1. Lighthouse

Level 7 · Team size per manager

The request

From Nicole Bennett, HR Business Partner

“We're reviewing span of control before the 2026 reorg. For every manager, how many people report to them directly, and what's the average salary on their team?”

Your goal

Join employees to itself (each employee to their manager through manager_id). Return one row per employee who has at least one direct report, with: manager_name (the manager's first_name, a space, last_name), title (the manager's title), direct_reports (number of employees whose manager_id is that manager) and avg_report_salary (average salary of those direct reports, rounded to 0). Sort by direct_reports descending, then manager_name ascending.

  • Read from the employees tablenot done yet
  • Show exactly manager_name title direct_reports avg_report_salarynot done yet
  • 12 rows, sorted as askednot done yet

Your query

SQL

Loading the editor…

    ResultPreview of employees · press Run to see yours
    Preview of employees
    employee_idfirst_namelast_namedepartmenttitle
    1CatherineHaleExecutiveChief Executive Officer
    2RobertKimExecutiveChief Operating Officer
    3MeganCollinsSalesHead of Sales
    4ChloeGutierrezSalesAccount Executive

    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.

    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
    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
    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
    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
    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

    A self-join reads one table twice under two aliases. In employees, every row is a person and manager_id points to another row of the same table. Giving the table two names lets you treat one copy as “the report” and the other as “the manager”.

    Recap: two roles, one table

    SELECT e.first_name || ' ' || e.last_name AS employee_name,
           e.department,
           m.first_name || ' ' || m.last_name AS manager_name,
           m.department AS manager_department
    FROM employees AS e
    JOIN employees AS m ON m.employee_id = e.manager_id
    WHERE e.department <> m.department;

    This lists the people whose manager sits in another department: 8 rows, all department heads reporting to Catherine Hale or Robert Kim in Executive. The direction of the join condition carries the meaning: m.employee_id = e.manager_id reads “m is the manager of e”.

    For the ticket, the same join is followed by a GROUP BY on the manager. After the join there is one row per report, so counting rows per manager counts their direct reports. The inner join drops anyone with no reports, which is exactly the “at least one direct report” rule. Only 12 of the 60 employees manage someone. If HR also wanted the people who manage nobody, with 0 reports, you would start from the manager copy and LEFT JOIN the reports instead.

    Group by m.employee_id as well as the name columns. Two managers could share a name; the id keeps them apart even when you only display the name.

    Common mistakes

    • Reversed condition. ON m.manager_id = e.employee_id makes m the report and e the manager. The query still runs and returns plausible but wrong teams.
    • Averaging the wrong alias. AVG(m.salary) is the manager’s own salary repeated on every row.
    • Direct versus all reports. This counts direct reports only. Someone reporting to a team lead who reports to a head is not counted for the head. Walking the whole chain needs a recursive query, which appears later in the track.

    In SQL Server

    String concatenation uses + or CONCAT: m.first_name + ' ' + m.last_name AS manager_name. CONCAT also treats NULL as an empty string, while + returns NULL if any part is NULL. || exists only in the newest versions (Azure SQL, SQL Server 2025), so do not count on it.

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