Data & Database

DATA

Data can be defined as a representation of fact, concept or instruction. It is suitable for communication, interpretation or process by human or electronic devices.

DATA can be divided into 2 types

  • Qualitative Data
  • Quantitative Data

Qualitative Data is provide descriptive information eg:-  Name and Description

Quantitative Data is like numeric information eg:- Number

For saving the data we are using

  1. Books and Paper
  2. Flat files (This file system was developed with high-level programing language; eg:- Note pad)
  3. Database

WHY DATABASE?

This is the most important question that comes to our mind, the answer is below

  • Data Retrieval: – If you want to retrieve data from Flat files than you must need to program in a high level language which is a tough task. But in Database fetch any record is very easy and simple by SQL language.
  • Data Redundancy: – In Flat file, data duplication is a major issue, same data can store multiple time, which can avoid in the database. Not only avoid duplicate data also we can avoid partially duplication.
  • Data Integrity: – In a database, data integrity can maintain very easily by using constraint.
  • Data Security: – Datastore in a flat-file can’t be secured because the file doesn’t provide a security mechanism. Whereas the database provides role-based security. eg:- Manage can see the salary of all of his worker but the worker can’t see.

Data indexing: – Due to data indexing mechanism data can be retrieved very fast from the database, whereas flat file this mechanism is not given.

Data Base Management System (DBMS)

It is a collection of programs (Software) written to manage the database. eg:- Oracle, SQL Server, My SQL, Teradata

When we are installing DBMS software then automatically someplace is created in hard disk is called database. And also a user interface automatically created to interact directly or indirectly through the application program.

Every Database having 2 types of structure

  1. Physical Structured
  2. Logical Structured

Physical Structured:- A structured which is visible on OS is called Physical Structured. This is handled by only DBA.

Logical Structured:- This is not visible in the OS. Logical Structured handled by Database Developer.

Logical Structured contain database object as tables, views, synonyms, sequence.

DBMS Architecture

ANSI has established 3 levels of architecture for DBMS, this architecture is also known as ANSI/SPARC (standard planning and requirement committee).

  • Conceptual Level
  • External Level
  • Internal Level

3 level of architecture provides Data Independence.

DATA INDEPENDENCE

The upper level is unaffected by changing the lower level is called data independence.

DBMS provides

  • Physical Data Independence :

Changes in the internal level don’t require changes to the conceptual level is called Physical Data Independence.

  • Logical Data Independence :

Change in the conceptual level doesn’t require changes to the external level is called logical data independence.

CONCEPTUAL LEVEL

It provides the logical structure of the database. The conceptual level doesn’t define how data is storing in the database. It defines what type of data is storing in the database by specifying the data type and also defines what type of data can’t be stored in the database by specifying constraints.

EXTERNAL LEVEL

The external level provides a security mechanism for the database because at the external level some type of user allowed accessing portion of the data from the conceptual level.

Generally DBA creates views from the table and those views are given to the number of users to allow access portion of the data at a conceptual level.

INTERNAL LEVEL

The internal level defines how data is physically stored within the database. This level is handle by DBA only.

DATA MODEL

How the data is represented at the conceptual level defined by means of data model

There are 3 types of data models used.

  1. Hierarchical data model
  2. Network data model
  3. Relational data model

HIERARCHICAL DATA MODEL

In this data model data organize tree-like structure also data is represented in the format of records. Hierarchical data model parent and child record relationship define based on one to many relationships, on this relationship, many child records having one parent record. That’s why that data model produces more duplicate data because here child records are repeated.

If you want to retrieve data from Hierarchical data model product database server will very slowly retrieve data from the database.

In 1960 IBM introduce IMS (Information Management System)product based on the Hierarchical data model.

NETWORK DATA MODEL

In 1970 COADASYL (Conference on data system language) committee introduces network data model. In this data model data is represented in the form of records. This model is implemented based on many to many relationships in between parent and child. Network data model reduces number of records because here child record is not repeated. In 1970 IBM introduce IDMS (Information Data Management System) product based on Network data model.

RELATIONAL DATA MODEL

In 1970 E.F CODD introduce the Relational data model. Which are consists of a collection of 2D table.

A relational database uses this table for storing data or information. Relational Data Model mainly consists of 3 components these are.

  1. Collection of the database object (table, views, index)
  2. Set of the operator (>,<,/,*,-,+)
  3. Collection of integrity rules.

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