanding and implementing ER models in database design.
Unilever was formed in 1930 through the merger of Margarine Unie and Lever Brothers. It is now one of the world's largest suppliers of consumer goods, selling products in over 190 countries. The company's vision is to help people feel good, look good and get more out of life while inspiring small actions that benefit the world. Unilever has over 163,000 employees worldwide and generates sales through brands in home, personal care, and food/beverage products. The company focuses on innovation, people, marketplace performance, and continuous improvement to achieve sustainable profitable growth.
The document discusses how to transform an entity-relationship (ER) diagram into a set of relational tables by representing entities as tables, relationships as links between tables, and enforcing constraints like primary keys and foreign keys. Key steps include representing entities as tables with a primary key, relationships as links between tables with foreign keys, normalizing the tables, and merging the results. Constraints like primary keys must be unique and non-redundant, while foreign keys enforce referential integrity by linking to primary keys.
The document discusses how to convert ER diagrams to relational databases. It explains that each entity set maps to a table, while relationship sets can map to tables or be represented within other tables by adding attributes. It also covers handling special cases like one-to-one/many relationships, composite attributes, and specialization/aggregation. The document provides SQL commands for creating tables, adding constraints, and altering or dropping tables during the conversion process.
The document discusses various concepts for modeling entity-relationship diagrams and mapping them to relational database schemas. It covers modeling entities, relationships, attributes, keys, and converting specialized and generalized entity types. Specifically, it describes four approaches to mapping specialized entity types to relational schemas: (1) separate relations for supertype and subtypes, (2) separate relations only for subtypes, (3) a single relation with a type attribute, and (4) a single relation with multiple type attributes. It also discusses mapping categories and handling cases where supertypes have different keys.
The document discusses the concept of Entity Relationship (ER) diagrams, introduced by Peter Chen in 1976, which are used in database design to represent entities and their relationships. It covers topics such as entity sets, attributes, relationships, cardinality, weak entities, and self-relationships, offering examples and guidelines for designing ER diagrams for various applications. It also emphasizes best practices for creating efficient and effective ER diagrams in different scenarios.
This document discusses statistical learning approaches, including Naive Bayes classification. It provides an example of predicting the flavor of candy from different bags based on prior probabilities. It explains how Bayesian learning uses all hypotheses weighted by their probabilities to make predictions. The document also discusses Naive Bayes, which makes a strong independence assumption to simplify probability calculations for diagnosis problems using symptoms. It provides an example of using symptom probabilities learned from training data to determine the most likely diagnosis.
The document discusses enhanced entity-relationship (EER) modeling concepts used to more completely represent requirements of complex database applications. It introduces subclasses/superclasses to represent subgroupings of entities, with subclasses inheriting attributes and relationships from superclasses. Specialization defines subclasses of a superclass based on distinguishing characteristics, while generalization combines entity sets with common features into a higher-level superclass. Constraints on specialization/generalization include predicate-defined subclasses with membership conditions and attribute-defined specializations.
This document discusses the enhanced entity-relationship (EER) model. The EER model extends the basic ER model to represent more complex business data through the addition of supertypes and subtypes, generalization and specialization, constraints on supertype-subtype relationships, subtype discriminators, and entity clustering. Supertypes represent generic entity types that have subtypes as subgroups with both shared and distinct attributes. The EER model allows for more flexible modeling of real-world data.
Entity Relationship Diagram Templates by CreatelyCreately
Â
The document provides a list of entity relationship diagram templates for various systems including management, reservation, and enrollment. It suggests visiting specific websites for more templates and diagrams. The document aims to assist users in creating visual representations of database structures.
Assignmet 2 selectedtopic Topic in Computer EngineerAey Unthika
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Create simple IoT that connect to web service on cloud
āļ§āļąāļāļāļļāļāļŦāļ āļđāļĄāļīāđāļāļĒāđāļāđ dht11 āļŠāđāļāļāđāļēāđāļ§āļĨāļēāđāļĨāļ°āļāļļāļāļ āļđāļĄāļīāļāđāļēāļ Webservice āļāļķāđāļāļāļ°āļĄāļĩāļāļąāļāļāđāļāļąāļāļŠāđāļāļāđāļ§āļāđāļ§āļĨāļēāļāļąāļāļāļļāļāļąāļ āļŦāļĢāļ·āļāļāđāļ§āļāļŦāļāļķāđāļāļāļķāļāļāļĩāļāļāđāļ§āļāļŦāļāļķāđāļ āđāļĨāđāļ§āļāļ·āļāļāđāļēāđāļāđāļāļāļļāļāļŦāļ āļđāļĄāļīāļāļąāļāđāļ§āļĨāļēāđāļāļāđāļ§āļāđāļ§āļĨāļēāļāļąāđāļāđ
Assignmet1 selectedtopic Topic in Computer EngineerAey Unthika
Â
Start by finding web services using SOAP and WSDL on the Internet/Cloud
Try to use the web services with each group programming language
Then create web services for your group XML data
try to deploy your web services on the cloud
Each group presents about XML
Homework:
To try and use XML parser
G1 Python
G2 Lua
G3 Java
G4 Ruby
G5 Javascript
G6 C#
G1-G3 create XML data about books (10 for each member)
G4-G6 create XML data about movies (10 for each member)
9. TablesName Users Passenger Airport Staff Admins
Airport R CRU Full Control (CRUD)
Airplane_Type - CRU Full Control (CRUD)
Airplane - CRU Full Control (CRUD)
Leg_Instance - CRU Full Control (CRUD)
Seat R CRU Full Control (CRUD)
Flight_Leg R CRU Full Control (CRUD)
Flight R CRU Full Control (CRUD)
Fare R CRU Full Control (CRUD)
Can_Land - CRU Full Control (CRUD)
Discretionary
Access Control
R: Read, Retrieve C: Create U: Update, Modify D: Delete, Destroy
41. âĒ SQL INJECTION
ïSQL injection is a technique where malicious users can inject SQL commands into an SQL
statement, via web page input.
ïāđāļāđāļāđāļāļāļāļīāļāļāļĩāđāļāļđāđāļāļĢāļ°āļŠāļāļāđāļĢāđāļēāļĒāļŠāļēāļĄāļēāļĢāļāļāļĩāļāļāļēāļŠāļąāđāļāļāļāļ SQL āđāļāđāļēāđāļāđāļāļāđāļāļāļ§āļēāļĄ SQL āļāđāļēāļāļāļēāļāļŦāļāđāļēāđāļ§āļāđāļāļ
ïInjected SQL commands can alter SQL statement and compromise the security of a web
application.
ïāļāļēāļŠāļąāđāļ SQL āļāļĩāđāļāļđāļāļāļĩāļāļāļąāļ āļŠāļēāļĄāļēāļĢāļāļāļĢāļąāļāđāļāļĨāļĩāđāļĒāļāļāļēāļŠāļąāđāļ SQL āđāļĨāļ°āļĒāļāļĄāļĢāļąāļāļāļ§āļēāļĄāļāļĨāļāļāļ āļąāļĒāļāļāļāđāļ§āļ
āđāļāļāļāļīāđāļāļāļąāđāļ
42. âĒ Example of SQL Injection
āļāđāļāļāļāļģāļĢāļāđāļāļŦāļģāļāđāļāļĄāļđāļĨāļŠāļģāļĒāļāļģāļĢāļāļīāļ DMK
āļāļģāļŠāļąāđāļ SELECT * FROM Airport WHERE Airport_code = âDMKâ;
43. âĒ Example of SQL Injection
āđāļĨāļ°āļāđāļģāđāļāļīāđāļĄ or 1=1
āļāļģāļŠāļąāđāļ SELECT * FROM Airport WHERE Airport_code = âDMKâ or 1=1;
44. âĒ How to test SQL Injection
ïāļāļĢāļ§āļāļŠāļāļāđāļāļ·āđāļāļāļĩāđāļāđāļāļāļāļēāļĢāļŦāļēāļ§āđāļēāļāļēāļĢāļāđāļāļŦāļēāļŦāļĢāļ·āļāļāļķāļāļāđāļāļĄāļđāļĨ (Query) āļāļēāļāļāļēāļāđāļēāđāļāļŠ āļāļąāđāļāļāļđāļāļāđāļāļāļāļēāļĄāļāļĩāđ
āļāđāļāļāļāļēāļĢāļŦāļĢāļ·āļāđāļĄāđ
ïāļŠāđāļ§āļāļāļĩāđāļāđāļāļāļāļēāļĢāļāļĢāļ§āļāļŠāļāļāļāđāļāļ·āļāļŠāđāļ§āļāļāļĩāđāļĄāļĩāļāļāļīāļŠāļąāļĄāļāļąāļāļāđāļāļąāļāļāđāļāļĄāļđāļĨāđāļāļĒāļāļĢāļ
ïāđāļāđāļ āļŠāđāļ§āļāļāļāļāļĨāđāļāļāļāļīāļāļāļāļāļāļđāđāđāļāđ(Authentication) , āļŠāđāļ§āļāļāđāļāļŦāļēāļāđāļāļĄāļđāļĨ(Search Engines) , āļŠāđāļ§āļāļāļĩāđāļāļĢāļāļ
āļāļēāļāļ§āļāļŠāļīāļāļāđāļē āļŦāļĢāļ·āļāļĢāļēāļāļēāļāđāļēāļāđ (E-commerce)
45. âĒ Standard SQL Injection Testing
1. SQL Injection based on 1 = 1 is always TRUE
2. SQL Injection based on â=â is alsways TRUE
3. SQL Injection based on batched SQL statements
46. âĒ SQL Injection Based on ""="" is Always True
SELECT * FROM Airport WHERE Airport_code = âDMKâ or 1=1;