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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๐Ÿ“š Simply SQL (2024)

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๐Ÿ’ฌ Tags: #SQL

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๐Ÿ“š SQL QuickStart Guide (2024)

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๐Ÿ“š Practical SQL (2024)

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๐Ÿ“š NoSQL and SQL Data Modeling (2019)

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๐Ÿ’ฌ Tags: #NoSQL #SQL

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๐Ÿ“š SQL: 68 Things Beginners Need to Know

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๐Ÿš€ New to SQL?

Hereโ€™s a roadmap to get you started, step-by-step!
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(Don't forget to bookmark for later!!
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#SQL #ROADMAP

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MySQL Cheat Sheet

๐Ÿ’ฌ Tags: #MySQL #SQL

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SQL basic commands

๐Ÿ’ฌ Tags: #SQL #LEARN

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Free Certification Courses to Learn Data Analytics in 2025:

1. Python
๐Ÿ”— https://imp.i384100.net/5gmXXo

2. SQL
๐Ÿ”— https://edx.org/learn/relational-databases/stanford-university-databases-relational-databases-and-sql

3. Statistics and R
๐Ÿ”— https://edx.org/learn/r-programming/harvard-university-statistics-and-r

4. Data Science: R Basics
๐Ÿ”—https://edx.org/learn/r-programming/harvard-university-data-science-r-basics

5. Excel and PowerBI
๐Ÿ”— https://learn.microsoft.com/en-gb/training/paths/modern-analytics/

6. Data Science: Visualization
๐Ÿ”—https://edx.org/learn/data-visualization/harvard-university-data-science-visualization

7. Data Science: Machine Learning
๐Ÿ”—https://edx.org/learn/machine-learning/harvard-university-data-science-machine-learning

8. R
๐Ÿ”—https://imp.i384100.net/rQqomy

9. Tableau
๐Ÿ”—https://imp.i384100.net/MmW9b3

10. PowerBI
๐Ÿ”— https://lnkd.in/dpmnthEA

11. Data Science: Productivity Tools
๐Ÿ”— https://lnkd.in/dGhPYg6N

12. Data Science: Probability
๐Ÿ”—https://mygreatlearning.com/academy/learn-for-free/courses/probability-for-data-science

13. Mathematics
๐Ÿ”—https://matlabacademy.mathworks.com

14. Statistics
๐Ÿ”— https://lnkd.in/df6qksMB

15. Data Visualization
๐Ÿ”—https://imp.i384100.net/k0X6vx

16. Machine Learning
๐Ÿ”— https://imp.i384100.net/nLbkN9

17. Deep Learning
๐Ÿ”— https://imp.i384100.net/R5aPOR

18. Data Science: Linear Regression
๐Ÿ”—https://pll.harvard.edu/course/data-science-linear-regression/2023-10

19. Data Science: Wrangling
๐Ÿ”—https://edx.org/learn/data-science/harvard-university-data-science-wrangling

20. Linear Algebra
๐Ÿ”— https://pll.harvard.edu/course/data-analysis-life-sciences-2-introduction-linear-models-and-matrix-algebra

21. Probability
๐Ÿ”— https://pll.harvard.edu/course/data-science-probability

22. Introduction to Linear Models and Matrix Algebra
๐Ÿ”—https://edx.org/learn/linear-algebra/harvard-university-introduction-to-linear-models-and-matrix-algebra

23. Data Science: Capstone
๐Ÿ”— https://edx.org/learn/data-science/harvard-university-data-science-capstone

24. Data Analysis
๐Ÿ”— https://pll.harvard.edu/course/data-analysis-life-sciences-4-high-dimensional-data-analysis

25. IBM Data Science Professional Certificate
https://imp.i384100.net/9gxbbY

26. Neural Networks and Deep Learning
https://imp.i384100.net/DKrLn2

27. Supervised Machine Learning: Regression and Classification
https://imp.i384100.net/g1KJEA

#DataAnalytics #Python #SQL #RProgramming #DataScience #MachineLearning #DeepLearning #Statistics #DataVisualization #PowerBI #Tableau #LinearRegression #Probability #DataWrangling #Excel #AI #ArtificialIntelligence #BigData #DataAnalysis #NeuralNetworks #SupervisedLearning #IBMDataScience #FreeCourses #Certification #LearnDataScience
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20 most common SQL Interview Questions.

#SQL #Interview

Donโ€™t skip no. 15๐Ÿ”ฅ๐Ÿ“ท

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๐Ÿ“– Keys In #SQL With Tables Well Explained

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๐Ÿ“–  SQL CheatSheet Full Course


#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

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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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