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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 |

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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 🙌☺️

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🚨 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 ✔ 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

Hey everyone! Since you took the time to attend our last webinars , I wanted to give you this link before we announce it to the general public. As we discussed, the industry is rapidly shifting away from basic SQL/Excel and moving heavily toward Data Engineering, Spark, and Agentic AI. To help you bridge that gap, we are officially opening applications for Batch 2 of the Engineering Analytics Cohort (Starting the first week of April). Because you are part of this community, we are offering a limited 45- 50% Grant to early applicants. 👉 Fill out the fast-track application form here to see if you qualify: https://forms.gle/9S5wZsSquZGKB4DVA Note: This program includes 3 Capstone Projects AND a 3-month Internship Certificate from Topmate.io. Seats will fill fast. If you have any questions, just reply to this message or DM the admins! 🚀