Data modeling is a process used to define and analyze data requirements needed to support the business processes within the scope of corresponding information systems in organizations.
The Relational Data Model and Relational Database Constraints Ch5 (Navathe 4t...Raj vardhan
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Ch5 (Navathe 4th edition)/ Ch7 (Navathe 3rd edition)
Example of STUDENT Relation(figure 5.1)
Functional dependencies in Database Management SystemKevin Jadiya
Slides attached here describes mainly Functional dependencies in database management system, how to find closure set of functional dependencies and in last how decomposition is done in any database tables
Data modeling is a process used to define and analyze data requirements needed to support the business processes within the scope of corresponding information systems in organizations.
The Relational Data Model and Relational Database Constraints Ch5 (Navathe 4t...Raj vardhan
The Relational Data Model and Relational Database Constraints
Ch5 (Navathe 4th edition)/ Ch7 (Navathe 3rd edition)
Example of STUDENT Relation(figure 5.1)
Functional dependencies in Database Management SystemKevin Jadiya
Slides attached here describes mainly Functional dependencies in database management system, how to find closure set of functional dependencies and in last how decomposition is done in any database tables
The Art Pastor's Guide to Sabbath | Steve ThomasonSteve Thomason
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How to Split Bills in the Odoo 17 POS ModuleCeline George
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The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Students, digital devices and success - Andreas Schleicher - 27 May 2024..pptxEduSkills OECD
Andreas Schleicher presents at the OECD webinar ‘Digital devices in schools: detrimental distraction or secret to success?’ on 27 May 2024. The presentation was based on findings from PISA 2022 results and the webinar helped launch the PISA in Focus ‘Managing screen time: How to protect and equip students against distraction’ https://www.oecd-ilibrary.org/education/managing-screen-time_7c225af4-en and the OECD Education Policy Perspective ‘Students, digital devices and success’ can be found here - https://oe.cd/il/5yV
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
Ethnobotany and Ethnopharmacology:
Ethnobotany in herbal drug evaluation,
Impact of Ethnobotany in traditional medicine,
New development in herbals,
Bio-prospecting tools for drug discovery,
Role of Ethnopharmacology in drug evaluation,
Reverse Pharmacology.
2. Objectives
• To illustrate how relationships between
entities are defined and refined.
• To know how relationships are incorporated
into the database design process.
• To describe how ERD components affect
database design and implementation
6. TABLE
A table is a collection (rows) of data
on a single related topic.
7. Difference between table and
database
Table
Database
A table is an object inside a
database
A database has tables of data,
a table is a collection (rows) of data
on a single related topic.
A database can have 10 or
thousands of tables
Ex: employee table
Contains only employees detail. But
it not contains inventory detail.
But DB is a collection of Employee
table as well as inventory table.
10. Why we need ER diagram
giving you image of how the tables
should connect
what fields are going to be on each
table
the tables connection, if many-tomany, one-to-many.
“ER diagrams are easy for non-technical
people to understand, and thus are
typically used by database designers
before the schema ever exists”
11. Entity
• An entity is something that exists by itself.
• Entity: Real-world object distinguishable from
other objects. An entity is described using a
set of attributes.
ssn
name
Employees
email
13. Entity set
• Entity Set: A collection of similar entities.
E.g., all employees.
–
–
–
All entities in an entity set have the same set of
attributes.
Each entity set has a key.
Each attribute has a domain.
14. Example
Association between
the instances of one
or more entity types
EntityName
Person, place, object, event or
concept about which data is to
be maintained
Verb Phrase
AttributeName
named property or
characteristic of an
entity
15. RELATIONSHIP
• Relationship: Association among two or
more entities. e.g., rose works in Pharmacy
department.
• Relationship Set:
Collection of similar
relationships.
• Same entity set could participate in different
relationship sets, or in different “roles” in same set.
16. Relationship Example
Associations between instances of one or more entity types that is of interest
Given a name that describes its function.
• relationship name is an active or a passive verb.
Relationship name:
writes
Author
Book
An author writes one or more books
A book can be written by one or more authors.
17. Degree of Relationships
• Degree: number of entity types that participate in a relationship
• Three cases
– Unary: between two instances of one entity type
– Binary: between the instances of two entity types
– Ternary: among the instances of three entity types
18. Attributes
• Example of entity types and associated attributes:
STUDENT: Student_ID, Student_Name, Home_Address, Phone_Number,
Major
19. Attribute types
– Simple and composite attributes.
– Single-valued and multi-valued attributes
• Example: multivalued attribute: phone_numbers
– Derived attributes
• Can be computed from other attributes
• Example: age, given date_of_birth
21. Referential Attributes
•
Make Reference to another instance in another table
Referential attribute: Ties the lecturer entity to another
entity that is department.
Name
Ali
105
LG
ali@a.com
Mary
106
IT
mary@a.com
John
107
ENG
john@a.com
Lim
Instance of Lecturer.
IdNum
DeptID
Email
108
IT
lim@a.com
22. Mapping Cardinality Constraints
• Express the number of entities to which another
entity can be associated via a relationship set.
• Most useful in describing binary relationship sets.
• For a binary relationship set the mapping
cardinality must be one of the following types:
–
–
–
–
One to one
One to many
Many to one
Many to many
23. Mapping Cardinalities
One to one
One to many
Note: Some elements in A and B may not be mapped to any
elements in the other set
24. Mapping Cardinalities
Many to one
Many to many
Note: Some elements in A and B may not be mapped to any
elements in the other set
25. • Key and key attributes:
KEY
– Key: a unique value for an entity
– Key attributes: a group of one or more attributes that uniquely
identify an entity in the entity set
• Super key, candidate key, and primary key
–
–
Super key: a set of attributes that allows to identify and entity
uniquely in the entity set
Candidate key: minimal super key
•
–
There can be many candidate keys
Primary key: a candidate key chosen by the designer
•
Denoted by underlining in ER attributes.
26. Key Constraints
• Consider Works_In: An employee can work in many
departments; a dept can have many employees.
• In contrast, each dept has at most one manager,
according to the key constraint on Manages.
27. Weak Entity Sets
• An entity set that does not have a primary key is
referred to as a weak entity set.
• The existence of a weak entity set depends on
the existence of a identifying entity set
– it must relate to the identifying entity set via a
total, one-to-many relationship set from the
identifying to the weak entity set
– Identifying relationship depicted using a double
diamond
• The discriminator (or partial key) of a weak
entity set is the set of attributes that
distinguishes among all the entities of a weak
entity set.
• The primary key of a weak entity set is formed
by the primary key of the strong entity set on
which the weak entity set is existence
dependent, plus the weak entity set’s
discriminator.
28. • In a relational database, a Weak Entity is an entity that
cannot be uniquely identified by its attributes alone;
therefore, it must use a foreign key in conjunction with
its attributes to create a primary key. The foreign key is
typically a primary key of an entity it is related to.
29.
30. Conceptual design
• Conceptual design: (ER Model is used at this
stage.)
• Process of describing the data, relationships between
the data, and the constraints on the data.
31. Entity-Relationship (ER) Diagram
• ER Modeling is a “top-down” approach to database
design.
• Entity Relationship (ER) Diagram
– A detailed, “logical representation” of the entities,
associations and data elements for an organization or
business
Notation uses three main constructs
– Data entities
– Relationships
– Attributes
35. Roles
• Entity sets of a relationship need not be distinct
• The labels “manager” and “worker” are called roles; they
specify how employee entities interact via the works_for
relationship set.
• Roles are indicated in E-R diagrams by labeling the lines that
connect diamonds to rectangles.
• Role labels are optional, and are used to clarify semantics of the
relationship
36. Cardinality and Connectivity
• Relationships can be classified as either
• one – to – one
• one – to – many
• many – to –many
Connectivity
• Cardinality : minimum and maximum number of
instances of Entity B that can (or must be) associated
with each instance of entity A.
37. Cardinality Constraints
• We express cardinality constraints by drawing
either a directed line ( ), signifying “one,” or
an undirected line (—), signifying “many,”
between the relationship set and the entity
set.
• One-to-one relationship:
– A customer is associated with at most one loan via
the relationship borrower
– A loan is associated with at most one customer via
borrower
38. One-To-Many Relationship
• In the one-to-many relationship a loan is
associated with at most one customer via
borrower, a customer is associated with
several (including 0) loans via borrower
39. Many-To-One Relationships
• In a many-to-one relationship a loan is
associated with several (including 0)
customers via borrower, a customer is
associated with at most one loan via borrower
40. Many-To-Many Relationship
• A customer is associated with several (possibly
0) loans via borrower
• A loan is associated with several (possibly 0)
customers via borrower
41. Connectivity
• Chen Model
– 1 to represent one.
– M to represent many
1
M
• Crow’s Foot
One
many
One or many
Mandatory one , means (1,1)
43. Binary Relationships
•
1:1 relationship
– Should be rare in any relational database design
– A single entity instance in one entity class is
related to a single entity instance in another
entity class
– Could indicate that two entities actually belong
in the same table
45. Binary Relationships
•
M:N relationships
–
Must be avoided because they lead to data redundancies.
–
Can be implemented by breaking it up to produce a set of 1:M
relationships
–
Can avoid problems inherent to M:N relationship by creating a
composite entity or bridge entity
•
This will be used to link the tables that were originally
related in a M:N relationship
•
The composite entity structure includes-as foreign keys-at
least the primary keys of the tables that are to be linked.
46. The M:N Relationship Between STUDENT and CLASS
Bowser
Smithson
Accounting 1 (ACCT-211)
Intro to Microcomputing (CIS-220)
Intro to Statistics (QM-261)
This CANNOT be implemented as shown next…..
49. Specialization
• Top-down design process: we designate sub
groupings within an entity set that are
distinctive from other entities in the set.
• These sub groupings become lower-level entity
sets that have attributes or participate in
relationships that do not apply to the higherlevel entity set.
• Depicted by a “triangle component labeled ISA”
• Attribute inheritance – a lower-level entity set
inherits all the attributes and relationship
participation of the higher-level entity set to
which it is linked.
51. Generalization
• A bottom-up design process – combine a number of entity
sets that share the same features into a higher-level entity
set.
• Specialization and generalization are simple inversions of
each other; they are represented in an E-R diagram in the
same way.
• The terms specialization and generalization are used
interchangeably.
52. Specialization and Generalization
(Cont.)
• Can have multiple specializations of an entity
set based on different features.
• E.g.
permanent_employee
vs.
temporary_employee, in addition to officer vs.
secretary vs. teller
• Each particular employee would be
– a member of one of permanent_employee or
temporary_employee,
– and also a member of one of officer, secretary, or
teller
• The ISA relationship also referred to as
“superclass – subclass” relationship
53. Design Constraints on a
Specialization/Generalization
• Constraint on which entities can be members of a
given lower-level entity set.
– Condition-defined : evaluated by an explicit condition or
predicate.
– User-defined : database user assigns
• Constraint on whether or not entities may belong to
more than one lower-level entity set within a single
generalization.
– Disjoint
• An entity can belong to only one lower-level entity set
• Noted in E-R diagram by writing disjoint next to the ISA triangle
– Overlapping
• an entity can belong to more than one lower-level entity set
54. Design Constraints on a
Specialization/Generalization (Contd.)
• Completeness constraint
– Total : an entity must belong to one of the
lower-level entity sets
– Partial : an entity need not belong to one of the
lower-level entity sets
55. Aggregation
Consider the ternary relationship works-on, which we saw earlier
Suppose we want to record managers for tasks performed by an
employee at a branch
56. Aggregation (Cont.)
• Relationship sets works_on and manages represent
overlapping information
– Every manages relationship corresponds to a works_on
relationship
– However, some works_on relationships may not correspond to
any manages relationships
• So we can’t discard the works_on relationship
• Eliminate this redundancy via aggregation
– Treat relationship as an abstract entity
– Allows relationships between relationships
– Abstraction of relationship into new entity
• Without introducing redundancy, the following diagram
represents:
– An employee works on a particular job at a particular branch
– An employee, branch, job combination may have an associated
manager
57. Aggregation (Cont.)
• Relationship sets works-on and
represent overlapping information
manages
– Every manages relationship corresponds to a workson relationship
– However, some works-on relationships may not
correspond to any manages relationships we
can’t discard the works-on relationship
• Redundancy problem aggregation