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Day 13 of the #HTTDatachallange. It gets more interesting, using (SQL)Sub queries to figure out the customer who has made orders above average order value.Every step brings us closer to a solution. π€π.
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Day 13 of @hertechtrail #HTTDataChallenge task: find customers who have made orders above the average order value.
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@Ogbonna42449096 @AtiJoshua
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Mastering SQL Subqueries is key to efficient data manipulation, playing an important role in filtering, comparing, and aggregating data for optimizing database ops & reporting
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value.
-The main query pulls out customers who spend more than that. @hertechtrail @phaibooboo @it_is_reel @preciey_oma @ogbonna42449096 @som_nnamani @mychailblaise @AtiJoshua. #hertechtrailacademy #HTTDataChallenge #SQLSubqueries #DataAnalysis #Day13.
Query Breakdownπ
The inner query calculates the average order value.
The outer query selects customers whose total order amount exceeds this average.
DISTINCT ensures each customer appears only once.
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SQL Query:
SELECT o.account_id, https://t.co/vOGBS1f95b_amt_usd
FROM orders o
WHERE https://t.co/vOGBS1f95b_amt_usd >
(SELECT AVG(total_amt_usd)
FROM orders);
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#SQLSubqueries #DataAnalysis
A Subquery is a query within another SQL statement.
Using a subquery, I retrieved the customers (using customer id) who have made orders above the average order value which is $3,348.02
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#SQLSubqueries #DataAnalysis @tech_bella @it_is_reel
The main query retrieves the names of customers, their order IDs, and the order amounts from the accounts and orders tables. The JOIN operation links customers (accounts) with their respective orders (orders).
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