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Converting an Entity-Relationship (ER) diagram to a Relational Model is essential for database design, allowing the conceptual ER model to be translated into a physical structure for implementation in RDBMS like Oracle or MySQL. This article covers how to handle binary relationships with various cardinalities and participation constraints. We explore different scenarios such as 1:1 cardinality with total or partial participation. Case studies demonstrate how to convert entities and relationships into tables. The process ensures efficient database implementation and data integrity. For more details, check out the full article: <a href="https://www.geeksforgeeks.org/mapping-from-er-model-to-relational-model/">ER Model to Relational Model</a>.

Conversion ER Model to Relational Model - Part2

Converting an Entity-Relationship (ER) diagram to a Relational Model is essential for database design, allowing the conceptual ER model to be translated into a physical structure for implementation in RDBMS like Oracle or MySQL. This article covers how to handle binary relationships with various cardinalities and participation constraints. We explore different scenarios such as 1:1 cardinality with total or partial participation. Case studies demonstrate how to convert entities and relationships into tables. The process ensures efficient database implementation and data integrity. For more details, check out the full article: <a href="https://www.geeksforgeeks.org/mapping-from-er-model-to-relational-model/">ER Model to Relational Model</a>.

Conversion ER Model to Relational Model - Part1

An attribute in a Database Management System (DBMS) is a characteristic of an entity that describes its properties. It is represented as a column in a table, holding specific data values. A primary key is used to uniquely identify an entity, such as a student's roll number. Attributes help in organizing data efficiently for easy retrieval and manipulation. In an Entity-Relationship model, attributes are depicted in an elliptical shape, and can also be subdivided into additional attributes. For more details, check out the full article: <a href="https://www.geeksforgeeks.org/types-of-attributes-in-er-model/">Attributes in ER Model</a>.

Attributes in ER Model

The Relationship (ER) Model describes how entities are related within a database system. It represents entities and relationships, showing how entities interact through relationships like "enrolls" between students and courses. The ER model helps organize data and clarify associations between different data entities. For example, a student named Geeks may enroll in the Placement 100 course, where "enrolls" is the relationship. Understanding these relationships is essential for designing efficient database systems. For more details, check out the full article: <a href="https://www.geeksforgeeks.org/relationships-in-er-model/">Relationships in ER model</a>.

Relationship in ER Model

In database management, cardinality defines the number of times an entity participates in a relationship set. It helps determine how data in different tables are connected and ensures accurate data mapping. Participation constraints specify the minimum and maximum number of entities or relationships that can participate in a relationship, ensuring data integrity and consistency. These concepts are fundamental in building effective and efficient databases that model real-world scenarios accurately.&nbsp; For more details, check out the full article: <a href="https://www.geeksforgeeks.org/cardinality-in-dbms/">Cardinality</a> | <a href="https://www.geeksforgeeks.org/participation-constraints-in-dbms/">Participation</a>.

Cardinality and Participation in ER Diagram

In database management, super keys and candidate keys are essential for uniquely identifying records in a table. A super key is any set of attributes that can uniquely identify a record, but it may contain extra attributes not needed for identification. On the other hand, a candidate key is a minimal set of attributes that uniquely identifies a record, with no extra attributes. Understanding the difference between these keys is crucial for ensuring proper database design and data integrity. In this article, we explore how super keys and candidate keys function in database systems. For more details, check out the full article: &nbsp;<a href="https://www.geeksforgeeks.org/difference-between-super-key-and-candidate-key/">Super Key and Candidate Key</a>.

Find Super key and Candidate Key in DBMS

For more details, please go through -<a href="https://www.geeksforgeeks.org/dbms/difference-between-schema-and-instance-in-dbms/"> Difference between Schema and Instance in DBMS</a>

Lect-5 Database Schema representation (FINAL)

For more details, please go through - <a href="https://www.geeksforgeeks.org/dbms/dbms-architecture-2-level-3-level/">DBMS Architecture 1-level, 2-Level, 3-Level</a>

Lect-4: DBMS architectures (1-tier, 2-tier, 3-tier) (Final)

To minimize redundancy from a relation or group of relations we use normalization. Insertion, deletion, and update anomalies could result from relational redundancy. Therefore, it helps to reduce relational redundancy.&nbsp; We use second normal form to reduce the redundancies. Second Normal Form (2NF) is based on the concept of full functional dependency. A relation with a single-attribute primary key is automatically in at least 2NF.&nbsp; A relation that is not in 2NF may suffer from the update anomalies. To be in second normal form, a relation must be in first normal form and relation must not contain any partial dependency.&nbsp; A relation that is in First Normal Form and every non-primary-key attribute is fully functionally dependent on the primary key, then the relation is in Second Normal Form (2NF).&nbsp;2NF in Normalisation: <a href="https://www.geeksforgeeks.org/second-normal-form-2nf/">https://www.geeksforgeeks.org/second-normal-form-2nf/</a>

Second Normal Form (2NF) Normalisation in DBMS

In this video, we will be covering the functional dependencies &amp; its properties in DBMS. Let us first understand, what is functional dependencies In any relation, a functional dependency is said to be hold true If two tuples having the same value of one attribute also have the same value for another attribute.&nbsp; Functional Dependencies are domain dependent for a particular relation. A functional dependency set is a set of all the existing functional dependencies of a given relation.&nbsp; Set of all the attributes which are functionally reachable (determined) from attribute A is known as the closure of attribute A.&nbsp; It can be denoted by A+&nbsp; How to find attribute closure?&nbsp; Step:1 Find all the attributes determine by one attribute&nbsp; Step:2 Recursively find all the attributes set of the attributes determine by step 1 and add it to the result set&nbsp; Example: In a schema R(A,B,C,D,E) FD set is given as follows:&nbsp; {A → B, A → C, CD → E, B → D, E → A}&nbsp; Which of the following functional dependencies is implied by the above set?&nbsp; A. CD → AC&nbsp; B. BD → CD&nbsp; C. BC → CD&nbsp; D. AC → BC&nbsp; Solution:&nbsp; Option A holds true because CD determines the E, E determines A, and Hence this FD holds.&nbsp; Option B does not hold as B determines D and D determines no other attributes, so C cannot be determined.&nbsp; Option C holds true as B determines D.&nbsp; Option D holds true as A determines B.&nbsp; How to identify Candidate key or SuperKey?&nbsp; Step:1 Find attribute closure of the attributes/combination of attributes which contains all the attributes of a relation and make them as super key&nbsp; Step:2 If no subset of this attribute set can functionally determine all attributes of the relation, the set will be candidate key as well.&nbsp; Prime attributes: The attributes which is part of any of the candidate keys of a given relation then they are called as prime attributes.&nbsp; Non-Prime attributes: Attributes which are not prime attributes are known as non-prime attributes.&nbsp; Functional dependency: <a href="https://www.geeksforgeeks.org/functional-dependency-and-attribute-closure/">https://www.geeksforgeeks.org/functional-dependency-and-attribute-closure/</a>

Functional Dependency & its Properties in DBMS

In this video, we will be discussing Codd's rules in DBMS. What are Codd's Rules? Codd rules were given by E.F. Codd. These rules should be followed by relational table. Each relational table must follow each of the twelve rules given by E.F Codd. These rules are the basic building blocks of relational database, if these protocols are followed while designing the relational table during formation o fa relational database, then the resulting database would be efficient, optimized and have integrity, and will satisfy all the basic requirements of a relational database. There is a Foundation Rule, it says that the system should be able to manage database completely through relational capabilities, and it should be in tabular form.&nbsp; Codd's Rules: 1) Information Rule: Database stores different informations, and this information must be in a value of some rows or columns of the table.&nbsp; 2) Guaranteed Access Rule: In any relation undividable data must be accessible by the combination of corresponding relation name, primary key and name of corresponding attribute.&nbsp; 3) Systematic treatment of NULL values: Value of Primary key attributes can never be NULL, NULL value in database is missing, unknown, not applicable or inappropriate values.&nbsp; 4) Active Online Catalog: Database structure must be accessible by authorized users using queries. For this reason those databases must be stored in an online catalog.&nbsp; 5) Comprehensive Data Sublanguage Rule: If we want to access a database by a language supported for definition, manipulation and transaction management operation.&nbsp; 6) View Updating Rule: The system should be able to automatically update multiple views developed for diverse objectives.&nbsp; Insert, update and delete rule at Higher level: At each level of relations, the relational model should follow insert, delete, update, and other activities. Set operations must be supported as well.&nbsp; 7) Physical data independence: Any change in the physical location of a table should not impose modification at user view or application level.&nbsp; 8) Logical data independence: Any change in the logical data schema of a relation should not impose modification at application level.&nbsp; 9) Integrity Independence: Integrity constraints modified at lower level that is at the level of database should not impose change in application level.&nbsp; 10) Distribution Independence: A database that must function effectively even if it is stored in several places and is utilized by multiple end users&nbsp; 11) Non-Subversion Rule: Low level access to data should not be able to bypass integrity rule to change data. Watch this video till the end to understand these rules in detail with the help of examples Introduction of Relational Model and Codd Rules in DBMS <a href="https://www.geeksforgeeks.org/introduction-of-relational-model-and-codd-rules-in-dbms/">https://www.geeksforgeeks.org/introduction-of-relational-model-and-codd-rules-in-dbms/</a>

Codd's Rule in DBMS

In this video, we will be discussing the different types of joins in detail. But before that let us know why we need Join?Join needs two or more relations to perform an operation. Hence it is a binary operator that allows merging relations. The aim of using join is to combine the information from two or more tables (Relations).Joins are basically of two types, Inner Joins and Outer Joins, then these types are further classified into sub-types, which are as follows: 1) Inner Join: - Theta - Natural - Equi2) Outer Join: - Left - Right - FullInner Join: The result of this joins the tuples from both the relations which satisfy the given predicate. It can be thought of as a default join-type.Inner Join is of the following types: - Theta Join: Theta Join is used to combine two relations based on the predicate or condition. This condition is presented as theta. All comparison operators can be used by theta join. - Natural Join: Natural Join does not include any of the comparison operators. Here common attribute should be there between two relations that share a common domain as well. - EQUI Join: EQUI Join is used by putting the equivalence conditions in Theta join. Outer Join: This doesn’t need any common record. It preserves each record from relation even if there is no other matching record exists.Outer Join is of following types: - Left Outer Join: The result of this join is the tuples from the table on the left even if no matching tuples have been found in the table on the right. An unmatched record is found in the table on the right, NULL is returned. - Right Outer Join: The result of this join is the tuples from the table on the right even if no matching rows have been found in the table on the left. An unmatched record is found in the table on the left, NULL is returned. - Full Outer Join: In a Full Outer Join, all tuples from both relations are included in the result, despite of the matching condition.SQL Join (Inner left-right &amp; full joins)- <a href="https://www.geeksforgeeks.org/sql-join-set-1-inner-left-right-and-full-joins/">https://www.geeksforgeeks.org/sql-join-set-1-inner-left-right-and-full-joins/</a>

Types of Joins in DBMS

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