📊Here's a breakdown of SQL interview questions covering various topics:

🔺Basic SQL Concepts:
-Differentiate between SQL and NoSQL databases.
-List common data types in SQL.

🔺Querying:
-Retrieve all records from a table named "Customers."
-Contrast SELECT and SELECT DISTINCT.
-Explain the purpose of the WHERE clause.


🔺Joins:
-Describe types of joins (INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN).
-Retrieve data from two tables using INNER JOIN.

🔺Aggregate Functions:
-Define aggregate functions and name a few.
-Calculate average, sum, and count of a column in SQL.

🔺Grouping and Filtering:
-Explain the GROUP BY clause and its use.
-Filter SQL query results using the HAVING clause.

🔺Subqueries:
-Define a subquery and provide an example.

🔺Indexes and Optimization:
-Discuss the importance of indexes in a database.
&Optimize a slow-running SQL query.

🔺Normalization and Data Integrity:
-Define database normalization and its significance.
-Enforce data integrity in a SQL database.

🔺Transactions:
-Define a SQL transaction and its purpose.
-Explain ACID properties in database transactions.

🔺Views and Stored Procedures:
-Define a database view and its use.
-Distinguish a stored procedure from a regular SQL query.

🔺Advanced SQL:
-Write a recursive SQL query and explain its use.
-Explain window functions in SQL.

✅👀These questions offer a comprehensive assessment of SQL knowledge, ranging from basics to advanced concepts.

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Answers for this👀

🔺Basic SQL Concepts:
SQL vs NoSQL: SQL is relational, structured, and uses a predefined schema. NoSQL is non-relational, flexible, and schema-less.
Common Data Types: Examples include INT, VARCHAR, DATE, and BOOLEAN.

🔺Querying:
Retrieve all records from "Customers": SELECT * FROM Customers;
SELECT vs SELECT DISTINCT: SELECT retrieves all rows, while SELECT DISTINCT returns only unique values.
WHERE clause: Filters data based on specified conditions.

🔺Joins:
Types of Joins: INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN.
INNER JOIN example: SELECT * FROM Table1 INNER JOIN Table2 ON Table1.ID = Table2.ID;

🔺Aggregate Functions:
Aggregate Functions: Examples include COUNT, AVG, SUM.
Calculate average, sum, count: SELECT AVG(column), SUM(column), COUNT(column) FROM Table;

🔺Grouping and Filtering:
GROUP BY clause: Groups results based on specified columns.
HAVING clause: Filters grouped results.

🔺Subqueries:
Subquery: A query within another query. Example: SELECT column FROM Table WHERE column = (SELECT MAX(column) FROM Table);

🔺Indexes and Optimization:
Importance of Indexes: Improve query performance by speeding up data retrieval.
Optimize slow query: Add indexes, optimize queries, and consider database design.

🔺Normalization and Data Integrity:
Normalization: Organizing data to reduce redundancy and dependency.
Data Integrity: Enforce rules to maintain accuracy and consistency.

🔺Transactions:
SQL Transaction: A sequence of one or more SQL statements treated as a single unit.
ACID properties: Atomicity, Consistency, Isolation, Durability.

🔺Views and Stored Procedures:
Database View: Virtual table based on the result of a SELECT query.
Stored Procedure: Precompiled SQL code stored in the database for reuse.

🔺Advanced SQL:
Recursive SQL query: Used for hierarchical data.
Window Functions: Perform calculations across a set of rows related to the current row.

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TOP CONCEPTS FOR INTERVIEW PREPARATION!!

🚀TOP 10 SQL Concepts for Job Interview

1. Aggregate Functions (SUM/AVG)
2. Group By and Order By
3. JOINs (Inner/Left/Right)
4. Union and Union All
5. Date and Time processing
6. String processing
7. Window Functions (Partition by)
8. Subquery
9. View and Index
10. Common Table Expression (CTE)


🚀TOP 10 Statistics Concepts for Job Interview

1. Sampling
2. Experiments (A/B tests)
3. Denoscriptive Statistics
4. p-value
5. Probability Distributions
6. t-test
7. ANOVA
8. Correlation
9. Linear Regression
10. Logistics Regression


🚀TOP 10 Python Concepts for Job Interview

1. Reading data from file/table
2. Writing data to file/table
3. Data Types
4. Function
5. Data Preprocessing (numpy/pandas)
6. Data Visualisation (Matplotlib/seaborn/bokeh)
7. Machine Learning (sklearn)
8. Deep Learning (Tensorflow/Keras/PyTorch)
9. Distributed Processing (PySpark)
10. Functional and Object Oriented Programming

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SQL COMMANDS 👇
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📊🚀A beginner's roadmap for learning SQL:

🔹Understand Basics:
Learn what SQL is and its purpose in managing relational databases.
Understand basic database concepts like tables, rows, columns, and relationships.

🔹Learn SQL Syntax:
Familiarize yourself with SQL syntax for common commands like SELECT, INSERT, UPDATE, DELETE.
Understand clauses like WHERE, ORDER BY, GROUP BY, and JOIN.

🔹Setup a Database:
Install a relational database management system (RDBMS) like MySQL, SQLite, or PostgreSQL.
Practice creating databases, tables, and inserting data.

🔹Retrieve Data (SELECT):
Learn to retrieve data from a database using SELECT statements.
Practice filtering data using WHERE clause and sorting using ORDER BY.

🔹Modify Data (INSERT, UPDATE, DELETE):
Understand how to insert new records, update existing ones, and delete data.
Be cautious with DELETE to avoid unintentional data loss.

🔹Working with Functions:
Explore SQL functions like COUNT, AVG, SUM, MAX, MIN for data analysis.
Understand string functions, date functions, and mathematical functions.

🔹Data Filtering and Sorting:
Learn advanced filtering techniques using AND, OR, and IN operators.
Practice sorting data using multiple columns.

🔹Table Relationships (JOIN):
Understand the concept of joining tables to retrieve data from multiple tables.
Learn about INNER JOIN, LEFT JOIN, RIGHT JOIN, and FULL JOIN.

🔹Grouping and Aggregation:
Explore GROUP BY clause to group data based on specific columns.
Understand aggregate functions for summarizing data (SUM, AVG, COUNT).

🔹Subqueries:
Learn to use subqueries to perform complex queries.
Understand how to use subqueries in SELECT, WHERE, and FROM clauses.

🔹Indexes and Optimization:
Gain knowledge about indexes and their role in optimizing queries.
Understand how to optimize SQL queries for better performance.

🔹Transactions and ACID Properties:
Learn about transactions and the ACID properties (Atomicity, Consistency, Isolation, Durability).
Understand how to use transactions to maintain data integrity.

🔹Normalization:
Understand the basics of database normalization to design efficient databases.
Learn about 1NF, 2NF, 3NF, and BCNF.

🔹Backup and Recovery:
Understand the importance of database backups.
Learn how to perform backups and recovery operations.

🔹Practice and Projects:
Apply your knowledge through hands-on projects.
Practice on platforms like LeetCode, HackerRank, or build your own small database-driven projects.

👀👍Remember to practice regularly and build real-world projects to reinforce your learning. Happy coding!

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No matter your target job– data analyst, developer, or business pro – becoming an SQL expert helps you make smart decisions and plan for the future.

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CRUD operations in SQL

1.Create (INSERT): Adds new records to a table
2.Read (SELECT): Retrieves data from a table.
3.Update (UPDATE): Modifies existing records in a table.
4. Delete (DELETE): Removes records from a table.

SQL Quick Notes to refresh your concepts

Me after learning SQL👇
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Quick Recap of SQL Concepts

1️⃣ FROM clause: Specifies the tables from which data will be retrieved.
2️⃣ WHERE clause: Filters rows based on specified conditions.
3️⃣ GROUP BY clause: Groups rows that have the same values into summary rows.
4️⃣ HAVING clause: Filters groups based on specified conditions.
5️⃣ SELECT clause: Specifies the columns to be retrieved.
6️⃣ WINDOW functions: Functions that perform calculations across a set of table rows.
7️⃣ AGGREGATE functions: Functions like COUNT, SUM, AVG that perform calculations on a set of values.
8️⃣ UNION / UNION ALL: Combines the result sets of multiple SELECT statements.
9️⃣ ORDER BY clause: Sorts the result set based on specified columns.
🔟 LIMIT / OFFSET (or FETCH / OFFSET in some databases): Controls the number of rows returned and starting point for retrieval.

🔅 Most important SQL commands

30-day Roadmap plan for SQL covers beginner, intermediate, and advanced topics 👇

Week 1: Beginner Level

Day 1-3: Introduction and Setup
1. Day 1: Introduction to SQL, its importance, and various database systems.
2. Day 2: Installing a SQL database (e.g., MySQL, PostgreSQL).
3. Day 3: Setting up a sample database and practicing basic commands.

Day 4-7: Basic SQL Queries
4. Day 4: SELECT statement, retrieving data from a single table.
5. Day 5: WHERE clause and filtering data.
6. Day 6: Sorting data with ORDER BY.
7. Day 7: Aggregating data with GROUP BY and using aggregate functions (COUNT, SUM, AVG).

Week 2-3: Intermediate Level

Day 8-14: Working with Multiple Tables
8. Day 8: Introduction to JOIN operations.
9. Day 9: INNER JOIN and LEFT JOIN.
10. Day 10: RIGHT JOIN and FULL JOIN.
11. Day 11: Subqueries and correlated subqueries.
12. Day 12: Creating and modifying tables with CREATE, ALTER, and DROP.
13. Day 13: INSERT, UPDATE, and DELETE statements.
14. Day 14: Understanding indexes and optimizing queries.

Day 15-21: Data Manipulation
15. Day 15: CASE statements for conditional logic.
16. Day 16: Using UNION and UNION ALL.
17. Day 17: Data type conversions (CAST and CONVERT).
18. Day 18: Working with date and time functions.
19. Day 19: String manipulation functions.
20. Day 20: Error handling with TRY...CATCH.
21. Day 21: Practice complex queries and data manipulation tasks.

Week 4: Advanced Level

Day 22-28: Advanced Topics
22. Day 22: Working with Views.
23. Day 23: Stored Procedures and Functions.
24. Day 24: Triggers and transactions.
25. Day 25: Windows Function

Day 26-30: Real-World Projects
26. Day 26: SQL Project-1
27. Day 27: SQL Project-2
28. Day 28: SQL Project-3
29. Day 29: Practice questions set
30. Day 30: Final review and practice, explore advanced topics in depth, or work on a personal project.

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If you are trying to transition into the data analytics domain and getting started with SQL, focus on the most useful concept that will help you solve the majority of the problems, and then try to learn the rest of the topics:

👉🏻 Basic Aggregation function:
1️⃣ AVG
2️⃣ COUNT
3️⃣ SUM
4️⃣ MIN
5️⃣ MAX

👉🏻 JOINS
1️⃣ Left
2️⃣ Inner
3️⃣ Self (Important, Practice questions on self join)

👉🏻 Windows Function (Important)
1️⃣ Learn how partitioning works
2️⃣ Learn the different use cases where Ranking/Numbering Functions are used? ( ROW_NUMBER,RANK, DENSE_RANK, NTILE)
3️⃣ Use Cases of LEAD & LAG functions
4️⃣ Use cases of Aggregate window functions

👉🏻 GROUP BY
👉🏻 WHERE vs HAVING
👉🏻 CASE STATEMENT
👉🏻 UNION vs Union ALL
👉🏻 LOGICAL OPERATORS

Other Commonly used functions:
👉🏻 IFNULL
👉🏻 COALESCE
👉🏻 ROUND
👉🏻 Working with Date Functions
1️⃣ EXTRACTING YEAR/MONTH/WEEK/DAY
2️⃣ Calculating date differences

👉🏻CTE
👉🏻Views & Triggers (optional)

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1. Danny’s Diner:
Restaurant analytics to understand the customer orders pattern.
Link: https://8weeksqlchallenge.com/case-study-1/

2. Pizza Runner
Pizza shop analytics to optimize the efficiency of the operation
Link: https://8weeksqlchallenge.com/case-study-2/

3. Foodie Fie
Subnoscription-based food content platform
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Analytics based on customer activities with the digital bank
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5. Data Mart: Fresh is Best
Analytics on Online supermarket
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6. Clique Bait: Attention capturing
Analytics on the seafood industry
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7. Balanced Tree: Clothing Company
Analytics on the sales performance of clothing store
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8. Fresh segments: Extract maximum value
Analytics on online advertising
Link: https://8weeksqlchallenge.com/case-study-8