Database Management System from scratch - Part 1

Explore the entity-relationship model, defining entities, relationships, and attributes, illustrated with examples like employees and departments; learn to diagram ER diagrams and convert them to relational models.

Explore how entities like student and course form an ER diagram with attributes and the enrolls for relationship, then translate to tables and a relational model for a database.

Compare ER model and relational model, outlining ease of understanding versus detailed records, using a college example with student and course tables linked by an enrolls form.

Explore how attributes extend beyond entities to relationships, with examples like an employee works for a department and its shift timing as a relationship attribute, while focusing on entity attributes.

Classify attributes as simple or composite, and single valued or multi valued, and illustrate how to represent them in ER diagrams for an employee entity.

Differentiate stored attributes from derived attributes with an employee example. See how age is derived from year of birth using the current year, while YOB remains stored.

A complex attribute combines composite and multi-valued features. For example, an employee's address can have multiple values and be divided into door number, street number, and pin code.

Understand degree and cardinality ratio in database relationships, noting that in the 'works for' example, an employee relates to one department while a department may have many employees.

Explain how to compute the cardinality ratio between students and courses from the enrollment relationship, deriving N:M or N:1 based on max per-student and per-course counts.

Analyze total versus partial participation in a works for relationship, identifying how double lines indicate total participation and single lines indicate partial participation.

Analyze total versus partial participation in the student-course enrolls-for relationship, identifying that every student has at least one enrolled course and every course is taken by at least one student.

Explore types of relationships in database design by examining ER diagrams, including many-to-many, one-to-many, and one-to-one relationships, guided by maximum cardinality.

Discover recursive relationships in which the same entity appears on both sides, illustrated by employees managing other employees, and distinguish total versus partial participation.

Identify whether a relationship is one-to-one, many-to-one, or many-to-many in database design, using the employee–manager example to show a manager can oversee at most one employee.

Explore relational model basics, including relation (table), tuple (row), attribute or field (column), and domain, and distinguish between entity types and entities within a schema.

See how discrete mathematics and set theory underpin the relational model by defining relations as subsets of Cartesian products of attribute domains.

Explore degree of a relation, current state, and how insertions and deletions alter tuples, plus intention versus extension in schema and entities.

Explain that a relation is a set with no duplicates, and illustrate domain constraints and the use of null values for not applicable or doesn't exist cases.

Explains domain constraints in relational models, showing that attributes must take atomic values from defined domains, avoiding composite and multi-valued attributes, and converting them for flat file relational schemas.

Explore key constraints by showing that no two tuples can share the same values for all attributes, since a relation is a set of records and duplicates are forbidden.

Explore how a super key uniquely identifies a tuple using one or more attributes, and why every superset of a super key is also a super key.

Demonstrate how to identify a super key by ensuring distinct values across all tuples for chosen attributes, and explain that any superset of a super key remains a super key.

Distinguish super keys from keys by defining minimal super keys, and learn how deleting attributes tests minimality to identify a true key in a relation.

Explore how emp.id and name form super keys and their supersets, note that age and sex are not super keys due to duplicates, and recognize single-attribute super keys as keys.

Compare super keys, keys, candidate keys, and primary keys; identify candidate keys as possible identifiers and primary key as the selected key, illustrated by emp.id versus name.

The lecture shows that if ac is the only key, every super key must include ac, giving four super keys: ac, acb, acd, and acbd.

Explore counting super keys for a four-attribute relation, showing that every super key must include A and yields eight possible super keys using permutations and combinations.

Demonstrate that in a four-attribute relation where abc is the only key, all superkeys must include abc, yielding two superkeys: abc and abcd.

Explore key constraints in relational databases, defining domain constraints and primary, candidate, and super keys while enforcing no duplicate tuples and non-null primary keys, as every table has a key.

Explain entity integrity constraints, showing that a primary key must not contain nulls and must uniquely identify each tuple, preventing duplicates in the relation.

Explore how a foreign key enforces referential integrity by tying employee records to existing departments, restricting department ids to the department table, and ensuring department heads are valid company employees.

The lecture shows a manager name as a foreign key in the employee table. Foreign keys may reference non-primary attributes, but usually point to a primary key.

Explore how primary keys uniquely identify tuples and cannot be null, while foreign keys may reference other attributes and accept null values in relational databases.

Learn how referential integrity constraints enforce that a foreign key can only reference values of the referred attribute, and that the foreign and referred attribute names may differ.

Explore how insertion into relational tables may violate domain, key, entity integrity, and referential constraints, with examples like invalid ages, duplicate keys, null primary keys, and department references.

Learn how deleting a tuple affects database constraints: domain, key, and entity integrity stay intact, but referential integrity can be violated during deletion.

Explore how a DBMS enforces constraints during insert, delete, and update, and apply strategies like on delete cascade or on delete set null to preserve referential integrity.

Analyze on delete cascade by solving a problem where deleting (2,4) enforces referential integrity, cascading deletions of related tuples (5,2), (7,2), and (9,5) to preserve A and C.

Explore how referential integrity constraints between R and S react to operations; inserting into S or deleting from R can violate the foreign key referencing R's primary key.

Preserve Attr1 as the key and combine with any subset of the remaining attributes to form super keys, yielding 2^n-1 possibilities.

Count super keys for a relation using a venn diagram when Attr1 and Attr2 are keys, applying inclusion-exclusion and subtracting the overlap of 2^(n-2).

Learn to count super keys in a relation using a three-circle Venn diagram, applying formulas like 2^n-1, 2^n-2, and 2^n-3 to determine all possible keys.

Explore why (attr1, attr2) is a super key but not a key, and why attr1 as a key makes it a super key, highlighting minimal super keys.

Explore how to count super keys in a relation using a two-key Venn diagram, identify minimal super keys, and derive counts like 2^n-1, 2^n-2, and 2^n-3.

Count super keys on a Venn diagram by inclusion-exclusion, treating (Attr1,Attr2) and (Attr3,Attr4) as keys; use 2^n-2 per circle and 2^n-4 for the overlap to get the total.

convert an er diagram to a relational model by identifying entities and attributes, and using prime attributes as keys. split composite attributes into simple sub-attributes; the relational model avoids composites.

Convert a one-to-many ER relationship to a relational model by moving the primary key from the one side to the many side as a foreign key, avoiding multi-valued attributes.

Demonstrate converting a one-to-many ER relationship to a relational model by using a foreign key, avoiding multi-valued attributes, and choosing between two-table and three-table designs.

Learn to convert a one-to-one ER diagram relationship to a relational model by using foreign keys or a joint table, and understand primary keys and null values.

Explains converting a many-to-many relationship from an ER diagram to relational model by creating a junction table with both tables' primary keys as a composite primary key and foreign keys.

Choose primary key placement carefully in one-to-one relationships to minimize nulls and prioritize maximum cardinality over participation when possible. For many-to-many, create a new junction table to avoid multi-valued attributes.

Explore multivalued and composite attributes in the ER model, contrast with the relational model, and learn how to represent or remove them using employee phone numbers as an example.

Learn how to convert an ER diagram to a relational model by minimizing tables for one-to-many and many-to-many relationships, culminating in four tables.

Determine the maximum number of tables to represent an ER diagram in a relational model, modeling many-to-many relationships with additional tables and foreign keys, concluding five tables.

Examine a one-to-one, total-participation relation between department and department head, using the minimum tables, where each department has exactly one head and the tuple counts in both tables are equal.

Learn when a one-to-one, total participation ER diagram can be represented with the minimum number of tables by merging department and department head.

Identify weak versus strong entities: a weak entity has no prime attribute, while a strong entity has one, as shown in the ER diagram and relational model.

Examines how weak entities require total participation with a strong entity and a partial key, and demonstrates converting them to relational models using the strong key and a composite key.

Explore n-ary relationships that involve more than two entities and learn to represent them in the relational model with a new table containing the participating primary keys as foreign keys.

See how a weak entity lacking a primary key becomes uniquely identifiable through an identifying relationship with a strong entity, marked by double lines and total participation.

Review ER diagram notations: entities as rectangles, relationships as diamonds, attributes as ovals, with key attributes underlined, and multi-valued, composite attributes; weak entities use double shapes and identifying relationships.

determine the minimum number of tables required to represent the er diagram in a relational model; the caption shows three.

Move an attribute of a relationship to its related entity in a one-to-many ER model, using the primary key as a foreign key and avoiding multi-valued attributes.

Explore the one-to-one relationship by assigning either the foreign key or the primary key appropriately, ensuring at most one department per employee and vice versa.

Explore how to handle many-to-many relationships by creating a new table that contains the primary keys of both tables, avoiding multi-valued attributes.

Learn how to convert an er diagram to a relational model by using one-to-many rules, moving primary keys, and ensuring no multi-valued attributes.

Examine functional dependencies and their role in normalization by comparing how A determines B and how B determines A through concrete table examples.

Explore functional dependency with examples like A implies BC and AC implies B, showing how a unique left-hand side determines a single right-hand side value.

If the left-hand side A has distinct values, A implies right-hand side holds; with duplicates, A implies B may fail when a value of A maps to multiple B values.

Examine functional dependencies with table examples to show that AC implies BD does not hold, while AB implies C and AB implies CD due to AB being distinct.

Explore functional dependencies, including trivial functional dependencies where Y is a subset of X, and understand why trivial FD always holds.

Explore non-trivial functional dependency: determine X implies Y only when X and Y share no attributes; trivial dependencies always hold, while non-trivial ones may or may not hold.

Define a semi-trivial functional dependency as neither trivial nor non-trivial, with X ∩ Y ≠ pi, illustrated by Ab → AC; trivial FDs always hold, others may not.

Examine the equivalence of A implies BC, A implies B, and A implies C in a three-attribute relation, using propositional logic, proofs, and decomposition of functional dependencies.

Learn how to compute the closure set of an attribute in a relation with functional dependencies, using left-hand sides, transitivity, and decomposition to identify all attributes uniquely determined by A.

Explore the closure set of attributes like D, E, AB, and ABD. Learn how functional dependencies and decomposition determine what the closure includes.

Show how a closure like AB+ or C+ can include all attributes, making AB a superkey but not a key, while a single attribute that determines all is a key.

Compute closure sets for functional dependencies and determine superkeys using step-by-step checks of LHS and RHS, illustrated with CF, BG, AF, and BA examples.

Explore how closure operation helps determine all keys and their count in a relation, test equivalence of functional dependencies, and derive a minimal dependency set in database design.