Lighthouse

Level 5 · Boss: catalog snapshot

From Jessica Turner, Merchandising Manager

“The board meeting is Thursday and I need a quick catalog snapshot: a price list with our planned 10% sale price, the cost share of each price, and a clean list of the sales channels and order statuses we use.”

Your goal

Step 1 of 3. From products, return product_id, name, unit_price and sale_price, where sale_price is unit_price reduced by 10%, rounded to 2 decimals.

Read from the products tablenot done yet
Show exactly product_id name unit_price sale_pricenot done yet
120 rowsnot done yet

Step 1 · your query

SQL

Loading the editor…

Reference solution

ResultPreview of products · press Run to see yours

Preview of products
product_id	name	category	subcategory	unit_price
101	Vale Velvet Loveseat	Furniture	Sofas	1659.00
102	Alder Oak Coffee Table	Furniture	Tables	919.00
103	Orchard Rattan Dining Chair	Furniture	Chairs	789.00
104	Upland Oak Bookcase	Furniture	Storage	429.00

Mote checks your result

Press Run. Each row that matches the goal becomes a firefly in your lantern.

Step 2 · your query

SQL

Loading the editor…

Reference solution

ResultPreview of products · press Run to see yours

Preview of products
product_id	name	category	subcategory	unit_price
101	Vale Velvet Loveseat	Furniture	Sofas	1659.00
102	Alder Oak Coffee Table	Furniture	Tables	919.00
103	Orchard Rattan Dining Chair	Furniture	Chairs	789.00
104	Upland Oak Bookcase	Furniture	Storage	429.00

Mote checks your result

Press Run. Each row that matches the goal becomes a firefly in your lantern.

Step 3 · your query

SQL

Loading the editor…

Reference solution

ResultPreview of orders · press Run to see yours

Preview of orders
order_id	customer_id	order_date	status	channel
1001	125	2023-01-01 20:51:19	completed	web
1002	156	2023-01-02 07:58:46	completed	web
1003	22	2023-01-02 10:25:27	completed	marketplace
1004	48	2023-01-02 11:21:51	completed	marketplace

Mote checks your result

Press Run. Each row that matches the goal becomes a firefly in your lantern.

Tables

Harbor & Pine store data, ready to query.

products120 rows · 8 columns

product_idinteger
namevarchar
categoryvarchar
subcategoryvarchar
unit_pricedecimal
unit_costdecimal
launched_ondate
is_activeboolean

First 5 rows of products
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_idinteger
customer_idinteger
order_datetimestamp
statusvarchar
channelvarchar
shipping_feedecimal
coupon_codevarchar

First 5 rows of orders
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

customers2,018 rows · 9 columns

customer_idinteger
first_namevarchar
last_namevarchar
emailvarchar
cityvarchar
statevarchar
signup_datedate
segmentvarchar
referral_sourcevarchar

First 5 rows of customers
customer_id	first_name	last_name	email	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	pinterest
5	Kyle	Jimenez	kjimenez27@yahoo.com	Indianapolis	IN	2022-06-07	consumer	NULL

order_items30,338 rows · 6 columns

order_item_idinteger
order_idinteger
product_idinteger
quantityinteger
unit_pricedecimal
discount_pctdecimal

First 5 rows of order_items
order_item_id	order_id	product_id	quantity	unit_price
1	1001	121	9	31.99
2	1001	154	3	11.99
3	1002	154	4	11.99
4	1002	194	1	149.00
5	1002	193	2	19.99

returns1,673 rows · 5 columns

return_idinteger
order_item_idinteger
returned_ondate
reasonvarchar
refund_amountdecimal

First 5 rows of returns
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

employees60 rows · 8 columns

employee_idinteger
first_namevarchar
last_namevarchar
departmentvarchar
titlevarchar
manager_idinteger
hire_datedate
salaryinteger

First 5 rows of employees
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

web_sessions40,000 rows · 7 columns

session_idinteger
customer_idinteger
started_attimestamp
devicevarchar
sourcevarchar
pages_viewedinteger
convertedboolean

First 5 rows of web_sessions
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_datedate
channelvarchar
amountdecimal

First 5 rows of marketing_spend
spend_date	channel	amount
2023-01-01	paid	492.99
2023-01-01	email	37.38
2023-01-01	social	200.53
2023-01-02	paid	709.13
2023-01-02	email	64.13

The lesson

Boss levels are small cases. Each step is checked on its own, and together they answer the full request. This one uses everything from the chapter: choosing columns, computing new ones, naming them, rounding, and removing duplicates.

Step 1: the sale price list

A 10% discount means the customer pays 90% of the price, so the sale price is unit_price * 0.9. Writing it as a multiplication is clearer and less error-prone than unit_price - unit_price * 0.1, though both give the same answer. Round the result to cents and give it a readable alias:

ROUND(unit_price * 0.9, 2) AS sale_price

Keep the original unit_price next to it. People reading a price sheet want to compare the two numbers side by side, and an analyst who shows the input next to the output makes mistakes easy to spot.

Finance teams often talk about cost as a share of price (the inverse view of margin). If a lamp sells for 80 and costs 32, the cost share is 40%. The expression is unit_cost / unit_price * 100. Some products have no recorded cost, so their cost share is NULL. Leave those as NULL: an unknown cost is not a zero cost, and filling in 0 would make those items look like pure profit on the board slide.

A quick sanity check analysts do on a column like this: is every value between 0 and 100? A cost share above 100 means the product sells at a loss, which is worth flagging to Jessica rather than quietly passing on.

Step 3: channels and statuses

SELECT DISTINCT channel, status FROM orders lists each combination once. With three channels and four statuses you would expect at most twelve rows. If you see fewer, some combination never happens. If you see more, the data has spelling variants, and that is a finding in itself.

What a reviewer would check

Every computed column has a clear alias.
Rounding happens once, on the final value.
NULLs are left as NULL unless there is a business reason to fill them.
The result has only the columns that were asked for.

Those four habits will save you from most of the comments you would get in a code review as a junior analyst.

Level 5 · Boss: catalog snapshot

Your goal

Step 1 · your query

Reference solution

Mote checks your result

Step 2 · your query

Reference solution

Mote checks your result

Step 3 · your query

Reference solution

Mote checks your result

What Jessica gets, and why

Tables

The lesson

Step 1: the sale price list

Step 3: channels and statuses

What a reviewer would check

Lantern lit!

Level 5 · Boss: catalog snapshot

The request

Your goal

Step 1 · your query

Reference solution

Mote checks your result

Step 2 · your query

Reference solution

Mote checks your result

Step 3 · your query

Reference solution

Mote checks your result

What Jessica gets, and why

Tables

The lesson

Step 1: the sale price list

Step 2: cost share

Step 3: channels and statuses

What a reviewer would check