Basic SELECT - All Columns
Return every column from the employees table.
Exercise brief
Understand the request
HR analyst You are starting a basic employee roster pull and need the raw table first.
Retrieve every column for every employee from the employees table. This is the baseline "show me everything" query — useful when you are exploring a table for the first time.
Return
- Include all employee columns.
Constraints
- Use a basic SELECT against employees with no filters.
Data you will use
Review the relevant tables before deciding how to join, filter, or aggregate them.
employees
employee_idINTEGERfirst_nameVARCHAR(50)last_nameVARCHAR(50)emailVARCHAR(100)hire_dateDATEjob_idVARCHAR(20)salaryINTEGERmanager_idINTEGERdepartment_idINTEGER
Hints, when you need them
Open one clue at a time so you still do the reasoning.
Hint 1
You want every column, so reach for the SELECT * shortcut. Think of `*` as "all columns of the FROM table".
Hint 2
Syntax: SELECT * FROM <table_name>; Always end with a semicolon and make sure the table name is spelled exactly as in the schema browser.
Hint 3
Start with SELECT *, then add the employees table as the source.
Verified SQL answer
Attempt the problem first, then compare structure and reasoning—not just syntax.
Reveal solution and explanation
SELECT * FROM employees;Why this works
`SELECT *` projects every column of the FROM table in the order they were defined. It is the fastest way to peek at unfamiliar data, but in production code you should usually list columns explicitly so the query stays stable when the schema evolves.
Success check
Every employees row is returned with every source column, without filtering or changing the table grain.
Expected result
Use this output to verify values, aliases, ordering, and row count.
| employee_id | first_name | last_name | hire_date | job_id | salary | manager_id | department_id | |
|---|---|---|---|---|---|---|---|---|
| 100 | John | Smith | john.smith@company.com | 2020-01-15 | IT_MGR | 120000 | NULL | 10 |
| 101 | Alice | Johnson | alice.johnson@company.com | 2021-03-20 | IT_PROG | 85000 | 100 | 10 |
| 102 | Bob | Wilson | bob.wilson@company.com | 2021-06-10 | IT_PROG | 80000 | 100 | 10 |
| 103 | Carol | Davis | carol.davis@company.com | 2019-09-05 | HR_REP | 60000 | NULL | 20 |
| 104 | David | Brown | david.brown@company.com | 2022-02-14 | FIN_ANALYST | 70000 | NULL | 30 |
| 105 | Emma | Taylor | emma.taylor@company.com | 2020-11-30 | MKT_MGR | 95000 | NULL | 40 |
| 106 | Frank | Green | frank.green@company.com | 2021-08-25 | SALES_REP | 65000 | 105 | 40 |
| 107 | Grace | White | grace.white@company.com | 2019-05-12 | IT_PROG | 90000 | 100 | 10 |
| 108 | Henry | Clark | henry.clark@company.com | 2022-07-18 | HR_REP | 55000 | 103 | 20 |
| 109 | Ivy | Martinez | ivy.martinez@company.com | 2023-01-10 | FIN_ANALYST | 68000 | 104 | 30 |
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