SQL - RDBMS Concepts Flashcards
RDBMS Concepts
RDBMS stands for
Relational Database Management System.
RDBMS Concepts
The data in an RDBMS is stored in database objects which are called as
tables
RDBMS Concepts
is basically a collection of related data entries and it consists of numerous columns and rows.
tables
RDBMS Concepts
Every table is broken up into smaller entities called
fields
RDBMS Concepts
is a column in a table that is designed to maintain specific information about every record in the table.
Answer: fields
+—-+———-+—–+———–+———-+
| ID | NAME | AGE | ADDRESS | SALARY |
+—-+———-+—–+———–+———-+
| 1 | Ramesh | 32 | Ahmedabad | 2000.00 |
| 2 | Khilan | 25 | Delhi | 1500.00 |
| 3 | kaushik | 23 | Kota | 2000.00 |
| 4 | Chaitali | 25 | Mumbai | 6500.00 |
| 5 | Hardik | 27 | Bhopal | 8500.00 |
| 6 | Komal | 22 | MP | 4500.00 |
| 7 | Muffy | 24 | Indore | 10000.00 |
+—-+———-+—–+———–+———-+
The fields in the CUSTOMERS
table consist of ID, NAME, AGE, ADDRESS and SALARY.
RDBMS Concepts
A record is also called as a _____ of data is each individual entry that exists in a table.
Answer: row
+—-+———-+—–+———–+———-+
| ID | NAME | AGE | ADDRESS | SALARY |
+—-+———-+—–+———–+———-+
| 1 | Ramesh | 32 | Ahmedabad | 2000.00 |
| 2 | Khilan | 25 | Delhi | 1500.00 |
| 3 | kaushik | 23 | Kota | 2000.00 |
| 4 | Chaitali | 25 | Mumbai | 6500.00 |
| 5 | Hardik | 27 | Bhopal | 8500.00 |
| 6 | Komal | 22 | MP | 4500.00 |
| 7 | Muffy | 24 | Indore | 10000.00 |
+—-+———-+—–+———–+———-+
There are 7 records in the table CUSTOMERS
RDBMS Concepts
is a horizontal entity in a table.
Answer: Record
+—-+———-+—–+———–+———-+
| 1 | Ramesh | 32 | Ahmedabad | 2000.00 |
+—-+———-+—–+———–+———-+
RDBMS Concepts
is a vertical entity in a table that contains all information associated with a specific field in a table.
Answer: Column
+———–+
| ADDRESS |
+———–+
| Ahmedabad |
| Delhi |
| Kota |
| Mumbai |
| Bhopal |
| MP |
| Indore |
+—-+——+
RDBMS Concepts
is a value in a field that appears to be blank (no value)
NULL
Identification
are the rules enforced on data columns on a table
Constraints
Identification
These are used to limit the type of data that can go into a table. This ensures the accuracy and reliability of the data in the database.
Constraints
SQL Constraints
are applied
only to one column
Column level constraints
SQL Constraints
are applied to the entire table
table level constraints
SQL Constraints
Ensures that a column cannot have a NULL value.
NOT NULL Constraint
SQL Constraints
Provides a default value for a column when none is specified.
DEFAULT Constraint
SQL Constraints
Ensures that all the values in a column are different.
UNIQUE Constraint
SQL Constraints
Uniquely identifies each row/record in a database table.
PRIMARY Key
SQL Constraints
Uniquely identifies a row/record in any another database table.
FOREIGN Key
SQL Constraints
ensures that all values in a column satisfy certain conditions.
CHECK Constraint
SQL Constraints
Used to create and retrieve data from the database very quickly.
INDEX
Data Integrity
There are no duplicate rows in a table.
Entity Integrity
Data Integrity
Enforces valid entries for a given column by restricting the
type, the format, or the range of values.
Domain Integrity
Data Integrity
Rows cannot be deleted, which are used by other records.
Referential integrity
Data Integrity
Enforces some specific business rules that do not fall
into entity, domain or referential integrity.
User-Defined Integrity
Data Integrity
These categories of data integrity exist with each RDBMS:
- Entity Integrity
- Domain Integrity
- Referential integrity
- User-Defined Integrity
Identification
is the process of efficiently organizing data in a database
Database normalization
Database Normalization
There are two reasons of this normalization process:
- Eliminating redundant data
- Ensuring data dependencies make sense
Database Normalization
Rules of First Normal form (1NF)
- Define the data items required, place the related data items in a table.
- Ensure that there are no repeating groups of data.
- Ensure that there is a primary key
Database Normalization
Rules of Second Normal form (2NF)
- Meet all the rules for 1NF
- Remove partial dependences of any of the columns on the primary key
Database Normalization
Rules of Third Normal form (3NF)
- Must be in 2NF
- Remove all transitive dependencies
Database Normalization
A functional dependency between two (or more) nonkey attributes
Transitive Dependency
Database Normalization
Q
a situation in which a non-key attribute of a table depends on only a part of the primary key.
Partial Dependency
