ru
Feedback
PrepNPlaced

PrepNPlaced

Открыть в Telegram

🚀 Welcome to the Elite Data Engineering & Agentic AI Hub! 🚀 👑 Community Creator: Mandar Patil 👨‍💻 Admin & Mentor: Durgesh Yadav The era of basic data tasks is over. With Agentic AI evolving the industry, up to 60% of traditional Data Analyst roles

Больше

📈 Аналитический обзор Telegram-канала PrepNPlaced

Канал PrepNPlaced (@dataanalyticsbuddy) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 27 585 подписчиков, занимая 6 954 место в категории Образование и 14 702 место в регионе Индия.

📊 Показатели аудитории и динамика

С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 27 585 подписчиков.

Согласно последним данным от 29 августа, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило -616, а за последние 24 часа — -16, при этом общий охват остаётся высоким.

  • Статус верификации: Не верифицирован
  • Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 2.96%. В первые 24 часа после публикации контент обычно набирает 1.10% реакций от общего числа подписчиков.
  • Охват публикаций: В среднем каждый пост получает 817 просмотров. В течение первых суток публикация набирает 303 просмотров.
  • Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 1.
  • Тематические интересы: Контент сосредоточен на ключевых темах, таких как analyst, sql, analytic, dashboard, roadmap.

📝 Описание и контентная политика

Автор описывает ресурс как площадку для выражения субъективного мнения:
🚀 Welcome to the Elite Data Engineering & Agentic AI Hub! 🚀 👑 Community Creator: Mandar Patil 👨‍💻 Admin & Mentor: Durgesh Yadav The era of basic data tasks is over. With Agentic AI evolving the industry, up to 60% of traditional Data Analyst ...

Благодаря высокой частоте обновлений (последние данные получены 30 августа, 2026) канал поддерживает актуальность и высокий уровень охвата публикаций. Аналитика показывает, что аудитория активно взаимодействует с контентом, что делает его важной точкой влияния в категории Образование.

27 585
Подписчики
-1624 часа
-1367 дней
-61630 день
Архив постов
🔥 FREE LIVE SESSION ALERT 🔥 🚀 Databricks in 3 Hours for Analysts & Engineers 📅 12th April (Sunday) ⏰ 12:00 PM (IST) ⏳ Duration: 3 Hours Want to master Databricks end-to-end in just 3 hours? This hands-on session will cover: ✅ Databricks Workspace & Architecture ✅ Spark-based ETL Pipelines ✅ Delta Lake (Industry Standard) ✅ Real-world Data Engineering Workflows ✅ Performance Optimization Techniques 💡 Perfect for: • Data Analysts • Data Engineers • Freshers & Working Professionals 🎯 Learn what usually takes weeks — in just 3 hours 💸 Absolutely FREE 👉 Limited Seats — Register Now: https://topmate.io/durgesh_yadav/2030311 Reply “JOIN” and I’ll guide you

*Last 1 Hour to Enroll in Our Self Paced Recorded Course which has everything u need to crack Data Analyst Job and its at 95% Discount* 🚨 ENROLLMENTS CLOSING | LIMITED SEATS 🚨 🎓 Data Analytics End-to-End (SELF-PACED) + Placement Cohort 💼 Complete Career Package – ₹399 Only ⏳ Learn at your own pace 📱 Watch anytime | Rewatch anytime 💻 Perfect for students & working professionals ✅ What’s Included: ✔ SELF-PACED COURSE  • SQL (Basics → Advanced, CTEs, Window Functions)  • Power BI (Industry-level Dashboards)  • Excel (Analytics, Pivot Tables, Dynamic Dashboards)  • Python (Pandas, NumPy on Real Datasets) ✔ Placement Cohort – 20 Guided Sessions  • Resume Building  • Interview Preparation  • Real Case Studies  • Mock Interviews & Guidance ✔ 300+ Hands-On Projects ✔ Complete Interview Prep Kit 👨‍🏫 Course by Industry Data Analyst 🔗 https://www.linkedin.com/in/yadavdurgesh711 ⏳ Cohort Seats Are Limited 👉 Enroll Now: 🔗 https://topmate.io/durgesh_yadav/1776905 📩 Queries: durgeshyadavlkh@gmail.com

SQL Zero to Advanced Roadmap with Practice Questions 🔥 Share with others to help ✨ ✅ Join our Communities: Telegram Channel: https://t.me/dataanalyticsbuddy WhatsApp Channel: https://whatsapp.com/channel/0029VaFZ2LbKGGGRCU0lnd46 Do react ❤️ if you want more resources like this

Hey All, Finally we are giving exclusive Discount on our Cohort. This Cohort will make you a Advance Data Analyst & Data Engineer from Level Zero along with AI Fundamentals all in *Live Class* Enroll Today & Ping me I will help you with discounted Prize. Check Cohort - Go to www.datacity.in and click on *Paid Course* Section & Check the Cohort & then *Contact me* on +917887289947 ! *A Best Career Guidance Program by Our Team & Topmate*

𝐒𝐐𝐋 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐑𝐨𝐚𝐝𝐦𝐚𝐩🔥🔥🔥 |── Basics | ├── What is SQL? | ├── Database vs DBMS vs RDBMS | ├── Databases & Tables | ├── Rows vs Columns | ├── Data Types (INT, VARCHAR, DATE, FLOAT, BOOLEAN) | ├── Constraints (NOT NULL, UNIQUE, PRIMARY KEY, FOREIGN KEY, CHECK, DEFAULT) | ├── Keys (Primary, Foreign, Candidate, Composite, Super Key) | └── CRUD Operations (Create, Read, Update, Delete) | |── DDL (Data Definition Language) | ├── CREATE DATABASE | ├── CREATE TABLE | ├── ALTER TABLE | ├── DROP TABLE | ├── TRUNCATE TABLE | └── RENAME TABLE | |── DML (Data Manipulation Language) | ├── INSERT INTO | ├── UPDATE | ├── DELETE | └── Bulk Inserts | |── DQL (Data Query Language) | ├── SELECT | ├── Column Selection | ├── Aliases (AS) | └── Expressions & Calculations | |── Data Retrieval | ├── SELECT, FROM, WHERE | ├── DISTINCT | ├── ORDER BY (ASC, DESC) | ├── LIMIT / TOP / OFFSET-FETCH | ├── BETWEEN | ├── IN / NOT IN | ├── LIKE (%, _) | └── IS NULL / IS NOT NULL | |── Filtering & Conditions | ├── AND, OR, NOT | ├── Operator Precedence | ├── Nested Conditions | └── Short-circuit Evaluation | |── Joins | ├── INNER JOIN | ├── LEFT JOIN | ├── RIGHT JOIN | ├── FULL OUTER JOIN | ├── CROSS JOIN | ├── SELF JOIN | ├── Join Conditions (ON vs WHERE) | └── Handling NULLs in Joins | |── Grouping & Aggregation | ├── GROUP BY | ├── Aggregate Functions: COUNT(), SUM(), AVG(), MIN(), MAX() | ├── HAVING | ├── Conditional Aggregation (CASE WHEN) | └── Grouping Rules & Errors | |── CASE Statements & Conditional Logic | ├── CASE WHEN | ├── Nested CASE | ├── Conditional Columns | └── Conditional Aggregations | |── NULL Handling | ├── NULL Behavior in SQL | ├── IS NULL, IS NOT NULL | ├── COALESCE() | ├── NULLIF() | └── NULL in Aggregations | |── Subqueries & Nested Queries | ├── Subquery in SELECT | ├── Subquery in WHERE | ├── Subquery in FROM | ├── Correlated Subqueries | ├── Scalar vs Multi-row Subqueries | └── Performance Considerations | |── Set Operations | ├── UNION | ├── UNION ALL | ├── INTERSECT | └── EXCEPT / MINUS | |── Advanced SQL | ├── EXISTS / NOT EXISTS | ├── Derived Tables | ├── Inline Views | ├── Pivoting & Unpivoting | └── Dynamic SQL (Basics) | |── Window Functions (Analytical SQL) | ├── OVER() Clause | ├── PARTITION BY | ├── ORDER BY in Window | ├── Ranking: ROW_NUMBER(), RANK(), DENSE_RANK() | ├── Value Functions: LEAD(), LAG() | ├── Aggregates as Window Functions | └── Running Totals & Moving Averages | |── Common Table Expressions (CTEs) | ├── WITH Clause | ├── Multiple CTEs | ├── Recursive CTEs | └── CTE vs Subquery | |── Views | ├── Creating Views | ├── Updating Views | ├── Materialized Views | └── Use Cases | |── Indexes & Performance | ├── What is Index | ├── Clustered vs Non-Clustered Index | ├── Composite Index | ├── Indexing Strategies | ├── Query Optimization | ├── Execution Plan | └── EXPLAIN / ANALYZE | |── Transactions & ACID | ├── Transaction Basics | ├── COMMIT, ROLLBACK, SAVEPOINT | ├── ACID Properties | └── Concurrency Issues | |── Locks & Isolation Levels | ├── Lock Types | ├── Isolation Levels | ├── Dirty Read, Non-repeatable Read, Phantom Read | └── Deadlocks | |── Database Design Concepts | ├── ER Diagrams | ├── Normalization (1NF, 2NF, 3NF, BCNF) | ├── Denormalization | ├── Relationships (1-1, 1-M, M-M) | └── Schema Design Best Practices | |── Data Warehousing Concepts | ├── OLTP vs OLAP | ├── Fact & Dimension Tables | ├── Star Schema | ├── Snowflake Schema | └── ETL Basics | |── SQL for Data Analysis | ├── Business Metrics (Revenue, Retention, AOV) | ├── Cohort Analysis | ├── Funnel Analysis | ├── Time Series Analysis | └── Data Cleaning in SQL | |── SQL in Real Projects | ├── E-commerce Analysis | ├── Customer Behavior Analysis | ├── Sales Dashboard Queries | └── KPI Reporting | |── Tools & Platforms | ├── MySQL | ├── PostgreSQL | ├── SQL Server | ├── Oracle | ├── SQLite | ├── BigQuery | ├── Snowflake | └── Amazon Redshift | |── END 👉WhatsApp Channel: https://whatsapp.com/channel/0029VaFZ2LbKGGGRCU0lnd46 👉Telegram Channel: https://t.me/dataanalyticsbuddy Till then keep learning and keep exploring 🙌 😊

Till then keep learning and keep exploring 🙌 😊

𝐒𝐐𝐋 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐑𝐨𝐚𝐝𝐦𝐚𝐩 𝐰𝐢𝐭𝐡 𝐅𝐫𝐞𝐞 𝐑𝐞𝐬𝐨𝐮𝐫𝐜𝐞𝐬 🔥🔥🔥 |── Basics | ├── What is SQL? | ├── Database vs DBMS vs RDBMS | ├── Databases & Tables | ├── Rows vs Columns | ├── Data Types (INT, VARCHAR, DATE, FLOAT, BOOLEAN) | ├── Constraints (NOT NULL, UNIQUE, PRIMARY KEY, FOREIGN KEY, CHECK, DEFAULT) | ├── Keys (Primary, Foreign, Candidate, Composite, Super Key) | └── CRUD Operations (Create, Read, Update, Delete) | |── DDL (Data Definition Language) | ├── CREATE DATABASE | ├── CREATE TABLE | ├── ALTER TABLE | ├── DROP TABLE | ├── TRUNCATE TABLE | └── RENAME TABLE | |── DML (Data Manipulation Language) | ├── INSERT INTO | ├── UPDATE | ├── DELETE | └── Bulk Inserts | |── DQL (Data Query Language) | ├── SELECT | ├── Column Selection | ├── Aliases (AS) | └── Expressions & Calculations | |── Data Retrieval | ├── SELECT, FROM, WHERE | ├── DISTINCT | ├── ORDER BY (ASC, DESC) | ├── LIMIT / TOP / OFFSET-FETCH | ├── BETWEEN | ├── IN / NOT IN | ├── LIKE (%, _) | └── IS NULL / IS NOT NULL | |── Filtering & Conditions | ├── AND, OR, NOT | ├── Operator Precedence | ├── Nested Conditions | └── Short-circuit Evaluation | |── Joins | ├── INNER JOIN | ├── LEFT JOIN | ├── RIGHT JOIN | ├── FULL OUTER JOIN | ├── CROSS JOIN | ├── SELF JOIN | ├── Join Conditions (ON vs WHERE) | └── Handling NULLs in Joins | |── Grouping & Aggregation | ├── GROUP BY | ├── Aggregate Functions: COUNT(), SUM(), AVG(), MIN(), MAX() | ├── HAVING | ├── Conditional Aggregation (CASE WHEN) | └── Grouping Rules & Errors | |── CASE Statements & Conditional Logic | ├── CASE WHEN | ├── Nested CASE | ├── Conditional Columns | └── Conditional Aggregations | |── NULL Handling | ├── NULL Behavior in SQL | ├── IS NULL, IS NOT NULL | ├── COALESCE() | ├── NULLIF() | └── NULL in Aggregations | |── Subqueries & Nested Queries | ├── Subquery in SELECT | ├── Subquery in WHERE | ├── Subquery in FROM | ├── Correlated Subqueries | ├── Scalar vs Multi-row Subqueries | └── Performance Considerations | |── Set Operations | ├── UNION | ├── UNION ALL | ├── INTERSECT | └── EXCEPT / MINUS | |── Advanced SQL | ├── EXISTS / NOT EXISTS | ├── Derived Tables | ├── Inline Views | ├── Pivoting & Unpivoting | └── Dynamic SQL (Basics) | |── Window Functions (Analytical SQL) | ├── OVER() Clause | ├── PARTITION BY | ├── ORDER BY in Window | ├── Ranking: ROW_NUMBER(), RANK(), DENSE_RANK() | ├── Value Functions: LEAD(), LAG() | ├── Aggregates as Window Functions | └── Running Totals & Moving Averages | |── Common Table Expressions (CTEs) | ├── WITH Clause | ├── Multiple CTEs | ├── Recursive CTEs | └── CTE vs Subquery | |── Views | ├── Creating Views | ├── Updating Views | ├── Materialized Views | └── Use Cases | |── Indexes & Performance | ├── What is Index | ├── Clustered vs Non-Clustered Index | ├── Composite Index | ├── Indexing Strategies | ├── Query Optimization | ├── Execution Plan | └── EXPLAIN / ANALYZE | |── Transactions & ACID | ├── Transaction Basics | ├── COMMIT, ROLLBACK, SAVEPOINT | ├── ACID Properties | └── Concurrency Issues | |── Locks & Isolation Levels | ├── Lock Types | ├── Isolation Levels | ├── Dirty Read, Non-repeatable Read, Phantom Read | └── Deadlocks | |── Database Design Concepts | ├── ER Diagrams | ├── Normalization (1NF, 2NF, 3NF, BCNF) | ├── Denormalization | ├── Relationships (1-1, 1-M, M-M) | └── Schema Design Best Practices | |── Data Warehousing Concepts | ├── OLTP vs OLAP | ├── Fact & Dimension Tables | ├── Star Schema | ├── Snowflake Schema | └── ETL Basics | |── SQL for Data Analysis | ├── Business Metrics (Revenue, Retention, AOV) | ├── Cohort Analysis | ├── Funnel Analysis | ├── Time Series Analysis | └── Data Cleaning in SQL | |── SQL in Real Projects | ├── E-commerce Analysis | ├── Customer Behavior Analysis | ├── Sales Dashboard Queries | └── KPI Reporting | |── Tools & Platforms | ├── MySQL | ├── PostgreSQL | ├── SQL Server | ├── Oracle | ├── SQLite | ├── BigQuery | ├── Snowflake | └── Amazon Redshift | |── END 👉WhatsApp Channel: https://whatsapp.com/channel/0029VaFZ2LbKGGGRCU0lnd46 👉Telegram Channel: https://t.me/dataanalyticsbuddy

👉Telegram Channel: https://t.me/dataanalyticsbuddy Don't forget to share with others who are looking for learning more about SQL 🙌☺️ Till then keep learning and keep exploring 🙌 😊

𝐒𝐐𝐋 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐑𝐨𝐚𝐝𝐦𝐚𝐩 𝐰𝐢𝐭𝐡 𝐅𝐫𝐞𝐞 𝐑𝐞𝐬𝐨𝐮𝐫𝐜𝐞𝐬 🔥🔥🔥 |── Basics | ├── What is SQL? | ├── Database vs DBMS vs RDBMS | ├── Databases & Tables | ├── Rows vs Columns | ├── Data Types (INT, VARCHAR, DATE, FLOAT, BOOLEAN) | ├── Constraints (NOT NULL, UNIQUE, PRIMARY KEY, FOREIGN KEY, CHECK, DEFAULT) | ├── Keys (Primary, Foreign, Candidate, Composite, Super Key) | └── CRUD Operations (Create, Read, Update, Delete) | |── DDL (Data Definition Language) | ├── CREATE DATABASE | ├── CREATE TABLE | ├── ALTER TABLE | ├── DROP TABLE | ├── TRUNCATE TABLE | └── RENAME TABLE | |── DML (Data Manipulation Language) | ├── INSERT INTO | ├── UPDATE | ├── DELETE | └── Bulk Inserts | |── DQL (Data Query Language) | ├── SELECT | ├── Column Selection | ├── Aliases (AS) | └── Expressions & Calculations | |── Data Retrieval | ├── SELECT, FROM, WHERE | ├── DISTINCT | ├── ORDER BY (ASC, DESC) | ├── LIMIT / TOP / OFFSET-FETCH | ├── BETWEEN | ├── IN / NOT IN | ├── LIKE (%, _) | └── IS NULL / IS NOT NULL | |── Filtering & Conditions | ├── AND, OR, NOT | ├── Operator Precedence | ├── Nested Conditions | └── Short-circuit Evaluation | |── Joins | ├── INNER JOIN | ├── LEFT JOIN | ├── RIGHT JOIN | ├── FULL OUTER JOIN | ├── CROSS JOIN | ├── SELF JOIN | ├── Join Conditions (ON vs WHERE) | └── Handling NULLs in Joins | |── Grouping & Aggregation | ├── GROUP BY | ├── Aggregate Functions: COUNT(), SUM(), AVG(), MIN(), MAX() | ├── HAVING | ├── Conditional Aggregation (CASE WHEN) | └── Grouping Rules & Errors | |── CASE Statements & Conditional Logic | ├── CASE WHEN | ├── Nested CASE | ├── Conditional Columns | └── Conditional Aggregations | |── NULL Handling | ├── NULL Behavior in SQL | ├── IS NULL, IS NOT NULL | ├── COALESCE() | ├── NULLIF() | └── NULL in Aggregations | |── Subqueries & Nested Queries | ├── Subquery in SELECT | ├── Subquery in WHERE | ├── Subquery in FROM | ├── Correlated Subqueries | ├── Scalar vs Multi-row Subqueries | └── Performance Considerations | |── Set Operations | ├── UNION | ├── UNION ALL | ├── INTERSECT | └── EXCEPT / MINUS | |── Advanced SQL | ├── EXISTS / NOT EXISTS | ├── Derived Tables | ├── Inline Views | ├── Pivoting & Unpivoting | └── Dynamic SQL (Basics) | |── Window Functions (Analytical SQL) | ├── OVER() Clause | ├── PARTITION BY | ├── ORDER BY in Window | ├── Ranking: ROW_NUMBER(), RANK(), DENSE_RANK() | ├── Value Functions: LEAD(), LAG() | ├── Aggregates as Window Functions | └── Running Totals & Moving Averages | |── Common Table Expressions (CTEs) | ├── WITH Clause | ├── Multiple CTEs | ├── Recursive CTEs | └── CTE vs Subquery | |── Views | ├── Creating Views | ├── Updating Views | ├── Materialized Views | └── Use Cases | |── Indexes & Performance | ├── What is Index | ├── Clustered vs Non-Clustered Index | ├── Composite Index | ├── Indexing Strategies | ├── Query Optimization | ├── Execution Plan | └── EXPLAIN / ANALYZE | |── Transactions & ACID | ├── Transaction Basics | ├── COMMIT, ROLLBACK, SAVEPOINT | ├── ACID Properties | └── Concurrency Issues | |── Locks & Isolation Levels | ├── Lock Types | ├── Isolation Levels | ├── Dirty Read, Non-repeatable Read, Phantom Read | └── Deadlocks | |── Database Design Concepts | ├── ER Diagrams | ├── Normalization (1NF, 2NF, 3NF, BCNF) | ├── Denormalization | ├── Relationships (1-1, 1-M, M-M) | └── Schema Design Best Practices | |── Data Warehousing Concepts | ├── OLTP vs OLAP | ├── Fact & Dimension Tables | ├── Star Schema | ├── Snowflake Schema | └── ETL Basics | |── SQL for Data Analysis | ├── Business Metrics (Revenue, Retention, AOV) | ├── Cohort Analysis | ├── Funnel Analysis | ├── Time Series Analysis | └── Data Cleaning in SQL | |── SQL in Real Projects | ├── E-commerce Analysis | ├── Customer Behavior Analysis | ├── Sales Dashboard Queries | └── KPI Reporting | |── Tools & Platforms | ├── MySQL | ├── PostgreSQL | ├── SQL Server | ├── Oracle | ├── SQLite | ├── BigQuery | ├── Snowflake | └── Amazon Redshift | |── END W3Schools SQL Tutorial: https://www.w3schools.com/sql/ 👉WhatsApp Channel: https://whatsapp.com/channel/0029VaFZ2LbKGGGRCU0lnd46

|── END W3Schools SQL Tutorial: https://www.w3schools.com/sql/ 👉WhatsApp Channel: https://whatsapp.com/channel/0029VaFZ2LbKGGGRCU0lnd46 👉Telegram Channel: https://t.me/dataanalyticsbuddy Don't forget to share with others who are looking for learning more about SQL 🙌☺️ Till then keep learning and keep exploring 🙌 😊

𝐒𝐐𝐋 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐑𝐨𝐚𝐝𝐦𝐚𝐩 𝐰𝐢𝐭𝐡 𝐅𝐫𝐞𝐞 𝐑𝐞𝐬𝐨𝐮𝐫𝐜𝐞𝐬 🔥🔥🔥 |── Basics | ├── What is SQL? | ├── Database vs DBMS vs RDBMS | ├── Databases & Tables | ├── Rows vs Columns | ├── Data Types (INT, VARCHAR, DATE, FLOAT, BOOLEAN) | ├── Constraints (NOT NULL, UNIQUE, PRIMARY KEY, FOREIGN KEY, CHECK, DEFAULT) | ├── Keys (Primary, Foreign, Candidate, Composite, Super Key) | └── CRUD Operations (Create, Read, Update, Delete) | |── DDL (Data Definition Language) | ├── CREATE DATABASE | ├── CREATE TABLE | ├── ALTER TABLE | ├── DROP TABLE | ├── TRUNCATE TABLE | └── RENAME TABLE | |── DML (Data Manipulation Language) | ├── INSERT INTO | ├── UPDATE | ├── DELETE | └── Bulk Inserts | |── DQL (Data Query Language) | ├── SELECT | ├── Column Selection | ├── Aliases (AS) | └── Expressions & Calculations | |── Data Retrieval | ├── SELECT, FROM, WHERE | ├── DISTINCT | ├── ORDER BY (ASC, DESC) | ├── LIMIT / TOP / OFFSET-FETCH | ├── BETWEEN | ├── IN / NOT IN | ├── LIKE (%, _) | └── IS NULL / IS NOT NULL | |── Filtering & Conditions | ├── AND, OR, NOT | ├── Operator Precedence | ├── Nested Conditions | └── Short-circuit Evaluation | |── Joins | ├── INNER JOIN | ├── LEFT JOIN | ├── RIGHT JOIN | ├── FULL OUTER JOIN | ├── CROSS JOIN | ├── SELF JOIN | ├── Join Conditions (ON vs WHERE) | └── Handling NULLs in Joins | |── Grouping & Aggregation | ├── GROUP BY | ├── Aggregate Functions: COUNT(), SUM(), AVG(), MIN(), MAX() | ├── HAVING | ├── Conditional Aggregation (CASE WHEN) | └── Grouping Rules & Errors | |── CASE Statements & Conditional Logic | ├── CASE WHEN | ├── Nested CASE | ├── Conditional Columns | └── Conditional Aggregations | |── NULL Handling | ├── NULL Behavior in SQL | ├── IS NULL, IS NOT NULL | ├── COALESCE() | ├── NULLIF() | └── NULL in Aggregations | |── Subqueries & Nested Queries | ├── Subquery in SELECT | ├── Subquery in WHERE | ├── Subquery in FROM | ├── Correlated Subqueries | ├── Scalar vs Multi-row Subqueries | └── Performance Considerations | |── Set Operations | ├── UNION | ├── UNION ALL | ├── INTERSECT | └── EXCEPT / MINUS | |── Advanced SQL | ├── EXISTS / NOT EXISTS | ├── Derived Tables | ├── Inline Views | ├── Pivoting & Unpivoting | └── Dynamic SQL (Basics) | |── Window Functions (Analytical SQL) | ├── OVER() Clause | ├── PARTITION BY | ├── ORDER BY in Window | ├── Ranking: ROW_NUMBER(), RANK(), DENSE_RANK() | ├── Value Functions: LEAD(), LAG() | ├── Aggregates as Window Functions | └── Running Totals & Moving Averages | |── Common Table Expressions (CTEs) | ├── WITH Clause | ├── Multiple CTEs | ├── Recursive CTEs | └── CTE vs Subquery | |── Views | ├── Creating Views | ├── Updating Views | ├── Materialized Views | └── Use Cases | |── Indexes & Performance | ├── What is Index | ├── Clustered vs Non-Clustered Index | ├── Composite Index | ├── Indexing Strategies | ├── Query Optimization | ├── Execution Plan | └── EXPLAIN / ANALYZE | |── Transactions & ACID | ├── Transaction Basics | ├── COMMIT, ROLLBACK, SAVEPOINT | ├── ACID Properties | └── Concurrency Issues | |── Locks & Isolation Levels | ├── Lock Types | ├── Isolation Levels | ├── Dirty Read, Non-repeatable Read, Phantom Read | └── Deadlocks | |── Database Design Concepts | ├── ER Diagrams | ├── Normalization (1NF, 2NF, 3NF, BCNF) | ├── Denormalization | ├── Relationships (1-1, 1-M, M-M) | └── Schema Design Best Practices | |── Data Warehousing Concepts | ├── OLTP vs OLAP | ├── Fact & Dimension Tables | ├── Star Schema | ├── Snowflake Schema | └── ETL Basics | |── SQL for Data Analysis | ├── Business Metrics (Revenue, Retention, AOV) | ├── Cohort Analysis | ├── Funnel Analysis | ├── Time Series Analysis | └── Data Cleaning in SQL | |── SQL in Real Projects | ├── E-commerce Analysis | ├── Customer Behavior Analysis | ├── Sales Dashboard Queries | └── KPI Reporting | |── Tools & Platforms | ├── MySQL | ├── PostgreSQL | ├── SQL Server | ├── Oracle | ├── SQLite | ├── BigQuery | ├── Snowflake | └── Amazon Redshift | |── Interview Preparation | ├── SQL Query Writing Practice | ├── Case-Based Questions | ├── Optimization Questions | ├── Debugging Queries | └── Explaining Approach Clearly |

SQL Notes by APNA College 🔥 Share with others to help ✨ ✅ Join our Communities: Telegram Channel: https://t.me/dataanalyticsbuddy WhatsApp Channel: https://whatsapp.com/channel/0029VaFZ2LbKGGGRCU0lnd46 Do react ❤️ if you want more resources like this

Last Day to Enroll in Our Self Paced Recorded Course which has everything u need to crack Data Analyst Job and its at 95% Discount 🚨 ENROLLMENTS CLOSING | LIMITED SEATS 🚨 🎓 Data Analytics End-to-End (SELF-PACED) + Placement Cohort 💼 Complete Career Package – ₹399 Only ⏳ Learn at your own pace 📱 Watch anytime | Rewatch anytime 💻 Perfect for students & working professionals ✅ What’s Included: ✔ SELF-PACED COURSE  • SQL (Basics → Advanced, CTEs, Window Functions)  • Power BI (Industry-level Dashboards)  • Excel (Analytics, Pivot Tables, Dynamic Dashboards)  • Python (Pandas, NumPy on Real Datasets) ✔ Placement Cohort – 20 Guided Sessions  • Resume Building  • Interview Preparation  • Real Case Studies  • Mock Interviews & Guidance ✔ 300+ Hands-On Projects ✔ Complete Interview Prep Kit 👨‍🏫 Course by Industry Data Analyst 🔗 https://www.linkedin.com/in/yadavdurgesh711 ⏳ Cohort Seats Are Limited 👉 Enroll Now: 🔗 https://topmate.io/durgesh_yadav/1776905 📩 Queries: durgeshyadavlkh@gmail.com

DATA ANALYST ROADMAP 2026 🔥 Share with others to help ✨ ✅ Join our Communities: Telegram Channel: https://t.me/dataanalyticsbuddy WhatsApp Channel: https://whatsapp.com/channel/0029VaFZ2LbKGGGRCU0lnd46 Do react ❤️ if you want more resources like this

𝗙𝗥𝗘𝗘 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝘁𝗼 𝗟𝗲𝗮𝗿𝗻 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝘁 🔥 1️⃣ Core Skills Every Data Analyst Must Learn 📈 Excel/ Spreadsheets Skills: – Formulas (IF, VLOOKUP/XLOOKUP) – Pivot Tables – Charts – Power Query (basic) Excel - https://www.w3schools.com/excel/ 2️⃣ SQL (Most Important Skill) Skills: – SELECT, WHERE, ORDER BY – JOINs – GROUP BY, HAVING – Subqueries & CTEs – Window Functions SQL - https://www.w3schools.com/sql/ 3️⃣ Python for Data Analysis Skills: – pandas – numpy – matplotlib – seaborn – Data cleaning & EDA Python - https://www.w3schools.com/python/ 4️⃣ Data Visualization Tools Power BI & Tableau Skills: – Data modeling – DAX basics – Filters & slicers – Dashboard design Power BI - https://www.datacamp.com/tutorial/tutorial-power-bi-for-beginners Tableau - https://www.datacamp.com/tutorial/tableau-tutorial-for-beginners For Free resources below channels are best & don't forget to join & share invitation with others as well 👉 WhatsApp Channel: https://whatsapp.com/channel/0029VaFZ2LbKGGGRCU0lnd46 👉 Telegram Channel: https://t.me/dataanalyticsbuddy Don't forget to share with others who are looking for learning more about Data Analyst 🙌 ☺️ Till then keep learning & keep exploring 🙌☺️

*All of you Join Now* Hey All Link to join the Webibar Directly without Enrolment - Direct Link - https://topmate.onlineclass.site/joinPublic/69bd50f1640ea4d20824a9c485391322 Please Join at sharp 8:05 pm and we will understand all about "Killing Jobs of Data Analyst & Whats the new Trend in Market"

🚨 Free Webinar: Data Analyst + AI Agents Learn how to use AI Agents to: ✔ Automate data tasks ✔ Generate SQL queries ✔ Creat
🚨 Free Webinar: Data Analyst + AI Agents Learn how to use AI Agents to: ✔ Automate data tasks ✔ Generate SQL queries ✔ Create reports faster ✔ Extract insights in minutes 👥 For: Data Analysts | Students | Professionals 🗓 20th March 2026 🕒 Friday 8 PM.IST 🔗 Webinar Link : https://topmate.io/durgesh_yadav/2007930

🚨 URGENT: I am shutting down my old WhatsApp groups. If you want my Free Webinars, Job Referrals, and Premium Data Engineering resources, you MUST move to the new Master Group right now. 👉 Secure your spot in the NEW Elite Hub here: 🔗 https://chat.whatsapp.com/DbV99szqITf6qhMBOd52Np 👇 Why am I doing this? And why are there strictly only 1,500 spots? 👇 (WhatsApp "Read more" will likely trigger around here) Managing scattered groups is killing the quality of my mentorship. I am tired of my best content getting lost in the noise. So, I am combining everything into ONE Premium VIP Hub. ⚠️ ACTION REQUIRED: If you are in any of my old groups, LEAVE them immediately. They will be archived soon. Why you need to be in the final 1,500: 🔥 Hidden Job Referrals: Direct hiring alerts from my network. 🔥 Private Free Webinars: Real-world Agentic AI & Data Engineering skills to future-proof your career. 🔥 Massive Cohort Discounts: This group gets VIP pricing (like our current Flat 45-50% OFF) before anyone else even sees it. Once we hit 1,500 members, the link expires forever to keep the quality elite. If you are serious about cracking a top Product-Based Company this year, don't get left in a dead group. Click the link at the top and join the Master Group now. 🚀

🚨 Free Webinar: Data Analyst + AI Agents Learn how to use AI Agents to: ✔ Automate data tasks ✔ Generate SQL queries ✔ Creat
🚨 Free Webinar: Data Analyst + AI Agents Learn how to use AI Agents to: ✔ Automate data tasks ✔ Generate SQL queries ✔ Create reports faster ✔ Extract insights in minutes 👥 For: Data Analysts | Students | Professionals 🗓 20th March 2026 🕒 Friday 8 PM.IST 🔗 Webinar Link : https://topmate.io/durgesh_yadav/2007930

Fill this Google Form if you are Interested for our Cohort at Discounted Prize - https://forms.gle/9S5wZsSquZGKB4DVA Cohort Link - https://topmate.io/durgesh_yadav/page/u9i8z92C1jtK4o15DR Webinar Recordings Link- https://drive.google.com/drive/folders/1R0CUMWVsFChUH4mSCG1Rmdw3WubX9Jo_?usp=drive_link