Published on November 26, 2013
TOPIC 2 : DATABASES & DBMS Er. Pradip Kharbuja
Metadata Metadata is data about data. It is the way in which the database keeps information about its own structure. Metadata is stored in the data dictionary.
Metadata Name Student Name Type Character Length 50 Student ID Number 8 Date of Birth Date 8 Description Student’s name Unique identification number for a student Student’s date of birth in the format ’01.01.80’
Metadata in MS Access
Metadata in Oracle SQL SQL> DESC emp Name Null? ------------------------------- -------EMPNO NOT NULL ENAME JOB MGR HIREDATE SAL COMM DEPTNO SQL> Type ---NUMBER(4) VARCHAR2(10) VARCHAR2(9) NUMBER(4) DATE NUMBER(7,2) NUMBER(7,2) NUMBER(2)
Metadata in SQL Server
Metadata Column Name Datatypes 1. 2. 3. 4. 5. VARCHAR TEXT INTEGER DECIMAL DATE Type Length NULL
Activity Define metadata for data about the following: Students in a college database College Examination Books in a library system Holidays booked by a person at a workplace Shopping Mart Try to think about what data needs to be kept - will it be a character, date or number?
Two-File Processing System Customer File User Customer Processing System Customer File Rental File User Rental Processing System Rental File
Two-File Processing System The example used is of a car rental system. One system processes CUSTOMER data, and the other processes RENTAL data. Each of the files and the applications that use them are totally separate. Although this is an improvement over older manual systems, there are a number of problems.
Problems in Two-File Processing System 1. Data are separated and isolated. 2. Data are often duplicated. 3. Problem of Data integrity 4. Application programs are dependent on file formats. 5. Files are often incompatible with one another. 6. It is difficult to represent data in a user’s perspective.
Basic Structure of a Database User Customer Processing Application User Rental Processing Application DBMS User Other Application Database
Database System in Detail User Customer Processing Application DBMS serves as intermediary between user and the database by translating user requests into the complex code required to fulfill those requests. Application Requests Data User Rental Processing Application METADATA Application Requests DATA Data Application Requests DBMS User Other Application Data Database Management System Application programs might be written in a programming Language, such as Visual Basic or C++, or it might be created through a DBMS utility e.g. Access’s forms wizard. Database
Features of the Database Approach 1. Integrated data 2. Reduced data duplication 3. Program/data independence 4. Easier representation of users’ perspectives 5. Database systems are self-describing
Common Applications 1. Forms 2. Reports 3. Web-applications 4. Batch processes
DBMS – Architecture • The DBMS is the software that handles all the interactions between applications and the database. • Paul Benyon-Davis provides a useful way of looking at the structure of the DBMS itself i.e. DBMS Architecture. • 3 layers 1. Kernel 2. Toolkit 3. Interface
Kernel, Interface and Toolkit DBMS Toolkit Interface DBMS Kernel Database
Kernel, Interface and Toolkit 1. Kernel Central engine, which operates most of the core data management functions 2. Toolkit The tools and applications that interact with the end-users. These might be provided as part of the DBMS product or as separate piece of software. 3. Interface It handles the interaction between the toolkit and the kernel
DBMS Functions 1. CRUD functions 2. Data dictionary 3. Transaction management 4. Concurrency control 5. Recovery 6. Authorization 7. Data integrity 8. Administration utilities
Advantages of DBMS Control of data redundancy Improved data integrity or Data consistency Sharing of data Improved security Enforcement of standards Improved data accessibility and responsiveness Improved maintenance Increased concurrency Improved backup and recovery services
Disadvantages of DBMS Complexity Size Cost of DBMSs Additional hardware costs Cost of conversion Performance
Data Models Hierarchical Network Relational Object-oriented Deductive Post-relational
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