#sqlsubqueries ผลการค้นหา
Day 16 of #20dayswithdata. Using a subquery in the WHERE clause, I determined the customers who have made orders above the average order value. The purpose of the subquery is to help filter out customers who haven't met the specified criteria. #SQLSubqueries
Completing MySQL without solving these questions is incomplete Have a look!!☑️🏁 #sqlsubqueries #subqueries #mysql
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.
Day 16: Subqueries Find customers who have made orders above the average order value #20dayswithdata #SQLSubqueries #DataAnalysis
Day 16 #20Dayswithdata Used subquery to calculate the overall average order value, then I filtered out orders that are less than the overall order value. #SQLSubqueries #DataAnalysis
Day 16. Today, we write a subquery. Lets gooooo!!! You can use the hashtags #20dayswithdata #SQLSubqueries #DataAnalysis.
Day 16:Subqueries I used a subquery to find Customers who have made orders above the Average order value which is 6.30. #SQLsubqueries #DataAnalytics #20dayswithdata #hertechtraialacademy @phaibooboo @ImaNjokko @fresh_gb @vicSomadina @AtiJoshua @OMOTOSHOOLAMI15
💙Practice SQL💙 Using the tables below, write a query to find employees whose salary is higher than the average salary of employees in their respective departments. #sql #thesqltribe #sqlsubqueries
Day 16 Subqueries to SQL queries. I wrote the query to retrieve the details of customers who bought less than the average amount of sales. I got the hang of using subqueries today. #20dayswithdata #SQLSubqueries #DataAnalysis
Day 15 SQL Query to calculate total sales and average sales by city. I have to come back to this because I have not gotten the proper hang of it. #20dayswithdata #SQLAggregation #DataAnalytics
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 #hertechtrailacademy #HTTDataChallenge #SQLSubqueries #DataAnalysis @tech_bella @it_is_reel
5/10: Get Comfortable with Subqueries Learn how to use subqueries (queries within queries) to perform more complex data retrievals. #SQLSubqueries #AdvancedSQL
Day 13: SQL Subqueries I was tasked with using a subquery to find customers who have made orders above the average order value. #hertechtrailacademy #HTTDataChallenge #SQLSubqueries #DataAnalysis
Day 16 #20dayswithdata #sqlsubqueries, #dataanalysis 188 made orders above the average order value out of 351 clients @phaibooboo @ImaNjokko @fresh_gb @vicSomadina @AtiJoshua @OMOTOSHOOLAMI15
Day 16. Today, we write a subquery. Lets gooooo!!! You can use the hashtags #20dayswithdata #SQLSubqueries #DataAnalysis.
Day 16: Subqueries 20 Days With Data Challenge I Wrote an SQL query using a subquery to find customers who have made orders above the average order value. #20dayswithdata #SQLSubqueries #DataAnalysis
Day 16: Subquery Using SQL subquery, I wrote a query to return customers who made orders greater than the average order value #20dayswithdata #SQLSubqueries #DataAnalysis
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). #HerTechTrailAcademy #HTTDataChallenge #SQLSubqueries #DataAnalytics
Query Breakdown👇 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. #hertechtrailacademy #SQLSubqueries @hertechtrail @phaibooboo @it_is_reel
📊 Day 16 of the #20DaysWithData Challenge! Challenge: Find customers who ordered above average. @phaibooboo , @ImaNjokko , @fresh_gb , @vicSomadina , @AtiJoshua , @OMOTOSHOOLAMI15 #SQLSubqueries #DataAnalysis #TechTrailAcademy #DataChallenge
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 Breakdown👇 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. #hertechtrailacademy #SQLSubqueries @hertechtrail @phaibooboo @it_is_reel
SQL Query: SELECT o.account_id, o.total_amt_usd FROM orders o WHERE _amt_usd > (SELECT AVG(total_amt_usd) FROM orders); #hertechtrailacademy #HTTDataChallenge #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 #hertechtrailacademy #HTTDataChallenge #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). #HerTechTrailAcademy #HTTDataChallenge #SQLSubqueries #DataAnalytics
Day 13: SQL Subqueries I was tasked with using a subquery to find customers who have made orders above the average order value. #hertechtrailacademy #HTTDataChallenge #SQLSubqueries #DataAnalysis
🃏 Lost in the sea of #SQLSubqueries? 😅 Here's a lifesaver: Scalar Subqueries are like a message in a bottle - just one row, one column. Multi-Row Subqueries? They're the party boat of SQL!
💙Practice SQL💙 Using the tables below, write a query to find employees whose salary is higher than the average salary of employees in their respective departments. #sql #thesqltribe #sqlsubqueries
Completing MySQL without solving these questions is incomplete Have a look!!☑️🏁 #sqlsubqueries #subqueries #mysql
Day 16 of #20dayswithdata. Using a subquery in the WHERE clause, I determined the customers who have made orders above the average order value. The purpose of the subquery is to help filter out customers who haven't met the specified criteria. #SQLSubqueries
Completing MySQL without solving these questions is incomplete Have a look!!☑️🏁 #sqlsubqueries #subqueries #mysql
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.
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 #hertechtrailacademy #HTTDataChallenge #SQLSubqueries #DataAnalysis @tech_bella @it_is_reel
Day 16:Subqueries I used a subquery to find Customers who have made orders above the Average order value which is 6.30. #SQLsubqueries #DataAnalytics #20dayswithdata #hertechtraialacademy @phaibooboo @ImaNjokko @fresh_gb @vicSomadina @AtiJoshua @OMOTOSHOOLAMI15
Day 16 #20Dayswithdata Used subquery to calculate the overall average order value, then I filtered out orders that are less than the overall order value. #SQLSubqueries #DataAnalysis
Day 16 #20dayswithdata #sqlsubqueries, #dataanalysis 188 made orders above the average order value out of 351 clients @phaibooboo @ImaNjokko @fresh_gb @vicSomadina @AtiJoshua @OMOTOSHOOLAMI15
Day 16. Today, we write a subquery. Lets gooooo!!! You can use the hashtags #20dayswithdata #SQLSubqueries #DataAnalysis.
Day 16. Today, we write a subquery. Lets gooooo!!! You can use the hashtags #20dayswithdata #SQLSubqueries #DataAnalysis.
Day 16 Subqueries to SQL queries. I wrote the query to retrieve the details of customers who bought less than the average amount of sales. I got the hang of using subqueries today. #20dayswithdata #SQLSubqueries #DataAnalysis
Day 15 SQL Query to calculate total sales and average sales by city. I have to come back to this because I have not gotten the proper hang of it. #20dayswithdata #SQLAggregation #DataAnalytics
Day 16: Subqueries Find customers who have made orders above the average order value #20dayswithdata #SQLSubqueries #DataAnalysis
📊 Day 16 of the #20DaysWithData Challenge! Challenge: Find customers who ordered above average. @phaibooboo , @ImaNjokko , @fresh_gb , @vicSomadina , @AtiJoshua , @OMOTOSHOOLAMI15 #SQLSubqueries #DataAnalysis #TechTrailAcademy #DataChallenge
💙Practice SQL💙 Using the tables below, write a query to find employees whose salary is higher than the average salary of employees in their respective departments. #sql #thesqltribe #sqlsubqueries
Day 13: SQL Subqueries I was tasked with using a subquery to find customers who have made orders above the average order value. #hertechtrailacademy #HTTDataChallenge #SQLSubqueries #DataAnalysis
Day 16: Subquery Using SQL subquery, I wrote a query to return customers who made orders greater than the average order value #20dayswithdata #SQLSubqueries #DataAnalysis
Day 16: Subqueries 20 Days With Data Challenge I Wrote an SQL query using a subquery to find customers who have made orders above the average order value. #20dayswithdata #SQLSubqueries #DataAnalysis
Something went wrong.
Something went wrong.
United States Trends
- 1. #UFC321 113K posts
- 2. Gane 128K posts
- 3. South Carolina 12.3K posts
- 4. Aspinall 115K posts
- 5. Jon Jones 10.9K posts
- 6. Ryan Williams N/A
- 7. Mizzou 5,271 posts
- 8. Liverpool 174K posts
- 9. Ty Simpson 1,700 posts
- 10. Iowa State 4,905 posts
- 11. Vandy 7,384 posts
- 12. Arch 18.7K posts
- 13. Mateer 5,999 posts
- 14. Matt Zollers N/A
- 15. Aaron Henry N/A
- 16. Sark 4,579 posts
- 17. June Lockhart 5,204 posts
- 18. Sellers 11.4K posts
- 19. Kirby Moore N/A
- 20. Pribula 1,251 posts