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TEDay 13 of learning SQL ✨
Window functions are very important for an interview.
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Follow @techiecodes for Day 14
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@techiecodes
#Sql Window Functions
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MESQL Window Functions for Interviews ✅✅🔥
Work on End-to-End Real-Time Projects on Data Analytics, Data Science, AI & Data Engineering
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🌟 Snowflake with Power BI Pipeline
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@meet_kanth
23.9K
COSQL Commands Explained – Complete SQL Chart (Light Theme)
Master SQL fundamentals at a glance with this clean, professional SQL command chart.
This visual breakdown covers DQL, DML, DDL, joins, functions, and window functions — perfect for beginners, students, and working professionals.
💡 What you’ll learn in this video:
🔹 SQL Command Types (DQL, DML, DDL)
🔹 SELECT, INSERT, UPDATE, DELETE
🔹 WHERE, GROUP BY, ORDER BY
🔹 JOINS (INNER, LEFT, RIGHT, FULL)
🔹 Aggregate & Window Functions
🔹 Real-world SQL structure simplified
🚀 Ideal for:
👨💻 Data Analysts
👩💻 SQL Developers
📈 Data Engineers
🎓 Students & Interview Prep
Save this video 📌 and come back whenever you need a quick SQL refresher.
🔑 Relevant Keywords
SQL tutorial, SQL commands, SQL chart, SQL basics, SQL for beginners, DML DDL DQL, SQL joins, SQL functions, SQL window functions, SQL interview questions, SQL cheat sheet, data analyst SQL, database fundamentals
🏷️ Hashtags (Optimized for Reach)
#SQL
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@codewithprashantt
193.9K
CLSave this SQL Commands Cheatsheet
Understanding the core categories of SQL commands is essential for mastering database management and data analysis.
Whether you’re defining the structure of your database, controlling transactions, querying data, or managing access, each SQL command plays a critical role.
Let’s break down these commands and functions to see how they empower you to interact with your database efficiently.
1. DDL (Data Definition Language): Commands to define and manage the structure of database objects.
2. TCL (Transaction Control Language): Commands to manage transactions in the database.
3. DQL (Data Query Language): Commands to query and retrieve data from the database.
4. DCL (Data Control Language): Commands to control access to data within the database.
5. DML (Data Manipulation Language): Commands to manipulate data stored in the database.
Functions
- Aggregate Functions: Functions that perform calculations on a set of values and return a single value (e.g., SUM, AVG, COUNT).
- Window Functions: Functions that perform calculations across a set of table rows that are related to the current row, without collapsing the result into a single value (e.g., ROW_NUMBER, RANK, LEAD).
#sql #mysql #database #datascience #bigdata #programming #coding #tech #devops #devsecops
@clouddevopsengineer
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DADay 31 SQL | Window Functions Begin 🚀 | ROW_NUMBER() Explained
SAVE this and SHARE with your Data Analyst batch 📊
📺 Follow on YouTube: Link in Bio
👉 www.youtube.com/@DataXOdyssey
❓ Interview + Real-World Concept
How do you assign a unique number to each row without hiding any data?
🪟 Introducing WINDOW FUNCTIONS
They calculate values
👉 without collapsing rows
👉 without using GROUP BY
Today we start with the most important one 👇
✅ ROW_NUMBER()
Assigns a unique number to each row based on logic you define.
Case 1: ROW_NUMBER() with just OVER()
SELECT
employee_name,
ROW_NUMBER() OVER () AS row_num
FROM employees;
🧠 What this means
👉 Whole table is the window
👉 Rows stay visible
👉 Numbers are assigned arbitrarily
Case 2: ROW_NUMBER() with ORDER BY
SELECT
employee_name,
salary,
ROW_NUMBER() OVER (ORDER BY salary DESC) AS row_num
FROM employees;
🧠 What this means
👉 Highest salary gets row number 1
👉 Every row still appears
👉 Duplicate salaries still get different numbers
Case 3: ROW_NUMBER() with PARTITION BY department
SELECT
employee_name,
department,
salary,
ROW_NUMBER() OVER (PARTITION BY department ORDER BY salary DESC) AS row_num
FROM employees;
🧠 What this means
👉 Ranking resets for each department
👉 No rows are removed
👉 Clean & interview-safe logic
🧠 Why ROW_NUMBER() Matters
👉 Used for Top-N queries
👉 Helps remove duplicates
👉 Powers pagination
👉 Foundation of window functions
📌 Part of Daily SQL Series – Day 31
🔁 Missed earlier days? Check previous videos to learn SQL from scratch
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#Day31 #WindowFunctions #ROW_NUMBER
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@dataxodyssey
9.7K
INSQL Window Functions Explained!
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window functions let you analyze data without grouping it.
you can rank rows, calculate running totals, and compare values all while keeping every record visible.
functions like ROW_NUMBER, RANK, LAG, and LEAD are game-changers for analytics.
once you learn them, your sql goes from basic to powerful.
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this is how analysts think in queries.
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{ sql window functions, sql analytics, data analysis, advanced sql, database queries }
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#sql #datascience #sqltips #windowfunctions #intellipaat
@intellipaat
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DEAll SQl Join Methods || Save For Later 📲
Boost your web dev skills 🧑💻
Follow @de.code.dev for more
@de.code.dev
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Learn Coding Frontend development, web development, HTML, CSS, JavaScript, React, Python
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@de.code.dev
8.2K
SHSQL Window Functions are one of the most powerful tools for anyone working in analytics, reporting, or data engineering. They help you analyse rows in relation to each other, build advanced metrics, compare trends, and create clean logic without complex subqueries.
This cheatsheet summarises the core window functions you’ll use across real-world projects: ranking, navigation, aggregates, statistical calculations, time-based logic, and frame clauses.
More pages include deeper examples, project-based use cases, and the exact patterns companies use in interviews and dashboards.
If you’re serious about SQL for analytics, learning window functions is one of the best investments you can make.
Save this post for future reference and follow for more detailed SQL breakdowns.
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#sqllearning #dataanalytics #bi #techskills #analyticscommunity
@she_explores_data
21.9K
SIWindow Functions in Sql #sql #sqlserver #sqldeveloper #sqldatabase #sqlinterview #sqlqueries #mysql #datascience #dataanalytics #datascientist #datavisualization #machinelearning #artificialintelligence #bigdata #ssrs #ssms #coding #coder #programming #learn #education
@simplybi4
0
57.6K
HUDay 8/21 – SQL Challenge
Solved 4 SQL questions today, mainly using window functions, self joins, and subqueries.
• Rising Temperature:
Used LAG() to compare today’s temperature with yesterday’s and filtered where today > previous day.
(Also possible using self join with date difference logic.)
• Customers Who Never Order:
Solved using
1.LEFT JOIN + NULL filter
2.NOT EXISTS subquery
• Repeated Payments (DataLemur):
Used LAG() to get previous transaction timestamp and calculated time difference.
Filtered payments repeated within 10 minutes for same card, merchant, and amount.
• Employees Earning More Than Their Manager:
Solved using self join on employee_id and manager_id and compared salaries.
Key learning:
Window functions + self joins make comparison-based problems much easier.
Day 9 loading…
@hustleuphoney
413.2K
EMComment “SQL” to get links!
🚀 Want to master SQL without getting bored to tears? This mini roadmap takes you from “what is a database?” to solving complex crimes with code.
🎨 DrawSQL
Stop trying to visualize complex databases in your head. This tool lets you build beautiful Entity Relationship Diagrams (ERDs) just by dragging and dropping. It is the best way to understand how tables relate to each other—Foreign Keys and Joins finally make sense when you can actually see them.
⚡ SQLBolt
Perfect if you want to learn by doing, not reading. This site gives you bite-sized, interactive lessons right in your browser. No installation needed. You’ll race through the basics of SELECT, filtering, and aggregations with instant feedback on your code.
🕵️ SQL Murder Mystery
The ultimate way to practice. There has been a murder in SQL City, and you have to solve it by querying the police database. You will use advanced logic, joins, and wildcards to find the killer. It turns “studying” into a detective game you actually want to play.
💡 With these resources you will:
Visualize database architecture like a System Designer
Master the syntax through hands-on repetition
Build real-world problem-solving skills (and have fun doing it)
If you are aiming for Data Analytics or Backend Engineering roles, these 3 tools are your cheat sheet.
📌 Save this post so you don’t lose the roadmap.
💬 Comment “SQL” and I’ll send you the direct links. 👉 Follow for more content on Coding, Data, and Tech Careers.
@emrcodes
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