Entity Relationship Diagram (ERD) Dr. Moustafa Elazhary

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1 Entity Relationship Diagram (ERD) Dr. Moustafa Elazhary

2 Data Modeling Data modeling is a very vital as it is like creating a blueprint to build a house before the actual building takes place. It is built in a phases with several iterations of validation to ensure that the structure and content of the model meets the business requirements WS 2018/2019 Information Systems - Entity Relationship Diagram 2

3 Database design Conceptual design Logical design Physical design WS 2018/2019 Information Systems - Entity Relationship Diagram 3

4 Conceptual data models These models are typically used to identify and document business concepts with project stakeholders. Conceptual data models are often created as the precursor or as alternatives to Logical Data Models (LDMs). The conceptual data model includes the main concepts and the main relationships among them. It delivers an ERD and associated data dictionary Customer Lives at Address John Doe Jane Doe 4 Leopold street 3 Leopold street WS 2018/2019 Information Systems - Entity Relationship Diagram 4

5 Data dictionary master customers WS 2018/2019 Information Systems - DB - Master 5

6 Logical data models They are used to explore the domain concepts, and their relationships and relationship cardinalities. They are outlined independently of a particular or storage technology but in terms of data structures such as relational tables. The logical data model transforms ERD to relational model such as tables, keys, etc. Customer Address Customer ID First name Last name Mobile Street City Zip Country WS 2018/2019 Information Systems - Entity Relationship Diagram 6

7 Data dictionary master customers WS 2018/2019 Information Systems - DB - Master 7

8 Physical data models They are used to design the internal schema of a database, documenting: The data tables (derived from the logical data entities) The data columns of those tables (derived from the entity attributes), The relationships between the tables derived from the entity relationships). The physical data model delivers the database and other supporting structures DBMS Database schema describes the details of the database, which can be represented by schema diagrams. A database schema defines its entities and the relationship among them. WS 2018/2019 Information Systems - Entity Relationship Diagram 8

Physical data models schema Source: https://ecs.victoria.ac.

9 Physical data models schema Source: WS 2018/2019 Information Systems - Entity Relationship Diagram 9

10 Physical data models view A database view is an object that can be searched in a database that is defined by a query. A view doesn t store data and sometimes called virtual tables,. It can combine data from two or more table, and it can also contain only a subset of information. WS 2018/2019 Information Systems - Entity Relationship Diagram 10

11 Chen ERD Attribute Attribute Attribute Attribute Entity Relationship Entity WS 2018/2019 Information Systems - Entity Relationship Diagram 11

12 Data entity A term used in logical data models to describe a class of persons, places, things, or events of interest to the business. The corresponding physical data model generally implements the entity in a database table or view. Entity class (entity set) is a structural description of things that share common attributes Entity instance is the occurrence of a particular entity Noun customers, items, orders Identifier Identifies an entity instance The value of the identifier attribute is unique for each entity instance Customer Item Student WS 2018/2019 Information Systems - Entity Relationship Diagram 12

13 Data attribute A term used in logical data models to describe a kind of fact common to all or most instances of an entity. Student ID is an attribute of the entity Student. The corresponding physical data model generally implements the attribute as a database column or field. It describes an entity class Customer name, address Item price, stock Order date, quantity All entity instances of a given entity class have the same attributes, but vary in the values of those attributes Name Student Student ID Identifier (underlined) Birthdate WS 2018/2019 Information Systems - Entity Relationship Diagram 13

14 Relationship It describes how entities are related A relationship is a named connection or association between entities. Each relationship is drawn as a line connecting the two entity types; Each relationship is given a name that indicates what information it imparts (relationships are named in both directions); Verb Relationship features Cardinality Entity instance s participation count Degree of relationship How many entities are involved in a relationship? Entity Relationship Entity WS 2018/2019 Information Systems - Entity Relationship Diagram 14

15 Chen ERD WS 2018/2019 Information Systems - Entity Relationship Diagram 15

16 Cardinality Cardinality is the number of instances of an entity from a relation that can be associated with the relation. One to one One to many Many to many WS 2018/2019 Information Systems - Entity Relationship Diagram 16

17 Cardinality One-to-One When only one instance of entity is associated with the relationship, it is marked as '1'. This image below shows that only 1 instance of each entity should be associated with the relationship. It indicates one-to-one relationship Entity Noun 1 Relationship 1 Verb Entity Noun Student 1 1 has Contact Info WS 2018/2019 Information Systems - Entity Relationship Diagram 17

18 Cardinality One-to-Many When more than one instance of entity is associated with the relationship, it is marked as 'N or M. The image below shows that only 1 instance of entity on the left and more than one instance of entity on the right can be associated with the relationship. It indicates one-to-many relationship Entity 1 M Entity Customer 1 M Places Orders WS 2018/2019 Information Systems - Entity Relationship Diagram 18

19 Cardinality Many-to-Many The image below shows that more than one instance of entity on the left and more than one instance of entity on the right can be associated with the relationship. It indicates many-to-many relationship Books-Authors, Students-Courses, Items-Suppliers Relational database systems usually don't allow you to implement a direct many-to-many relationship between two tables. Entity M M Entity Items M have M Suppliers WS 2018/2019 Information Systems - Entity Relationship Diagram 19

20 Referential integrity It refers to rules governing data consistency, specifically the interaction between primary keys and foreign keys in different tables. It dictates what happens when you update or delete a value in a referenced column in the parent table and when you delete a row containing a referenced column from the parent table. Consistency means that any data written to the database must be valid according to all defined rules If a transaction is executed that violates the database's consistency rules, the entire transaction will be rolled back and the database will be restored to its original state. Database consistency doesn't mean that the transaction is correct, only that the transaction didn't break the rules defined by the program. WS 2018/2019 Information Systems - Entity Relationship Diagram 20

21 Exercise student-course You need to translate this scenario into an ERD. There are many students in the DEM program where every student is identified by a student ID and his/her name. Students are required to enroll in many courses by selecting the course ID. Each course has its name, assessment method and a specified date. Students are also required to read books in electronic and printed formats. WS 2018/2019 Information Systems - Entity Relationship Diagram 21

22 Exercise student-course-solution Every student has a unique identifier called student ID Every course has a unique identifier called course ID Every book has a unique identifier called book ID Entities attributes Student student ID, student name, DEM program Books book ID, electronic, printed Course course ID, course name, assessment method, date Relationships Students enroll in a course Students read books in electronic and printed formats WS 2018/2019 Information Systems - Entity Relationship Diagram 22

23 Exercise student-course-solution-erd Student ID Student name Enroll In M Student M Read M Course Course ID Assess method Course date Book ID Printed M Book Electronic WS 2018/2019 Information Systems - Entity Relationship Diagram 23

24 Exercise customer-order You need to translate this scenario into an ERD. Customers place their sales orders that can have multiple items. Customers have their ID, names and contact information while sales orders have their ID, date and items and item quantity. Items have their ID, and price. WS 2018/2019 Information Systems - Entity Relationship Diagram 24

25 Exercise customer-order-solution Every customer has a unique identifier called customer ID Every item has a unique identifier called item ID Every sales order has a unique identifier called sales order ID Entities attributes Customer customer ID, customer name, contact information Sales order sales order ID, customer ID, item ID, item quantity, date Items item ID, item name, item price Relationships Customer places orders Order contains items WS 2018/2019 Information Systems - Entity Relationship Diagram 25

26 Exercise customer-order-solution-erd Do-it-yourself DIY Please send the solution in PowerPoint format by WS 2018/2019 Information Systems - Entity Relationship Diagram 26

27 Data Modeling Basic Steps 1. Identify entity types 2. Identify Attributes 3. Establish Data Naming Conventions 4. Identify Relationships 5. Assign Keys 6. Normalize Data 7. Optimize Performance WS 2018/2019 Information Systems - Entity Relationship Diagram 27

28 Identify entity types An entity type represents a collection of similar objects such as people, places, things, events, or concepts. Examples of entities in an order entry system would include Customer, Address, Order, Item, and Tax. Customer and order are clearly two different concepts; therefore it makes sense to model them as separate entities. WS 2018/2019 Information Systems - Entity Relationship Diagram 28

29 Identify Attributes Each entity type will have one or more data attributes. For example, the Customer entity has attributes such as First Name and Last Name and the tbl_customer table has corresponding data columns cust_first_name and cust_last_name (a column is the implementation of a data attribute within a relational database). Getting the level of detail right can have a significant impact on your development and maintenance efforts. WS 2018/2019 Information Systems - Entity Relationship Diagram 29

30 Establish Data Naming Conventions Standards and guidelines applicable to data modeling should be set and enforced which is usually the responsibility of a data administrator. These guidelines should include naming conventions for both logical and physical modeling, the logical naming conventions should be focused on human readability whereas the physical naming conventions will reflect technical considerations. The basic idea is that developers should agree to and follow a common set of modeling standards on a software project. WS 2018/2019 Information Systems - Entity Relationship Diagram 30

31 Identify Relationships Entities have relationships with other entities. For example, customers PLACE orders, customers LIVE AT addresses, and items ARE PART OF orders. Place, live at, and are part of are all terms that define relationships between entities. The relationships between entities are conceptually identical to the relationships (associations) between objects. WS 2018/2019 Information Systems - Entity Relationship Diagram 31

32 Assign Keys A key is one or more data attributes that uniquely identify an entity. A key that consists of two or more attributes is called a composite key (each key attribute itself is not unique). In a physical database, a key would be formed of one or more table columns whose value(s) uniquely identify a row within a relational table. Composite key WS 2018/2019 Information Systems - Entity Relationship Diagram 32

33 Normalize Data Normalization is restructuring a relational database to reduce data redundancy and improve data integrity. In other words, it is a process used to organize a database into tables and columns and the table should be about a specific topic and then only those columns which support that topic are included.. The goal is to reduce, and even eliminate, data redundancy. Data redundancy is when some data fields are repeated either in two or more tables or if the field is repeated within the table. Data redundancy can lead to: Unneeded increase in database size Data inconsistency Decreased efficiency WS 2018/2019 Information Systems - Entity Relationship Diagram 33

34 Optimize Performance Database optimization involves maximizing the speed and efficiency with which data is retrieved. Normalized data schemas, when put into production, may suffer from performance problems. This makes sense the rules of data normalization focus on reducing data redundancy, not on improving performance of data access. It may be necessary to denormalize portions of your data schema to improve database access efficiency. It should be documented why changes were made to the model. WS 2018/2019 Information Systems - Entity Relationship Diagram 34

course 3 Levels of Database Design CSCI 403 Database Management Mines Courses ERD Attributes Entities title 9/26/2018

course 3 Levels of Database Design CSCI 403 Database Management Mines Courses ERD Attributes Entities title 9/26/2018 3 Levels of Database Design CSCI 403 Database Management 13 Database Modeling with Entity-Relationship Diagrams Conceptual (this lecture) Understand data entities & relationships between them Communication