U1. Data Base Management System (DBMS) Unit -1. MCA 203, Data Base Management System

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1 Data Base Management System (DBMS) Unit -1 New Delhi-63,By Vaibhav Singhal, Asst. Professor U2.1 1 Data Base Management System Data: Data is the basic raw,fact and figures Ex: a name, a digit, a picture etc. Data Base: Collection of related data Ex. the names, telephone numbers and addresses of all the people you know Data Base Management System: A DBMS is a set of software programs that controls the organization, storage, management, and retrieval of data in a database. Ex: MS-Excel, MS-Access, Oracle, MS SQL, Sybase, IBM DB2 U2.2 2 Use of DBMS Corporate Airlines Hotels Banks Colleges /university Railway reservation Shopping Malls Telecommunication Industry Weather forecasting Pattern Recognition Data mining Space Research Software Industry U2.3 3

2 Advantages of Using DBMS Mass Data Storage Centralized Access Automatic Backup Possible Data Recovery Possible Security restrictions can be applied Easily updation & fetching of data Only authorized Access No Data Redundancy Data Consistency etc. U2.4 4 Database software... Flat Files Notepad, WordPad Light Duty Medium Duty Heavy Duty U2.5 5 Disadvantages of Flat File Systems No centralized control Data Redundancy Data Inconsistency Data can not be shared Standards can not be enforced Security issues Integrity can not be maintained Data Dependence U2.6 6

3 Data Base Characteristics Controls data redundancy. Enforces user defined rules. Ensures data sharing. It has automatic and intelligent backup and recovery procedures. It has central dictionary to store information. Pertaining to data and its manipulation. It has different interfaces via which user can manipulate the data. Enforces data access authorization. Represents complex relationship between data. U2.7 7 Data Base Users Naive User A person who does not know what is DBMS. Like:- A user of ATM. A user of credit card. Application Programmer A programmer who is responsible for developing application programs. This user can make change in the data base also and can run the queries. U2.8 8 Data Base Users contd.. Sophisticated User: sophisticated user interact with the system without writing programs. Instead, they form their requests in a database query language. Specialized User: Specialized users are sophisticated users who write specialized database applications that do not fit into the traditional data- processing framework. Ex: In expert system, AI, CAD design etc. 9 U2.9 9

4 Data Base Administrator A database administrator (DBA) is a person responsible for the design, implementation, maintenance and repair of an organization's database. U Roles of Data Base Administrator To Provide space to each user. To create the Physical and logical Schema. To Provide security from unauthorized access. To grant permission to the user Installation, configuration and upgrading of Oracle server software and related products. To take Back up and Recovery of data. Performance monitoring of the machine and database. U Data Base Architecture U

5 Disk MCA 203, Data Base Management System Three-Layer Abstraction External Schema - 1 External Schema - 2 External Schema - 3 Conceptual Schema Physical Schema U Description of Levels Users Level: At user level different -2 type of users of database are accessing the data by firing their queries. Conceptual Level: This level is designed by data base administrator. Under this level a schema of data base is created by DBA. This is also known as Logical Level. Internal Level: It indicates how the data will be stored ad describes the data structures and access methods to be used by data base. U Data Model According to Hoberman (2009), "A data model is a way finding tool for both business and IT professionals, which uses a set of symbols and text to precisely explain a subset of real information to improve communication within the organization and thereby lead to a more flexible and stable application environment. U

Different Data Models Flat file Hierarchical Data Model Network Data model Relational Data model U2.

The flat (or table) model consists of a single, two-dimensional array of data elements, where all members of a given column are assumed to be similar values, and

6 Different Data Models Flat file Hierarchical Data Model Network Data model Relational Data model U Flat Data model This may not strictly qualify as a data model. The flat (or table) model consists of a single, two-dimensional array of data elements, where all members of a given column are assumed to be similar values, and all members of a row are assumed to be related to one another. U Hierarchical Data Model In this model data is organized into a tree-like structure, implying a single upward link in each record to describe the nesting, and a sort field to keep the records in a particular order in each same-level list. U

7 Example :Hierarchical DBMS Data is represented by a tree structure P1 Nut Red 12 London P2 Bolt Green 17 Paris S2 Jones 10 Paris 300 S1 Smith 20 London 300 S3 Blake 30 Paris 200 S2 Jones 10 Paris 400 S1 Smith 20 London 200 P3 Screw Blue 17 Rome P4 Screw Red 14 London S1 Smith 20 London 400 U Drawbacks: Hierarchical DBMS Can not handle Many-Many relations Can not reflect all real life situations Anomalies in insert, delete and update operations. U Network Data Model This model organizes data using two fundamental constructs, called records and sets. Records contain fields, and sets define one-to-many relationships between records: one owner, many members. U

Relational Data Model Relational model is based on relations of the tables. It is bounded with 12 codd s rules. Every information will be stored in the form of columns and rows. U2.

8 Relational Data Model Relational model is based on relations of the tables. It is bounded with 12 codd s rules. Every information will be stored in the form of columns and rows. U Relational Data Model Example of tabular data in the relational model Attributes Customer-id customername customerstreet customercity accountnumber Johnson Alma Palo Alto A Smith North Rye A Johnson Alma Palo Alto A Jones Main Harrison A Smith North Rye A-201 U Relational Database schema U

9 Poor Table Design U Problems with Design U U

10 Name of the Data Models Relational Model DB2, Oracle, Informix, Sybase, MS-Access, Foxbase, Paradox, etc. Hierarchical Model IMS DBMS Network Model IDS & IDMS Object-Oriented Model ObjectStore & Versant Object-Relational Model Products from IBM, Oracle, ObjectStore, Versant. U Data Independence When a schema at a lower level is changed, only the mappings between this schema and higher-lever schemas need to be changed in a DBMS that fully supports data independence. The higher-level schemas themselves are unchanged. Hence, the application programs need not be changed since they refer to the external schemas. Disadvantages of two levels of mappings: Overhead during compilation or execution of a query or program U Data Independence Logical Data Independence: The capacity to change the conceptual schema without having to change the external schemas and their application programs. Reorganize physical files to improve performance e.g. List all sections offered in Fall 1998 Physical Data Independence: The capacity to change the internal schema without having to change the conceptual schema. U

11 Instance The collection of information stored in the database at a particular moment is called an instance of the database. Ex: Amit, 101 etc. U Schema The overall design of the database is called the database schema. A schema is the structure of the table which is decided before storing the data. Example: Create table student ( rollno number(5), name char(15), address varchar2(25)); U Tuple A tuple is a related record stored in a row of the table. Ex: 101,Alok,MCA,85% Tuple : Record Attributes: columns Entity : Tables U

34 34 E-R Diagrams Rectangles represent entity sets. Diamonds represent relationship sets. Lines link attributes to entity sets and entity sets to relationship sets.

12 E-R Diagram Entity Relationship Diagram Set of some predefined symbols E-R diagram is used to create a relational data base or data model. Before designing the data base we have to first create the E-R Diagram for whole data base than it will convert into the tables and relations. U E-R Diagrams Rectangles represent entity sets. Diamonds represent relationship sets. Lines link attributes to entity sets and entity sets to relationship sets. Ellipses represent attributes Double ellipses represent multivalued attributes. Dashed ellipses denote derived attributes. Underline indicates primary key attributes (will study later) U Symbols Used in E-R Notation U

Summary of Symbols (Cont.) U2.37 37 Cardinality E-R Notations U2.

13 Summary of Symbols (Cont.) U Cardinality E-R Notations U E-R Diagram With Composite, Multivalued, and Derived Attributes U

14 Types of Keys Superkey is a set of one or more attributes that allow us to identify uniquely an entity in the entity set. Like: s.no, name,age Candidate Key are minimal superkey in an entity, one of those keys is selected to be the primary key like: s.no and name both Primary Key is a candidate key that is chosen to identify entities within an entity set like: rollno Foreign Key is a primary key of another relation schema like: Any key which is primary key U Weak Entity set An entity set which is not having any primary key or candidate key is termed a weak entity set. U Strong entity set An entity set that has a primary key is termed as strong entity set. U

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 U2.

15 Mapping Cardinalities 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 U 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 U 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 U

Overall Database Design U2.46 46 Dr. Edgar F.

1963, and presented a thesis on the topic of a self- reproducing computer

interacts in a uniform manner with its four immediate neighbors.

16 Overall Database Design U Dr. Edgar F. Codd ( ) Codd completed his PhD at the University of Michigan in 1963, and presented a thesis on the topic of a self- reproducing computer consisting of a large number of simple identical cells, each of which interacts in a uniform manner with its four immediate neighbors. Codd reported this work in a book entitled Cellular Automata published by Academic Press in U Relational Terminology U

17 12 Codd's Rules U Rule 1 : The Information Rule All data should be presented in table form. Rollno Name Age college 10 Rohit 20 Bv 11 Rahul 21 Abes 12 Amit 22 Jss 13 Simran 23 its U Rule 2 : Guaranteed Access Rule All data should be accessible without ambiguity. This can be accomplished through a combination of the table name, primary key and column name. U

18 Rule 3: Systematic treatment of null values A field should be allowed to remain empty. This involves the support of null value, which is distinct from an empty string or a number with a value of zero. Most database implementations support the concept of a not null field constraint that prevent null values in a specific table column. U Rule 4: Dynamic on-line catalog based on the relational model A relational database must provide access to its structure through the same tools that are used to access the data. This is usually accomplished by storing the structure definition with in special system table. U Rule 5 : Comprehensive data sub-language Rule The database must support at least one clearly defined language that include functionality for data definition, data manipulation, data integrity and data transaction control. All commercial relational databases use forms of standard SQL( structure Query Language) as their supported comprehensive language. U

19 Rule 6 : View updating Rule Data can be presented into different logical combinations called views. Each view should support the same full range of data manipulation that has direct access to a table available. In practical, providing update and delete access to logical views is difficult and is not fully supported by current database. U Rule 7 : High-level Insert, Update and Delete Data can be retrieved from a relational database in sets constructed of data from multiple rows and multiple tables. This rule states that insert, update, delete operations should be supported for any retrievable set rather just for a single row in a single table. U Rule 8 : Physical data independence The user is isolated from the physical method of storing and retrieving information from the database. Changes can be made to the underlying architecture ( hardware, disk storage methods) without affecting how the user accesses it. U

20 Rule 9 : Logical Data Independence. How the data is viewed should not be changed when the logical structure (table s structure) of the database changes. This rule is difficult to satisfy. Most databases rely on strong ties between the data viewed and the actual structure of underlying tables. U Rule 10 : Integrity Independence SQL should support constraints on user input that maintain database integrity. At a minimum, all databases do preserve two constraints through SQL. Primary key should be not null and unique. If a foreign key is defined in one table, any value in it must exist as a primary key in another table. U Rule 11 : Distribution Independence A user should be totally unaware of whether or not the database is distributed ( whether parts of the database exist in multiple locations). A variety of reasons make this rule difficult to implement. U

21 Rule 12: The Non subversion rule There should be no way to modify the database structure other than through the multiple row database language( SQL). Most databases today support administrative tools that allows some direct manipulation of the data structure. U Specialization An entity set may include sub grouping of entities that are distinct in some way from other entities in the set. For Instance, a subset of entities with in an entity set may have attributes that are not shared by all the entities in the entity set. The process of designating sub grouping with in an entity set is called specialization. U Specialization Example U

22 Generalization The commonality can be expressed by generalization, which is containment relationship that exists between a higher level entity set and one or more lower level entity sets. The refinement from an initial entity set into successive level of entity sub grouping represent s a top down design process in which distinctions are made explicit. U 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. U Aggregation Aggregation is an abstraction through which relationships are treated as higher- level entities. One limitation of E-R Model is that it can not express relationship among relationship U

23 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. U Objective Questions Q1. What is Data Base Management system? A. file B. Tables with records C. Software C. none of these Q2. A data base follows how many rules at max? A. 6 B. 7 C. 11 D.11.5 Q3. What is Primary Key? A. NotNull B. Unique C. Unique +Notnull D. None of these U Objective Questions Q4. Which is not a DBMS? A. None of the these B. DB2 C. Access C. Sybase Q5. SQL stands for Q6. What is candidate Key? Q7. E- R Diagram is used for what? Q8.. is specialized user? U

24 Objective Questions Q9.Logical Data Independency is done at which level? A. Conceptual Level B. User Level C. Internal level C. None of the above Q10. DBA stands for Q11. What is generalization. U Short Questions: Q.1 What is data independence? Q.2.What do you mean by DBMS? Q.3 A transaction is a set of operations that must be performed completely or not at all. Explain with suitable example. Q.4What is the difference between Generalization and Specialization? Q.5 Describe the characteristics of DBMS. Q.6 Explain all components of E-R Diagram. Q.7 What is of keys in DBMS and explain how many types of keys are there. U Long Questions: Q.1 Describe 3-level of abstractions of DBMS. Q.2 Differentiate between physical and logical data independency. Q.3 Discuss all 12 rules of Dr. E.F. Codd s. Q.4 What is data model? Discuss various data models available in DBMS. Q.5Differentiate between weak and strong entity sets with example. Q.6 What is a DBMS? How does it differ from a conventional file system? U

Database Systems. Lecture2:E-R model. Juan Huo( 霍娟 )

Database Systems. Lecture2:E-R model. Juan Huo( 霍娟 ) Database Systems Lecture2:E-R model Juan Huo( 霍娟 ) Reference slides: http://www.cs.wisc.edu/ dbbook Berkeley, Professor Eben Haber,Professor Mary Roth Review: Benefits of a DBMS 1. Data independence applications