SQL Server Day 3 | WHERE Clause, GROUP BY & Real Data Analysis | SQL for Data Analyst | Scientist

In Day 3 of the SQL Server Complete Course, we dive deeper into databases, SQL and NoSQL concepts, and their real-world usage with practical examples. This session focuses on how structured and unstructured data is stored, queried, filtered, updated, and analyzed using SQL queries. You will learn how SQL works internally, how NoSQL databases like MongoDB differ, and how to handle real datasets such as e-commerce data. The video explains data import using CSV files, data types, NULL value handling, logical and comparison operators, and aggregation functions like COUNT, SUM, AVG, MIN, and MAX. This session is extremely useful for: SQL beginners Data Analysts Web & Backend Developers Database learners Anyone preparing for real-world SQL projects or interviews The video also touches upon modern AI-based query tools (Chat Query) and how they may influence the future of database management. ⏱️ Timeline / Chapters (Day 3) 00:00 – 03:40 – Introduction & importance of SQL in databases 03:40 – 07:20 – NoSQL overview, MongoDB & use cases 07:20 – 12:40 – SQL tools: MySQL & SQL Server basics 12:40 – 20:40 – Writing SQL queries, schema & tables 20:40 – 25:10 – SELECT, FROM, WHERE clause explained 25:10 – 33:50 – Data import using CSV & SQL data types 33:50 – 44:00 – WHERE clause operators (comparison & logical) 44:00 – 50:40 – IN, NOT IN & multiple conditions 50:40 – 57:45 – GitHub datasets for SQL practice 57:45 – 01:10:40 – E-commerce data analysis, DISTINCT, COUNT, GROUP BY 01:10:40 – 01:15:00 – Tables, metadata & schema usage 01:15:00 – 01:25:00 – Aggregation functions (SUM, AVG, MIN, MAX) 01:25:00 – 01:33:00 – NULL values, IS NULL, IS NOT NULL 01:33:00 – 01:52:30 – UPDATE queries & data handling precautions 01:52:30 – End – Next class preview & AI tools in database future 🎯 Key Takeaways 💡 Understand data types clearly – structured vs unstructured data 💡 SQL core commands – DDL, DML, DCL, TCL explained practically 💡 CSV format is best for large data imports 💡 Power of WHERE clause & operators for filtering data 💡 Aggregation functions help summarize large datasets 💡 NULL values need careful handling in real projects 💡 E-commerce datasets give real-world SQL experience 💡 Database objects (schema, tables) must be well-managed 💡 AI tools & Chat Queries may change how databases are queried ❓ Frequently Asked Questions (FAQs) 1. What is the main difference between SQL and NoSQL? SQL is used for structured, table-based data, while NoSQL is flexible and handles unstructured or file-based data. 2. Why is CSV preferred for data import? CSV supports very large datasets and avoids formatting issues common in Excel. 3. How should NULL values be handled in SQL? Use IS NULL or IS NOT NULL carefully to avoid incorrect results or data loss. 4. Why is WHERE clause important in SQL? It filters only the required records, improving accuracy and performance. 5. Why do companies restrict UPDATE and DELETE permissions? To prevent accidental data loss; such operations are usually limited to experienced users. 📌 Conclusion This Day 3 session provides a solid practical understanding of SQL and NoSQL databases, focusing on data import, querying, filtering, aggregation, and analysis. Learners gain hands-on exposure to real datasets, understand how to deal with NULL values, and see how modern AI-based query tools may shape the future of database management. 🚀 Action Steps Practice SQL queries daily on real datasets Install and explore SQL Server, MySQL & MongoDB Use GitHub datasets for hands-on projects Pay special attention to NULL values & data validation Stay updated with AI-based database tools #SQLDay3 #SQLServer #LearnSQL #SQLQueries #NoSQL #MongoDB #DatabaseManagement #DataAnalytics #StructuredData #UnstructuredData #SQLPractice #EcommerceData #DataAnalysis #CodingAnalyticsWithAnkit #ITCareer #SQLInterview