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Computer Awareness for Exams like IBPS PO, SO, Clerical, SBI, RBI

and others.

Computer Knowledge and Awareness is an important section in many govt. exams like IBPS PO,

IBPS SO, IBPS Clerical, SBI PO, SBI clerical and others. Also, during the Interviews especially in

IBPS Specialist officers interview , questions are asked which are related computer field.

Therefore, it is important to prepare Computer Awareness section well.

This series of Article on Computer Awareness gives you some of the important bits

of information related to computers. Some of the topics that will be covered in this are DBMS,

Computer Networks, Network Security, Web Technologies, E-Banking etc. It will surely help the

students in their exam preparations.

DBMS - Basic concepts for Bank Exams:

1. What is DBMS?

o DBMS means a collection of inter-related data and a set of programs to access

that data. The primary goal of a DBMS is to provide a way to store and retrieve

data in an efficient manner.

2. What is a Database?

o Database is a collection of inter-related data items.

3. Why one should use DBMS?

o DBMS should be used to :

Prevent Data Redundancy and Inconsistency.

keep the Data Secure.

easily access the Data.

Access data concurrently while maintaining Atomicity and Integrity of

Data.

4. What is Data Redundancy?

o Duplication of Data is called as Data Redundancy

5. What do you mean by Atomicity of Data?

o Atomicity of Data means that either all the required operations take place on the

data item or none of them takes place. There is no scope for 'Some' operations

taking place.

6. What are the different Levels of Data Abstraction?

o Data Abstraction means hiding the complexities from users. Three levels of

Abstraction in DBMS:

Physical Abstraction - At Physical Level.

Logical Abstraction- At Logical Level.Hiding the details about data and

the relation between data.

View Level- Showing only part of the database to the users.

7. What is Database Schema?

o The overall design of the Database is known as Database Schema.

8. What is Instance of a Database?

o The collection of information stored in a database at any point of time is the

Instance of a Database.

9. What is a Data Model?

o Data Model is a way to describe the design of a Database. It is a tool for

describing data, data relationship, data semantics and the constraints.

10. What is the Relational Data Model?

o The Relational Data model uses a collection of tables to represent both data and

the relationship among those data. Each table has a unique name and multiple

columns. Each column also has a unique name in a table.

11. What is E-R Model?

o E-R Data Model is based on the perception of real world that consists of basic

objects called entities and the relationships among those objects.

12. What is Object-based Data Model?

o It can be called as an extending E-R Model with Object oriented features like

Encapsulation, Methods etc.

13. What is DML?

o It stands for Data Manipulation Language. It lets users to access or manipulate

data by using database queries.

o 2 types - Procedural DMLs and Declarative DMLs.

o Procedural DMLs- Tells what data is needed and how to get that data.

o Declarative DMLs - only tells what data is needed.

14. What is a DDL?

o It stands for Data Definition Language. It is used to specify the database schema.

15. What do you mean by DATA DICTIONARY?

o Data Dictionary is a special type of Data Structure used by DBMS which contains

METADATA i.e. Data about Data.

o The output of DDLs are stored in the Data Dictionary.

o Data Dictionary can be accessed only by the DBMS and not the regular user.

16. What is a Transaction?

o A Transaction is a set of operations that performs a single logical function in a

database application.

17. What is Normalization?

o It is an approach to store information without unnecessary redundancy and yet

allows us to retrieve the information efficiently.

18. What is Data Mining?

o Data Mining is the process of analyzing the large databases to find useful

patterns. It attempts to discover rules and patterns from data.

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