Complete SQL Topics For Data Analytics
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Understanding CTEs in SQL

A Common Table Expression (CTE) is a temporary result set that you can refer to within a SELECT, INSERT, UPDATE, or DELETE statement. It provides better readability and can be thought of as defining a temporary view for just one query.

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📊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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📊🚀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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