Why SQL is the standard database language in DBMS Theory - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to select all records from a table named 'employees'.

DBMS Theory

SELECT * FROM [1];

Drag options to blanks, or click blank then click option'

Aemployees

Bproducts

Corders

Dcustomers

Attempts:

3 left

💡 Hint

Common Mistakes

Using a wrong table name.

Forgetting the FROM keyword.

The SQL command SELECT * FROM employees; retrieves all records from the 'employees' table.

2fill in blank

medium

Complete the code to filter records where the age is greater than 30.

DBMS Theory

SELECT * FROM employees WHERE age [1] 30;

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A<=

B<

C=

D>

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>'.

Using '=' which selects only age exactly 30.

The operator > means 'greater than', so this query selects employees older than 30.

3fill in blank

hard

Fix the error in the SQL query to count the number of employees.

DBMS Theory

SELECT COUNT([1]) FROM employees;

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A*

Bname

Cage

Dsalary

Attempts:

3 left

💡 Hint

Common Mistakes

Using COUNT(name) which ignores rows with null names.

Using COUNT(age) which ignores rows with null ages.

Using COUNT(*) counts all rows regardless of null values in any column.

4fill in blank

hard

Fill both blanks to create a query that selects employee names and orders them alphabetically.

DBMS Theory

SELECT [1] FROM employees ORDER BY [2];

Drag options to blanks, or click blank then click option'

Aname

Bage

Dsalary

Attempts:

3 left

💡 Hint

Common Mistakes

Selecting one column but ordering by a different one.

Ordering by a numeric column instead of name.

Selecting name and ordering by name lists employees alphabetically.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps employee names to their salaries if salary is above 50000.

DBMS Theory

{ [1]: [2] for [3] in employees if [3]['salary'] > 50000 }

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Aemployee['name']

Bemployee['salary']

Cemployee

Dsalary

Attempts:

3 left

💡 Hint

Common Mistakes

Using salary as the loop variable instead of employee.

Mixing keys and values incorrectly.

This comprehension creates a dictionary with employee names as keys and salaries as values, filtering salaries above 50000.