The request

From Laura Bennett, Head of Finance
Your goal
From employees, return employee_id, full_name (first_name, a space, then last_name, as one text value), department, salary and monthly_salary (salary divided by 12, rounded to 2 decimals). Include every employee.
- Read from the
employeestablenot done yet - Show exactly
employee_idfull_namedepartmentsalarymonthly_salarynot done yet - 60 rowsnot done yet
Your query
Loading the editor…
Reference solution
| employee_id | first_name | last_name | department | title |
|---|---|---|---|---|
| 1 | Catherine | Hale | Executive | Chief Executive Officer |
| 2 | Robert | Kim | Executive | Chief Operating Officer |
| 3 | Megan | Collins | Sales | Head of Sales |
| 4 | Chloe | Gutierrez | Sales | Account Executive |
Mote checks your result
Press Run. Each row that matches the goal becomes a firefly in your lantern.
What Laura gets, and why
Tables
Harbor & Pine store data, ready to query.
employees60 rows · 8 columns
employee_idintegerfirst_namevarcharlast_namevarchardepartmentvarchartitlevarcharmanager_idintegerhire_datedatesalaryinteger
| employee_id | first_name | last_name | department | title | manager_id | hire_date | salary |
|---|---|---|---|---|---|---|---|
| 1 | Catherine | Hale | Executive | Chief Executive Officer | NULL | 2016-03-01 | 285000 |
| 2 | Robert | Kim | Executive | Chief Operating Officer | 1 | 2017-01-09 | 235000 |
| 3 | Megan | Collins | Sales | Head of Sales | 1 | 2018-04-16 | 172000 |
| 4 | Chloe | Gutierrez | Sales | Account Executive | 3 | 2020-01-21 | 72000 |
| 5 | Frank | Bell | Sales | Account Executive | 3 | 2023-05-21 | 73000 |
customers2,018 rows · 9 columns
customer_idintegerfirst_namevarcharlast_namevarcharemailvarcharcityvarcharstatevarcharsignup_datedatesegmentvarcharreferral_sourcevarchar
| customer_id | first_name | last_name | city | state | signup_date | segment | referral_source | |
|---|---|---|---|---|---|---|---|---|
| 1 | Owen | Hudson | owen.hudson@icloud.com | San Francisco | CA | 2022-06-02 | consumer | search |
| 2 | Douglas | Mendoza | dmendoza69@gmail.com | Atlanta | GA | 2022-06-02 | consumer | NULL |
| 3 | Henry | Brooks | hbrooks@lakesidecafe.com | Los Angeles | CA | 2022-06-04 | business | NULL |
| 4 | Brian | Graham | bgraham@bluecedarhomes.com | Seattle | WA | 2022-06-06 | business | |
| 5 | Kyle | Jimenez | kjimenez27@yahoo.com | Indianapolis | IN | 2022-06-07 | consumer | NULL |
products120 rows · 8 columns
product_idintegernamevarcharcategoryvarcharsubcategoryvarcharunit_pricedecimalunit_costdecimallaunched_ondateis_activeboolean
| product_id | name | category | subcategory | unit_price | unit_cost | launched_on | is_active |
|---|---|---|---|---|---|---|---|
| 101 | Vale Velvet Loveseat | Furniture | Sofas | 1659.00 | NULL | 2023-09-11 | true |
| 102 | Alder Oak Coffee Table | Furniture | Tables | 919.00 | 503.50 | 2024-05-16 | true |
| 103 | Orchard Rattan Dining Chair | Furniture | Chairs | 789.00 | 429.87 | 2023-05-27 | true |
| 104 | Upland Oak Bookcase | Furniture | Storage | 429.00 | 214.70 | 2022-12-20 | true |
| 105 | Avery Leather Bed Frame | Furniture | Beds | 449.00 | 232.70 | 2021-08-31 | true |
orders12,000 rows · 7 columns
order_idintegercustomer_idintegerorder_datetimestampstatusvarcharchannelvarcharshipping_feedecimalcoupon_codevarchar
| order_id | customer_id | order_date | status | channel | shipping_fee | coupon_code |
|---|---|---|---|---|---|---|
| 1001 | 125 | 2023-01-01 20:51:19 | completed | web | 0.00 | NULL |
| 1002 | 156 | 2023-01-02 07:58:46 | completed | web | 0.00 | NULL |
| 1003 | 22 | 2023-01-02 10:25:27 | completed | marketplace | 4.99 | WELCOME10 |
| 1004 | 48 | 2023-01-02 11:21:51 | completed | marketplace | 4.99 | WELCOME10 |
| 1005 | 82 | 2023-01-02 11:43:36 | completed | web | 0.00 | WELCOME10 |
order_items30,338 rows · 6 columns
order_item_idintegerorder_idintegerproduct_idintegerquantityintegerunit_pricedecimaldiscount_pctdecimal
| order_item_id | order_id | product_id | quantity | unit_price | discount_pct |
|---|---|---|---|---|---|
| 1 | 1001 | 121 | 9 | 31.99 | 0.00 |
| 2 | 1001 | 154 | 3 | 11.99 | 0.00 |
| 3 | 1002 | 154 | 4 | 11.99 | 0.00 |
| 4 | 1002 | 194 | 1 | 149.00 | 0.00 |
| 5 | 1002 | 193 | 2 | 19.99 | 0.00 |
returns1,673 rows · 5 columns
return_idintegerorder_item_idintegerreturned_ondatereasonvarcharrefund_amountdecimal
| return_id | order_item_id | returned_on | reason | refund_amount |
|---|---|---|---|---|
| 1 | 14 | 2023-01-10 | damaged | 83.69 |
| 2 | 42 | 2023-01-10 | wrong_item | 19.99 |
| 3 | 105 | 2023-01-14 | wrong_item | 10.99 |
| 4 | 24 | 2023-01-16 | changed_mind | 26.99 |
| 5 | 126 | 2023-01-16 | late | 20.99 |
web_sessions40,000 rows · 7 columns
session_idintegercustomer_idintegerstarted_attimestampdevicevarcharsourcevarcharpages_viewedintegerconvertedboolean
| session_id | customer_id | started_at | device | source | pages_viewed | converted |
|---|---|---|---|---|---|---|
| 1 | NULL | 2023-01-01 23:02:24 | mobile | paid | 1 | false |
| 2 | 18 | 2023-01-01 15:07:49 | desktop | paid | 1 | false |
| 3 | NULL | 2023-01-01 16:55:46 | desktop | direct | 7 | false |
| 4 | NULL | 2023-01-01 12:43:28 | mobile | organic | 3 | false |
| 5 | NULL | 2023-01-01 13:06:21 | mobile | social | 2 | false |
marketing_spend3,276 rows · 3 columns
spend_datedatechannelvarcharamountdecimal
| spend_date | channel | amount |
|---|---|---|
| 2023-01-01 | paid | 492.99 |
| 2023-01-01 | 37.38 | |
| 2023-01-01 | social | 200.53 |
| 2023-01-02 | paid | 709.13 |
| 2023-01-02 | 64.13 |
The lesson
This ticket uses the moves from the margin level, on a new table: employees, one row per person
at Harbor & Pine, with a yearly salary in whole dollars. Two columns are built rather than picked:
one from text, one from numbers.
Gluing text and doing math in the SELECT list
|| is the SQL operator that joins text values end to end. Put a literal space between the names,
or they run together. Arithmetic works the same way, one row at a time:
SELECT
first_name || ' ' || last_name AS full_name,
salary,
ROUND(salary / 12.0, 2) AS monthly_salary
FROM employees;
The first two rows are Catherine Hale, 285,000 a year and 23,750 a month, and Robert Kim, 235,000 a
year and 19,583.33 a month. CONCAT(first_name, ' ', last_name) gives the same text and is
available in almost every database.
salary / 12.0 uses 12.0 on purpose. DuckDB, the engine in this game, returns a decimal for
salary / 12 anyway, but several databases throw the remainder away when both sides are integers.
Writing 12.0 makes the division decimal everywhere, so the query survives being pasted into the
company warehouse.
Common mistakes
- Concatenating a column that can be NULL. With
||, one NULL makes the whole string NULL. No employee name is missing here, but the next levels deal with it. - Rounding too early. Round once, in the final column. A rounded monthly figure multiplied back by 12 drifts away from the real salary.
- Writing
first_name + ' ' + last_name. In DuckDB and Postgres+is for numbers only, so the database tries to add text and reports an error. Use||orCONCATfor text. - Calling the new column
name. It works, butfull_namesays what is in it, and the products table already has anamecolumn that means something else. - Dropping the original column. Keep
salarynext tomonthly_salary, so the reader can check the math on any row by eye. Laura asked for both on purpose.
In SQL Server
SQL Server joins text with + (or CONCAT), and salary / 12 on an INT column truncates to a whole
number there:
SELECT FirstName + ' ' + LastName AS FullName,
ROUND(Salary / 12.0, 2) AS MonthlySalary
FROM Employees; Lantern lit!
Practised: select columnsexpressionsconcatenationaliasround
- Solved
- No hints
- First run
