DBMS & Data Models - In Introduction
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This document provides an introduction to database management systems (DBMS). It defines key terminology related to databases and discusses problems with manual databases. It describes the functions and advantages of DBMS, including data representation, transaction management, data sharing, and increased security. Examples of popular DBMS are provided, such as Oracle, Microsoft SQL Server, and MySQL. Database system architecture, data models, and the relational model are overviewed. Finally, entity relationship (ER) modeling is explained as a way to conceptualize data needs and design the database logically before implementation.
![Data Modelling
• A Data Model is a plan. It’s a blueprint for building a Database.
• Convert Data Needs into a Data Model ([Interface Model ->] ER Model)
• Convert the ER Model to Relational Model
• Implement the Relational Model using RDBMS of your Choice.
à SQL](https://image.slidesharecdn.com/1dbms-concepts-190225052916/85/DBMS-Data-Models-In-Introduction-13-320.jpg)
![Relational [Database] Model
• First defined by Computer Scientist Edgar Frank Codd
in 1969.
• Mathematical model, based on Relational Algebra and
Predicate Logic.
• Very well defined and extremely mature model
in terms of data storage and representation.
• All RDBMS (Relational Database Management Systems) derived from Relational
model.
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DBMS & Data Models - In Introduction
- 1. Introduction to DBMS Rajeev Srivastava
- 2. ToC • Basic Terminology • Database & DBMS • Problems in Manual Database • Applications of DBMS • Functions/Characteristics of DBMS • Advantages of DBMS • DBMS Examples • Database Systems Architecture • Data Models • Relational Model • ER Model • Cardinality Ratio of a Relation • Database Design • ER Model [email protected] 2
- 3. Basic Terminology • Data – Raw information, A value representing an quality or quantity A recorded fact. • Information – Processed data • Record – A collection of related data/information. • Data Dictionary – Data dictionary is a detailed description of data objects exists in a system. • Data Warehouse – Centralized repository of data from one or more sources and used for reporting and data analysis. [email protected] 3
- 4. Database & DBMS Database – A database is an organized collection of data, that can be easily accessed, managed and manipulated. OR A database is a collection of interrelated data stored together without harmful or unnecessary redundancy. DBMS A database management system(DBMS) is a software package used to store and manage data. [email protected] 4
- 5. Problems in Manual Database • No sharing • Data isolation • Diffused responsibilities • Poor coordination • Data redundancy • Weak (data) integrity [email protected] 5
- 6. Functions/Characteristics of DBMS • Data Representation • Data Manipulation Management • Performance • Transaction Management • Data Access Management •Integrity Services •Concurrency Control •Catalogue Management •Security Management •Backup & Recovery Management [email protected] 6
- 7. Advantages of DBMS • Storage and Data Redundancy Management • Increased Security • Faster Retrieval • Analysis Summary Reports • Restricted Access • Centralized Management and Control • Data Sharing [email protected] 7
- 8. Applications of DBMS • Banking • Railway • Airlines • Educational Organizations / University • Data Warehouses • And many more… • Enterprise Business • Manufacturing • Sales • Human Resource • Payroll • And many more… [email protected] 8 Find at least 3 more applications of DBMS
- 9. DBMS Examples • Oracle • Microsoft SQL Server • IBM DB2 • SAP Sybase ASE • Microsoft Access • Ingres (Open Source) • PostgreSQL (Open Source) • MySQL (Open Source) • MariaDB (Open Source) • SQLite • Teradata • NoSQL Databases •Couchbase •Google Firebase •MongoDB •Cassandra •Hbase [email protected] 9 Find names of at least 5 additional popular DBMS Find more about these listed databases – Type, Uses, Latest Versions, Underlying Data Modals, Owner Companies etc.
- 10. Database System Architecture Database System Architecture can be defined on three levels • External Level (View Level ) – The way data will be represented to the end user. High Level Architecture • Conceptual Level (Logical Level) – Defines logical structure of the database in terms of entities, relationships, attributes, datatypes etc. • Internal Level (Physical Level) – Defines the way data is stored on physical storage. Low level architecture. [email protected] 10
- 11. Database Design Goals • Accuracy-Integrity • Consistency • Speed/Performance - for all crud operations • Persistency • Backup & Recovery • Extensibility • Scalability • Error Correction • Robustness • ACID Support • Ease of Use • Portability • Security • Sharing • Ability to Perform Complex Calculations
- 12. Understand User/System’s Requirements • Functional • Reports • Data Flow • Data Format & Validity • Data Security Create Use Cases and Identify Data Needs for each Use Case
- 13. Data Modelling • A Data Model is a plan. It’s a blueprint for building a Database. • Convert Data Needs into a Data Model ([Interface Model ->] ER Model) • Convert the ER Model to Relational Model • Implement the Relational Model using RDBMS of your Choice. à SQL
- 14. Data Models • Data models defines how data in a database system get stored and represented. • A data model uses a set of construct or rules to provide a representation of data content, structure and constraints required by an application. Network Model – Data is represented in collection of records and relationship among records is in form of links (similar to pointers). Hierarchical Model – Data is represented in collection of records, and relationship among records is represented in form of hierarchical trees. Relational Model – Data is represented in tabular format. A table is comprises of rows and columns. Object Oriented Model – Data is represented in form of objects and based on the concept of Object Oriented Programming (OOP) Concepts. Hybrid Models – Ex. Object Relational Database Management Systems [email protected] 14 Learn more about these listed Data Modals. Find out few other data models with their examples
- 15. Relational [Database] Model • First defined by Computer Scientist Edgar Frank Codd in 1969. • Mathematical model, based on Relational Algebra and Predicate Logic. • Very well defined and extremely mature model in terms of data storage and representation. • All RDBMS (Relational Database Management Systems) derived from Relational model. [email protected] 15
- 16. Entity Relationship (ER) Model • Proposed by Peter Chen in 1970s. • An object model. • Graphical representation of the logical relationship among entities (or objects). • Describes data aspects of a system under implementation on abstract level. • Conceptual Model representing logical design of a database. • Notations • Chen Notation • Crow-Foot Notation • Bachman Notation • Martin Notation • IDEF1X Notation [email protected] 16
- 17. Entity Relationship (ER) Model Component Symbol Example Entity Rectangle Attribute Ellipse Link between Entity and Attribute Line Relationship Among Entities Diamond [email protected] 17 Learn about various symbols available in different ER notations.
- 18. Cardinality Ratio of Relationship Relationship among entities can be represented in following three ways – • One-to-one • One-to-many or Many-to-one • Many-to-many [email protected] 18 Find out at least 3 examples of each type of Relationship in real world
- 19. Simple ER Depiction Employee Department N 1 HODProject M N 1 1 EmpID Name Desig DeptID DeptName Location Works For [email protected] 19 Identify Entities, Relation among entities and Attributes in a System/Business and create an ER Diagram.
- 20. ER Diagram….more • Entities are generally Nouns. Relationships are Verbs • If every entity in a relationship set is must participate in a relationship, its known as Full Participation – represented by double line. • If an entity can participate in at most one instance of the relationship set its called as a Key Constraint - an arrow is used to connect entity to the relationship. • If an entity must be involved in exactly one instance of a relationship set to indicate both participation and key constraint, its indicated through a double or thick arrow. [email protected] 20
- 21. [email protected] 21 • Draw relationships from Left to Right and Top to Bottom. May be marked by arrow above/below the relationship. • Inheritance – is A – represented by a Triangle
- 22. • An entity that can not be identified by its attributes alone is called as Weak Entity. Its existence depends on another entity – it is represented by double border rectangle. • Multivalued attribute (an attribute representing more than one value for a single entity) is represented by double line ellipse. • Ternary or n-nary Relationship can be depicted in the same way as Binary. • Notes and comments may be added to ERD. But it should be done in a clean way. • The ultimate goal of creating an ERD is to help understanding the project. Hence easy information representation should be given priority over technical correctness. [email protected] 22 ER Diagram….more
- 23. ER Model to Relational Mapping Example [email protected] 23
- 24. Attributions: • Database System Concepts – Abraham Silberschatz, Henry F. Korth, S. Sudarshan • Beginning Database Design Solutions - Rod Stephens [email protected] 24