Data Analytics
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Dive into the world of Data Analytics โ€“ uncover insights, explore trends, and master data-driven decision making.
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#๐—ฆ๐—ค๐—Ÿ ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐˜ƒ๐—ถ๐—ฒ๐˜„ ๐—–๐—ต๐—ฒ๐—ฎ๐˜๐˜€๐—ต๐—ฒ๐—ฒ๐˜ โ†’ ๐—–๐—ฟ๐—ฎ๐—ฐ๐—ธ ๐—”๐—ป๐˜† ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐˜ƒ๐—ถ๐—ฒ๐˜„ ๐—ช๐—ถ๐˜๐—ต ๐—ง๐—ต๐—ฒ๐˜€๐—ฒ ๐—–๐—ผ๐—ป๐—ฐ๐—ฒ๐—ฝ๐˜๐˜€

โžœ ๐Ÿญ. ๐—ฆ๐—ค๐—Ÿ ๐—๐—ผ๐—ถ๐—ป๐˜€ โ†’ Combine data from multiple tables
๐Ÿก† INNER JOIN โ†’ Returns matching records from both tables
๐Ÿก† LEFT JOIN โ†’ Returns all records from the left table + matches from the right
๐Ÿก† RIGHT JOIN โ†’ Returns all records from the right table + matches from the left
๐Ÿก† FULL JOIN โ†’ Returns all records from both tables

โžœ ๐Ÿฎ. ๐——๐—”๐—ง๐—” ๐—™๐—œ๐—Ÿ๐—ง๐—˜๐—ฅ๐—œ๐—ก๐—š โ†’ Retrieve specific records efficiently
๐Ÿก† WHERE โ†’ Filters rows before aggregation
๐Ÿก† HAVING โ†’ Filters after aggregation
๐Ÿก† BETWEEN, IN, LIKE โ†’ Advanced filtering

โžœ ๐Ÿฏ. ๐—”๐—š๐—š๐—ฅ๐—˜๐—š๐—”๐—ง๐—œ๐—ข๐—ก & ๐—š๐—ฅ๐—ข๐—จ๐—ฃ๐—œ๐—ก๐—š โ†’ Summarize data
๐Ÿก† GROUP BY โ†’ Groups data based on a column
๐Ÿก† COUNT, SUM, AVG, MIN, MAX โ†’ Perform calculations

โžœ ๐Ÿฐ. ๐—ฆ๐—จ๐—•๐—ค๐—จ๐—˜๐—ฅ๐—œ๐—˜๐—ฆ & ๐—–๐—ง๐—˜๐˜€ โ†’ Break complex queries
๐Ÿก† Subquery โ†’ Nested query inside another query
๐Ÿก† Common Table Expressions (CTE) โ†’ Temporary named query

โžœ ๐Ÿฑ. ๐—œ๐—ก๐——๐—˜๐—ซ๐—œ๐—ก๐—š & ๐—ข๐—ฃ๐—ง๐—œ๐— ๐—œ๐—ญ๐—”๐—ง๐—œ๐—ข๐—ก โ†’ Speed up queries
๐Ÿก† Indexes โ†’ Improve search speed
๐Ÿก† EXPLAIN PLAN โ†’ Analyze query performance

โžœ ๐Ÿฒ. ๐—”๐——๐—ฉ๐—”๐—ก๐—–๐—˜๐—— ๐—ฆ๐—ค๐—Ÿ ๐—ง๐—ข๐—ฃ๐—œ๐—–๐—ฆ
๐Ÿก† Window Functions โ†’ RANK, ROW_NUMBER, LEAD, LAG
๐Ÿก† Stored Procedures & Triggers โ†’ Automate tasks
๐Ÿก† Normalization & Denormalization โ†’ Optimize database design

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๐—ฆ๐—ค๐—Ÿ ๐—๐—ผ๐—ถ๐—ป๐˜€ ๐—–๐—ต๐—ฒ๐—ฎ๐˜๐˜€๐—ต๐—ฒ๐—ฒ๐˜ - ๐—™๐˜‚๐—น๐—น๐˜† ๐—˜๐˜…๐—ฝ๐—น๐—ฎ๐—ถ๐—ป๐—ฒ๐—ฑ

๐—ช๐—ต๐˜† ๐—ท๐—ผ๐—ถ๐—ป๐˜€ ๐—บ๐—ฎ๐˜๐˜๐—ฒ๐—ฟ?
Joins let you combine data from multiple tables to extract meaningful insights.
Every serious data analyst or backend dev should master these.

Letโ€™s break them down with clarity:

๐—œ๐—ก๐—ก๐—˜๐—ฅ ๐—๐—ข๐—œ๐—ก
โ†’ Returns only the rows with matching keys in both tables
โ†’ Think of it as intersection
๐—˜๐˜…๐—ฎ๐—บ๐—ฝ๐—น๐—ฒ:
Customers who have placed at least one order

SELECT *
FROM Customers
INNER JOIN Orders
ON Customers.ID = Orders.CustomerID;

๐—Ÿ๐—˜๐—™๐—ง ๐—๐—ข๐—œ๐—ก (๐—ข๐—จ๐—ง๐—˜๐—ฅ)
โ†’ Returns all rows from the left table + matching rows from the right
โ†’ If no match, right side = NULL
๐—˜๐˜…๐—ฎ๐—บ๐—ฝ๐—น๐—ฒ:
List all customers, even if theyโ€™ve never ordered

SELECT *
FROM Customers
LEFT JOIN Orders
ON Customers.ID = Orders.CustomerID;

๐—ฅ๐—œ๐—š๐—›๐—ง ๐—๐—ข๐—œ๐—ก (๐—ข๐—จ๐—ง๐—˜๐—ฅ)
โ†’ Returns all rows from the right table + matching rows from the left
โ†’ Rarely used, but similar logic
๐—˜๐˜…๐—ฎ๐—บ๐—ฝ๐—น๐—ฒ:
All orders, even from unknown or deleted customers

SELECT *
FROM Customers
RIGHT JOIN Orders
ON Customers.ID = Orders.CustomerID;

๐—™๐—จ๐—Ÿ๐—Ÿ ๐—ข๐—จ๐—ง๐—˜๐—ฅ ๐—๐—ข๐—œ๐—ก
โ†’ Returns all records when thereโ€™s a match in either table
โ†’ Unmatched rows = NULLs
๐—˜๐˜…๐—ฎ๐—บ๐—ฝ๐—น๐—ฒ:
Show all customers and all orders, whether matched or not

SELECT *
FROM Customers
FULL OUTER JOIN Orders
ON Customers.ID = Orders.CustomerID;

๐—–๐—ฅ๐—ข๐—ฆ๐—ฆ ๐—๐—ข๐—œ๐—ก
โ†’ Returns Cartesian product (all combinations)
โ†’ Use with care. 1,000 x 1,000 rows = 1,000,000 results!
๐—˜๐˜…๐—ฎ๐—บ๐—ฝ๐—น๐—ฒ:
Show all possible product and supplier pairings

SELECT *
FROM Products
CROSS JOIN Suppliers;

๐—ฆ๐—˜๐—Ÿ๐—™ ๐—๐—ข๐—œ๐—ก
โ†’ Join a table to itself
โ†’ Used for hierarchical data like employees & managers
๐—˜๐˜…๐—ฎ๐—บ๐—ฝ๐—น๐—ฒ:
Find each employeeโ€™s manager

SELECT A.Name AS Employee, B.Name AS Manager
FROM Employees A
JOIN Employees B
ON A.ManagerID = B.ID;

๐—•๐—ฒ๐˜€๐˜ ๐—ฃ๐—ฟ๐—ฎ๐—ฐ๐˜๐—ถ๐—ฐ๐—ฒ๐˜€
โ†’ Always use aliases (A, B) to simplify joins
โ†’ Use JOIN ON instead of WHERE for better clarity
โ†’ Test each join with LIMIT first to avoid surprises

---
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SQL Query Optimaztion.pdf
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SQL interview.pdf
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