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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#SQL #DATABASE #LEARN

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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

โšก๏ธ BEST DATA SCIENCE CHANNELS ON TELEGRAM ๐ŸŒŸ
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SQL Query Optimaztion.pdf
897.9 KB
Your SQL query is running.

And running.

And ruuunnniiiiiiiing....โฑ๏ธโฑ๏ธโฑ๏ธโฑ๏ธ

Not so great for a tool meant to enable us quicker access to data, right?

Swipe for a few tips on how to optimize your #SQL queries, and not let them become a bottleneck in your reporting process.

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๐Ÿ“Œ How to Design Structured Database Systems Using SQL [Full Book]

โœ๏ธ Daniel Garcรญa Solla
๐Ÿท๏ธ #SQL
๐Ÿ“Œ A Brief Introduction to SQLite

โœ๏ธ Mark Mahoney
๐Ÿท๏ธ #SQL
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๐Ÿ“Œ Learn Databases and SQL from Harvard University

โœ๏ธ Beau Carnes
๐Ÿท๏ธ #SQL
300 Real Time SQL Interview.pdf
4.5 MB
300 Real Time SQL Interview practical Questions Asked at multiple companies
โ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ขโ€ข

Anyone who's preparing for an interview just reading theoretical concept will not help definitely you need to have practical hands on in #sql so create table with some data and try this queries running by your self so can help you to understand the logic of similar kind of queries

If you're preparing for an interview this doc will help a lot in the perpetration If you're experienced also freshers can also get hands on by practicing these queries and get confidence.
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Important SQL concepts to master.pdf
3 MB
Important #SQL concepts to master:
- Joins (inner, left, right, full)
- Group By vs Where vs Having
- Window functions (ROW_NUMBER, RANK, DENSE_RANK)
- CTEs (Common Table Expressions)
- Subqueries and nested queries
- Aggregations and filtering
- Indexing and performance basics
- NULL handling

Interview Tips:
- Focus on writing clean, readable queries
- Explain your logic clearly donโ€™t just jump to
#code
- Always test for edge cases (empty tables, duplicate rows)
- Practice optimization: how would you improve performance?


https://t.iss.one/DataAnalyticsX โญ
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SQL Ultimate Cheat Sheet

Standard #SQL, Queries & Management

https://t.iss.one/DataAnalyticsX ๐Ÿ‘พ
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