1. Lighthouse

Level 6 · Black Friday in the ad platform's time zone

The request

From Jordan Reyes, Head of Marketing

“The ad platform reports Black Friday weekend by UTC day, and our order counts per day never match its conversion counts. Black Friday shows 56 orders on our side. Can you rebuild our side on UTC days so we compare like with like?”

Your goal

order_date is stored in store local time (US Eastern, no time zone attached); in late November 2025 Eastern time is UTC-5, so UTC = order_date + 5 hours. Fix the query: for orders (all statuses) whose UTC time falls from 2025-11-28 00:00 up to but not including 2025-12-02 00:00, return one row per UTC day with: utc_day (a DATE), orders and completed_orders (orders with status 'completed'). Sort by utc_day ascending.

  • Read from the orders tablenot done yet
  • Show exactly utc_day orders completed_ordersnot done yet
  • 4 rows, sorted as askednot done yet

Your query

SQL

Loading the editor…

    ResultPreview of orders · press Run to see yours
    Preview of orders
    order_idcustomer_idorder_datestatuschannel
    10011252023-01-01 20:51:19completedweb
    10021562023-01-02 07:58:46completedweb
    1003222023-01-02 10:25:27completedmarketplace
    1004482023-01-02 11:21:51completedmarketplace

    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.

    orders12,000 rows · 7 columns
    • order_idinteger
    • customer_idinteger
    • order_datetimestamp
    • statusvarchar
    • channelvarchar
    • shipping_feedecimal
    • coupon_codevarchar
    First 5 rows of orders
    order_idcustomer_idorder_datestatuschannelshipping_feecoupon_code
    10011252023-01-01 20:51:19completedweb0.00NULL
    10021562023-01-02 07:58:46completedweb0.00NULL
    1003222023-01-02 10:25:27completedmarketplace4.99WELCOME10
    1004482023-01-02 11:21:51completedmarketplace4.99WELCOME10
    1005822023-01-02 11:43:36completedweb0.00WELCOME10
    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_idfirst_namelast_nameemailcitystatesignup_datesegmentreferral_source
    1OwenHudsonowen.hudson@icloud.comSan FranciscoCA2022-06-02consumersearch
    2DouglasMendozadmendoza69@gmail.comAtlantaGA2022-06-02consumerNULL
    3HenryBrookshbrooks@lakesidecafe.comLos AngelesCA2022-06-04businessNULL
    4BrianGrahambgraham@bluecedarhomes.comSeattleWA2022-06-06businesspinterest
    5KyleJimenezkjimenez27@yahoo.comIndianapolisIN2022-06-07consumerNULL
    products120 rows · 8 columns
    • product_idinteger
    • namevarchar
    • categoryvarchar
    • subcategoryvarchar
    • unit_pricedecimal
    • unit_costdecimal
    • launched_ondate
    • is_activeboolean
    First 5 rows of products
    product_idnamecategorysubcategoryunit_priceunit_costlaunched_onis_active
    101Vale Velvet LoveseatFurnitureSofas1659.00NULL2023-09-11true
    102Alder Oak Coffee TableFurnitureTables919.00503.502024-05-16true
    103Orchard Rattan Dining ChairFurnitureChairs789.00429.872023-05-27true
    104Upland Oak BookcaseFurnitureStorage429.00214.702022-12-20true
    105Avery Leather Bed FrameFurnitureBeds449.00232.702021-08-31true
    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_idorder_idproduct_idquantityunit_pricediscount_pct
    11001121931.990.00
    21001154311.990.00
    31002154411.990.00
    410021941149.000.00
    51002193219.990.00
    returns1,673 rows · 5 columns
    • return_idinteger
    • order_item_idinteger
    • returned_ondate
    • reasonvarchar
    • refund_amountdecimal
    First 5 rows of returns
    return_idorder_item_idreturned_onreasonrefund_amount
    1142023-01-10damaged83.69
    2422023-01-10wrong_item19.99
    31052023-01-14wrong_item10.99
    4242023-01-16changed_mind26.99
    51262023-01-16late20.99
    employees60 rows · 8 columns
    • employee_idinteger
    • first_namevarchar
    • last_namevarchar
    • departmentvarchar
    • titlevarchar
    • manager_idinteger
    • hire_datedate
    • salaryinteger
    First 5 rows of employees
    employee_idfirst_namelast_namedepartmenttitlemanager_idhire_datesalary
    1CatherineHaleExecutiveChief Executive OfficerNULL2016-03-01285000
    2RobertKimExecutiveChief Operating Officer12017-01-09235000
    3MeganCollinsSalesHead of Sales12018-04-16172000
    4ChloeGutierrezSalesAccount Executive32020-01-2172000
    5FrankBellSalesAccount Executive32023-05-2173000
    web_sessions40,000 rows · 7 columns
    • session_idinteger
    • customer_idinteger
    • started_attimestamp
    • devicevarchar
    • sourcevarchar
    • pages_viewedinteger
    • convertedboolean
    First 5 rows of web_sessions
    session_idcustomer_idstarted_atdevicesourcepages_viewedconverted
    1NULL2023-01-01 23:02:24mobilepaid1false
    2182023-01-01 15:07:49desktoppaid1false
    3NULL2023-01-01 16:55:46desktopdirect7false
    4NULL2023-01-01 12:43:28mobileorganic3false
    5NULL2023-01-01 13:06:21mobilesocial2false
    marketing_spend3,276 rows · 3 columns
    • spend_datedate
    • channelvarchar
    • amountdecimal
    First 5 rows of marketing_spend
    spend_datechannelamount
    2023-01-01paid492.99
    2023-01-01email37.38
    2023-01-01social200.53
    2023-01-02paid709.13
    2023-01-02email64.13

    The lesson

    Two systems can count the same orders and still disagree every single day. If one counts by Eastern days and the other by UTC days, the evening orders land on different dates.

    Local time versus UTC

    Harbor & Pine stores order_date in store local time, US Eastern, as a plain TIMESTAMP with no time zone attached. Ad platforms usually report in UTC. In late November, Eastern Standard Time is UTC-5: an order at 21:30 on Friday, Nov 28 in New York is 02:30 on Saturday, Nov 29 in UTC.

    Orders peak in the evening, so this is not a rounding issue. From 19:00 to midnight on Black Friday alone, 18 orders move to the next UTC day.

    What the starter does

    It labels local days as utc_day, and filters on local time. Compare the two versions:

    utc_day starter (local days) fixed (UTC days)
    2025-11-28 56 43
    2025-11-29 51 55
    2025-11-30 58 59
    2025-12-01 67 53

    The UTC version of Nov 28 runs from 19:00 on Nov 27 to 19:00 on Nov 28 local time.

    The fix

    Convert once, then use the converted value everywhere:

    CAST(order_date + INTERVAL 5 HOUR AS DATE) AS utc_day
    ...
    WHERE order_date + INTERVAL 5 HOUR >= '2025-11-28'
      AND order_date + INTERVAL 5 HOUR < '2025-12-02'

    A fixed offset is correct here because the whole window falls in standard time: daylight saving time ended on Nov 2, 2025. Over a range that crosses a DST change, a fixed offset is wrong for part of it (Eastern is UTC-4 in summer), and you should use a real time zone conversion such as AT TIME ZONE 'America/New_York' in Postgres or Snowflake’s CONVERT_TIMEZONE, which know the DST calendar.

    Common mistakes

    • Shifting the label but not the filter: the window still starts and ends at local midnight, so the first and last UTC days are incomplete.
    • Subtracting instead of adding. UTC is ahead of US time zones.
    • Assuming a column’s time zone from its name. Check the data documentation or ask the engineer who owns the pipeline.

    In SQL Server

    SQL Server 2016+ converts with Windows zone names, which handle DST:

    SELECT CAST(order_date AT TIME ZONE 'Eastern Standard Time'
                           AT TIME ZONE 'UTC' AS date) AS utc_day
    FROM orders;

    The first AT TIME ZONE says what the stored value is; the second converts it. DATEADD(hour, 5, order_date) is the fixed-offset version.

    On the job

    Ad spend, web analytics and payment systems often each use a different clock. State the time zone next to every daily number you publish.

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