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πŸ“Š Power BI with Advanced SQL – New Course Batch Starts December 1st!
tr.ee/LBRnWU
⏰ 8:00 AM (IST)
πŸ‘©β€πŸ« Trainer: Ms. Mohana

#PowerBI #AdvancedSQL #DataAnalytics #BusinessIntelligence #PowerBITraining #SQLDeveloper #DataAnalyst #NareshIT #LearnPowerBI #DashboardDesign #BIAnalyst #CareerGrowth

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Online Power BI training poster by Naresh i Technologies featuring Ms. Mohana, covering analytics with basic to advanced SQL. Includes tools like Excel, SQL, Power Query, Power BI, and DAX. Training runs from August 5th to 16th, 2025 at 11:00 AM IST with Zoom registration link."

Online Power BI training poster by Naresh i Technologies featuring Ms. Mohana, covering analytics with basic to advanced SQL. Includes tools like Excel, SQL, Power Query, Power BI, and DAX. Training runs from August 5th to 16th, 2025 at 11:00 AM IST with Zoom registration link."

πŸ“Š Power BI + Advanced SQL = Your Shortcut to Data

Careers!πŸš€ Limited Slots – Register Now: tr.ee/dL0YOf

πŸ”₯ Master data visualization + backend querying

🧠 With expert trainer Ms. Mohana
πŸ“… Starts: 5th Aug @ 8:30 PM IST

#PowerBI #AdvancedSQL #DataAnalytics #NareshIT

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πŸ“Š Turn raw data into stunning dashboards!
Master Power BI + Advanced SQL with Mr. Vijay Rama Raju

πŸ“… Starts 16th July | πŸ•˜ 9:00 AM IST

πŸ”—Enroll Link: tr.ee/lQAPFm

#PowerBI #AdvancedSQL #DataVisualization #NareshIT #BItraining #TechSkills #freshers

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πŸ“ˆ Power BI + SQL = Career Power-Up πŸ’Ό
πŸ—“οΈ 26 June | πŸ•’ 7:30 PM IST

πŸ”—Register here: tr.ee/NMTMUl

πŸŽ™οΈ Free demo with Mr. Laxman

More Courses: linktr.ee/ITcoursesFre...

#PowerBI #AdvancedSQL #BITraining #NareshIT
#DataAnalytics #FreeClass #DataVisualization #LearnSQL

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πŸ“Š Power BI with Advanced SQL – Free Demo!

πŸ“… 26 June | πŸ•’ 7:30 PM IST

πŸŽ™οΈ By Mr. Laxman
πŸ”— Register here : tr.ee/NMTMUl

Build dashboards, master SQL & unlock data insights πŸ’‘

#PowerBI #AdvancedSQL #DataAnalytics #NareshIT #FreeDEMOCourse #BITraining #TechSkills #OnlineLearning

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 Power BI with Advanced SQL – Free Class!

Power BI with Advanced SQL – Free Class!

πŸ“Š Free Training: Power BI with Adv SQL
πŸ“… 12th June | ⏰ 8:30 AM IST
πŸ‘©β€πŸ« Ms. Mohana
πŸ”— tr.ee/ejeZjg
Learn Dashboards, Queries, Reports β€” for FREE!

#PowerBI #AdvancedSQL #TechSkills #BlueskyTech

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Ready to master data like a pro? πŸ“ˆ

Join Mr. Laxman for a FREE session on Power BI + Advanced SQL

πŸ—“οΈ 22nd May 2025 | πŸ•  5:30 PM IST

πŸ”— tr.ee/pUa84z
πŸ“š More free courses: linktr.ee/ITcoursesFre...

#PowerBI #AdvancedSQL #DataAnalytics #FreeTechCourses #LearnSQL #BItools #OnlineLearning #DataSkills

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10 SQL Anti-Patterns You Must Avoid in Production ## 10 SQL Anti-Patterns You Must Avoid in Production > β€œSlow SQL isn’t always about bad servers β€” it’s often about bad habits.” As SQL developers and data engineers, we often prioritize functionality and overlook **query quality**. But poor SQL habits can lead to: * Long response times * Bottlenecked applications * Excessive I/O and CPU * Poor scalability In this post, we’ll break down 10 critical **SQL anti-patterns** and how to fix them. ## ❌ 1. N+1 Query Pattern **Problem:** Querying in a loop for each record. -- BAD: Fetching orders per customer inside loop SELECT * FROM Customers; -- For each customer: SELECT * FROM Orders WHERE customer_id = ?; βœ… **Fix:** Join and aggregate in one query SELECT c.id, c.name, COUNT(o.id) AS order_count FROM Customers c LEFT JOIN Orders o ON o.customer_id = c.id GROUP BY c.id, c.name; ## ❌ 2. Wildcard Index Scans **Problem:** Leading wildcard disables index usage. SELECT * FROM Products WHERE name LIKE '%phone'; βœ… **Fix:** Use full-text search or structured LIKE -- Better (index usable) SELECT * FROM Products WHERE name LIKE 'phone%'; ## ❌ 3. Implicit Data Type Conversions **Problem:** Filtering numeric column with a string. SELECT * FROM Orders WHERE id = '123'; βœ… **Fix:** Match types explicitly SELECT * FROM Orders WHERE id = 123; πŸ” Use query plans to detect implicit conversion overhead. ## ❌ 4. Scalar Subqueries in SELECT **Problem:** Executing subquery for every row. SELECT id, (SELECT COUNT(*) FROM OrderItems WHERE order_id = o.id) FROM Orders o; βœ… **Fix:** Use join and aggregation SELECT o.id, COUNT(oi.id) AS item_count FROM Orders o LEFT JOIN OrderItems oi ON oi.order_id = o.id GROUP BY o.id; ## ❌ 5. SELECT * in Production **Problem:** Fetches unnecessary columns, causes bloat. SELECT * FROM Transactions; βœ… **Fix:** Select only what you need SELECT id, amount, transaction_date FROM Transactions; ## ❌ 6. Redundant DISTINCT **Problem:** Using `DISTINCT` to patch bad joins. SELECT DISTINCT name FROM Customers c JOIN Orders o ON o.customer_id = c.id; βœ… **Fix:** Analyze join logic and duplicates instead. ## ❌ 7. Missing WHERE Clause in DELETE/UPDATE -- Danger zone! DELETE FROM Users; UPDATE Orders SET status = 'Shipped'; βœ… **Fix:** Always qualify with a WHERE clause. DELETE FROM Users WHERE is_deleted = true; ## ❌ 8. No Index on Foreign Keys **Problem:** FK lookups scan entire referenced table. -- Missing index on Orders.customer_id βœ… **Fix:** Add supporting indexes CREATE INDEX idx_orders_customer ON Orders(customer_id); ## ❌ 9. Overusing OR instead of UNION ALL SELECT * FROM Orders WHERE status = 'pending' OR status = 'shipped'; βœ… **Fix:** Separate indexed paths with UNION ALL SELECT * FROM Orders WHERE status = 'pending' UNION ALL SELECT * FROM Orders WHERE status = 'shipped'; ## ❌ 10. Not Using ANALYZE or EXPLAIN **Problem:** Blindly writing queries without measuring impact. βœ… **Fix:** Always inspect query plans EXPLAIN ANALYZE SELECT ... ## Final Thoughts: Write It Once, Run It Well Avoiding anti-patterns isn't just about style β€” it's about **performance, reliability, and cost**. > "SQL is declarative. Let the engine help β€” but don’t tie its hands with bad habits." _#SQL #Performance #AntiPatterns #QueryOptimization #BestPractices #AdvancedSQL #DataEngineering_
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10 SQL Anti-Patterns You Must Avoid in Production ## 10 SQL Anti-Patterns You Must Avoid in Production > β€œSlow SQL isn’t always about bad servers β€” it’s often about bad habits.” As SQL developers and data engineers, we often prioritize functionality and overlook **query quality**. But poor SQL habits can lead to: * Long response times * Bottlenecked applications * Excessive I/O and CPU * Poor scalability In this post, we’ll break down 10 critical **SQL anti-patterns** and how to fix them. ## ❌ 1. N+1 Query Pattern **Problem:** Querying in a loop for each record. -- BAD: Fetching orders per customer inside loop SELECT * FROM Customers; -- For each customer: SELECT * FROM Orders WHERE customer_id = ?; βœ… **Fix:** Join and aggregate in one query SELECT c.id, c.name, COUNT(o.id) AS order_count FROM Customers c LEFT JOIN Orders o ON o.customer_id = c.id GROUP BY c.id, c.name; ## ❌ 2. Wildcard Index Scans **Problem:** Leading wildcard disables index usage. SELECT * FROM Products WHERE name LIKE '%phone'; βœ… **Fix:** Use full-text search or structured LIKE -- Better (index usable) SELECT * FROM Products WHERE name LIKE 'phone%'; ## ❌ 3. Implicit Data Type Conversions **Problem:** Filtering numeric column with a string. SELECT * FROM Orders WHERE id = '123'; βœ… **Fix:** Match types explicitly SELECT * FROM Orders WHERE id = 123; πŸ” Use query plans to detect implicit conversion overhead. ## ❌ 4. Scalar Subqueries in SELECT **Problem:** Executing subquery for every row. SELECT id, (SELECT COUNT(*) FROM OrderItems WHERE order_id = o.id) FROM Orders o; βœ… **Fix:** Use join and aggregation SELECT o.id, COUNT(oi.id) AS item_count FROM Orders o LEFT JOIN OrderItems oi ON oi.order_id = o.id GROUP BY o.id; ## ❌ 5. SELECT * in Production **Problem:** Fetches unnecessary columns, causes bloat. SELECT * FROM Transactions; βœ… **Fix:** Select only what you need SELECT id, amount, transaction_date FROM Transactions; ## ❌ 6. Redundant DISTINCT **Problem:** Using `DISTINCT` to patch bad joins. SELECT DISTINCT name FROM Customers c JOIN Orders o ON o.customer_id = c.id; βœ… **Fix:** Analyze join logic and duplicates instead. ## ❌ 7. Missing WHERE Clause in DELETE/UPDATE -- Danger zone! DELETE FROM Users; UPDATE Orders SET status = 'Shipped'; βœ… **Fix:** Always qualify with a WHERE clause. DELETE FROM Users WHERE is_deleted = true; ## ❌ 8. No Index on Foreign Keys **Problem:** FK lookups scan entire referenced table. -- Missing index on Orders.customer_id βœ… **Fix:** Add supporting indexes CREATE INDEX idx_orders_customer ON Orders(customer_id); ## ❌ 9. Overusing OR instead of UNION ALL SELECT * FROM Orders WHERE status = 'pending' OR status = 'shipped'; βœ… **Fix:** Separate indexed paths with UNION ALL SELECT * FROM Orders WHERE status = 'pending' UNION ALL SELECT * FROM Orders WHERE status = 'shipped'; ## ❌ 10. Not Using ANALYZE or EXPLAIN **Problem:** Blindly writing queries without measuring impact. βœ… **Fix:** Always inspect query plans EXPLAIN ANALYZE SELECT ... ## Final Thoughts: Write It Once, Run It Well Avoiding anti-patterns isn't just about style β€” it's about **performance, reliability, and cost**. > "SQL is declarative. Let the engine help β€” but don’t tie its hands with bad habits." _#SQL #Performance #AntiPatterns #QueryOptimization #BestPractices #AdvancedSQL #DataEngineering_
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Start Coding with Flutter: A Complete Tutorial for New Developers | Tpoint Tech Get more from Tpoint Tech on Patreon

Start Coding with Flutter: A Complete Tutorial for New Developers

Visit Website: www.patreon.com/posts/start-...

#SQLTutorial, #LearnSQL, #SQLForBeginners, #SQLLearning, #SQLCourse, #SQLBasics, #AdvancedSQL

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SQL Tutorial Made Easy: From Basics to Advanced Queries If you’ve ever wanted to understand how websites, apps, and businesses manage massive amounts of...

SQL Tutorial Made Easy: From Basics to Advanced Queries

Visit Website: dev.to/tpointtech/s...

#SQLTutorial, #LearnSQL, #SQLForBeginners, #SQLLearning, #SQLCourse, #SQLBasics, #AdvancedSQL

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SQL Tutorial Made Easy: From Basics to Advanced Queries If you’ve ever wanted to understand how websites, apps, and businesses manage massive amounts of...

SQL Tutorial Made Easy: From Basics to Advanced Queries

Visit Website: dev.to/tpointtech/s...

#SQLTutorial, #LearnSQL, #SQLForBeginners, #SQLLearning, #SQLCourse, #SQLBasics, #AdvancedSQL

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Tpoint Tech If you’ve ever wanted to understand how websites, apps, and businesses manage massive amounts of information, learning SQL is a great place to start. SQL (Structured Query Language) is the standard la...

SQL Tutorial Made Easy: From Basics to Advanced Queries

Visit Website: sites.google.com/view/tutoria...

#SQLTutorial, #LearnSQL, #SQLForBeginners, #SQLLearning, #SQLCourse, #SQLBasics, #AdvancedSQL

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