Coders Learning

SQL for Data Analysis: 30 commonly asked questions in database management system (DBMS) interviews 👇👇 1. What is a DBMS? 2. Differentiate between DBMS and RDBMS. 3. What are the advantages and disadvantages of using a DBMS? 4. Explain the three levels of data abstraction in DBMS. 5. What is a database schema? 6. Define normalization and its importance in database design. 7. What are the different types of database models? 8. What is ACID (Atomicity, Consistency, Isolation, Durability) in DBMS? 9. What is a primary key, and why is it important? 10. Explain the concept of foreign keys. 11. Differentiate between a candidate key, primary key, and super key. 12. What is a transaction in a database? 13. Describe the differences between DELETE, TRUNCATE, and DROP commands. 14. What is a view in a database? 15. Explain indexing in databases. 16. What is a stored procedure? 17. What are the advantages of using stored procedures? 18. Describe the differences between clustered and non-clustered indexes. 19. What is a deadlock in DBMS? 20. How can you avoid deadlocks in a database? 21. What is data redundancy, and how can it be minimized? 22. What is a trigger in a database? 23. Describe the different types of joins in SQL. 24. What is a constraint in a database? 25. Explain the differences between a unique key and a primary key. 26. How does SQL differ from NoSQL databases? 27. What is the CAP theorem, and how does it relate to databases? 28. Explain the concept of data warehousing. 29. What are OLTP and OLAP, and how do they differ? 30. How would you approach database performance tuning and optimization?

𝟮𝟬 𝗦𝗤𝗟 𝗾𝘂𝗲𝗿𝘆 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 𝘁𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀 Below are the SQL query optimization techniques that I found to be significant, listed in the top 20: 1. Create an index on huge tables (>1.000.000) rows 2. Use EXIST() instead of COUNT() to find an element in the table 3. SELECT fields instead of using SELECT * 4. Avoid Subqueries in WHERE Clause 5. Avoid SELECT DISTINCT where possible 6. Use WHERE Clause instead of HAVING 7. Create joins with INNER JOIN (not WHERE) 8. Use LIMIT to sample query results 9. Use UNION ALL instead of UNION wherever possible 10. Use UNION where instead of WHERE ... or ... query. 11. Run your query during off-peak hours 12. Avoid using OR in join queries 14. Choose GROUP BY over window functions 15. Use derived and temporary tables 16. Drop the index before loading bulk data 16. Use materialized views instead of views 17. Avoid != or <> (not equal) operator 18. Minimize the number of subqueries 19. Use INNER join as little as possible when you can get the same output using LEFT/RIGHT join. 20. Frequently try to use temporary sources to retrieve the same dataset. Join @coderslearning for more ✅ Like this post if you need more!❤️ Hope it helps :)

Complete Roadmap to learn SQL 👇👇 Step 1: Basics of SQL 1. Learn SQL syntax, keywords, and basic commands (SELECT, FROM, WHERE). 2. Practice querying data from a single table. 3. Understand data types, NULL values, and basic functions (COUNT, SUM, AVG). 4. Experiment with simple filtering and sorting. Step 2: Intermediate SQL 1. Dive deeper into SQL with JOIN operations (INNER JOIN, LEFT JOIN, RIGHT JOIN). 2. Learn about subqueries and correlated subqueries. 3. Practice using aggregate functions (GROUP BY, HAVING) for data summarization. 4. Explore table creation, modification, and deletion commands (CREATE, ALTER, DROP). Step 3: Advanced SQL 1. Master advanced SQL concepts such as window functions and common table expressions (CTEs). 2. Learn about indexing and optimization techniques for query performance. 3. Practice writing complex queries involving multiple joins and subqueries. 4. Explore advanced topics like stored procedures, triggers, and transactions. Join @coderslearning for more ✅ Share this post if you need more! ❤️ Hope it helps :)

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