DATABASE MANAGEMENT SYSTEM
Data – collection of facts and figures.
Database –Pool of data stored in one or several places.
Why we are using Database?-To store data.
-To use data for obtaining information.
e.g database of students of an institute.
What is DBMS?-A system which manages database.
-A system collecting,storing, using, manipulating, controlling, evaluating, retrieving, validating, organizing data in a database.
Users of DBMS
3 particular users:-
a) Programming users:-programming language those who create codes and for database management systems.
They are highly skilled, experts who create language useful for end- users, generate codes, methods, queries so that language becomes easy for second users.
b) DBA: - Database administrators trained people who handle the entire database work
-Supervision
- data updation (addition, deletion)
-controlling data
-storing new data
-validating previous data
c) Non Programming User :-who use codes and queries for retrieving read data from database they can also insert new data in database .
e.g. while creating email id sign up page --> data collected this HTML stored by java oracle
there are three uses of DBMS
1. creating
2. managing
3. using
3 Component of DBMS----
1. DDL--Data Definition Language
2. DML—Data Manipulation language
3. DD—Data Dictionary
DDL—Creating codes ,etc. .work of programme user and DBA they are highly expertise people generating codes and queries as well as managing entire DBMS.
Language used by these PPl is DDl programing language.
DML—
it is a specific set of codes and queries used to insert new data to delete un revised data, to update data in database.
eg. Inserting new data in student database, non programme users.
eg. Inserting new data in student database, non programme users.
DD—
you will have codes and their usage (information about users) data and information info about those who access a database.
Three types of DBMS
Hierarchical DBMS ( HDBM)
-- using database in hierarchical way parent children relationship
Eg. Organisational Hierarchy
Network DBMS (NDBMS)
1 child many parents
Relational DBMS (RDBMS)Proposed by Dr. E.F. Codd in 1970 it is a simple two dimensional database consisting of rows and columns.
Rows- individual records
Columns- attributes of each records
Easiest database model.
DATA WAREHOUSING
DATA WAREHOUSE
A place where we store a lagre amount of relevant data is called a data warehouse
DATA WAREHOUSING
a process of storing data in a datawarehouse is data warehousing
Warehousing Process.
Central Data Depository
CDD is the place where all the data have been stored initially.
after that, the data have been sorted as per the needs of different departments and get availed in different data marts for the end users.
Why data mart?-Easily available
-Segregated/ required/ relevant data.
Metadata-
Central Data Depository
CDD is the place where all the data have been stored initially.
after that, the data have been sorted as per the needs of different departments and get availed in different data marts for the end users.
Data mart- is a sub faction of center data depository where data is retrieved by end users.
Why data mart?-Easily available
-Segregated/ required/ relevant data.
Metadata-
'Data about data’
- When data was generated?
- When was the data stored?
- Who stored?
- Why it was stored?
- Metadata will validate the data from data mart.
- When data was generated?
- When was the data stored?
- Who stored?
- Why it was stored?
- Metadata will validate the data from data mart.
Benefits of data warehousing-
- Availability of data.
- Time saving
- Useful for decision-making process.
- Correct/ accurate/ relevant data
- Avoid uncertainty coz more data available.
Data warehousing Def.
“It is a subject oriented integrated, time varying, non-volatile collection of data in management decision making process.”
Drawbacks of data warehousing-
- Huge storage capacity required even for unutilized data.
- Threat of theft of data
- If wrong data is stored, accurate info cant be availed
- Maintaining and updating the warehouse is a tedious job.
- No back up system.
Data Mining
Mining- digging to find valuable material from huge hidden place.
Data mining – searching valuable hidden data
Eg. Hospital mgmt – maintaining data of doctors, patients, other employees.
If by mistake doctors specialization field is not specified, then we can find that info from patients data (disease, consultant Dr.)
Process of data mining
1. Problem statement- define the required data
2. Collect sources of info
3. Evaluating sources
4. Designing model- as to how we are going to search the data.
5. Implementation.
6. Follow-up
7. Restoring.
8. Iteration- repeating process for another set of required data.
- Availability of data.
- Time saving
- Useful for decision-making process.
- Correct/ accurate/ relevant data
- Avoid uncertainty coz more data available.
Data warehousing Def.
“It is a subject oriented integrated, time varying, non-volatile collection of data in management decision making process.”
Drawbacks of data warehousing-
- Huge storage capacity required even for unutilized data.
- Threat of theft of data
- If wrong data is stored, accurate info cant be availed
- Maintaining and updating the warehouse is a tedious job.
- No back up system.
Data Mining
Mining- digging to find valuable material from huge hidden place.
Data mining – searching valuable hidden data
Eg. Hospital mgmt – maintaining data of doctors, patients, other employees.
If by mistake doctors specialization field is not specified, then we can find that info from patients data (disease, consultant Dr.)
Process of data mining
1. Problem statement- define the required data2. Collect sources of info
3. Evaluating sources
4. Designing model- as to how we are going to search the data.
5. Implementation.
6. Follow-up
7. Restoring.
8. Iteration- repeating process for another set of required data.
Application of datamining-1. Government ministries
2. [Note; basically almost everywhere where ther is handling of data]
3. all depts. Of an organization-
mkt- sales, promotion
HR- training
Finance- A/C etc.
A. R. Sayyed
