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Section 1: Introduction
Master Snowflake Data Warehousing: Tamil Course Promo
1. Finding Your IT Path: Choosing the Right Career & Structuring Your Journey
Section 2: Understanding Databases, Warehouses, ETL, SQL & Snowflake
2. Decoding Data: A Professional Explanation
3. Understanding Databases: The Why and How of Data Storage
4. ETL Explained: Mastering the Process of Data Integration
5. Data Warehouses: Why and How We Use Them
6. Reporting and Analysis: Tools in Today's Data Landscape
7. Generations in Data Warehousing: Evolution and Innovation
8. On-Premises vs. Cloud: Why Snowflake Reigns Supreme
9. Why SQL Matters: Simplifying Data Management
Section 3: Kickstarting Your Journey: Essential Tools Installation
10. Step-by-Step: Installing Notepad++ for Beginners
11. Unlocking Snowflake: How to Activate Your Account with Ease
12. Fetching Employee Data: A Snowflake Tutorial for Beginners
Section 4: Understanding SQL Clauses: Building Blocks of Data Queries
13. SQL Essentials: SELECT & FROM Clauses
14. SQL Essentials: ORDER BY Clauses
15. SQL Essentials: WHERE Clauses
16. SQL Essentials: DISTINCT Clauses
Section 5: SQL Operators
17. Mastering SQL Arithmetic Operators: Comprehensive Guide
18. SQL Column Alias Mastery: Renaming Columns Like a Pro
19. SQL Concatenation: Merging Data Seamlessly
20. SQL Comparison Operators Explained
21. Understanding SQL Special Operators
22. SQL Logical Operators Demystified
23. SQL Set Operators Explained
Section 6: SQL Single Row Functions
24. Beginner's Guide: Dive into Snowflake SQL Functions
25. SQL: CASE Functions
26. SQL: LENGTH Function
27. SQL: TRIM | LTRIM | RTRIM Function
28. SQL: TRANSLATE Function
29. SQL: REPLACE Function
30. SQL: REVERSE Function
31. SQL: SUBSTR Function
32. SQL: INSTR Function
33. SQL: SUBSTR & INSTR Function
34. SQL: NUMBER Function
35. SQL: CONVERSION Function
36. SQL: DATE Function
37. SQL: DECODE Function
38. SQL: CASE Statement
39. SQL: NVL Function
40. SQL: NVL2 Function
41. SQL: NULLIF Function
42. SQL: COALESCE Function
43. SQL: CONTEXT Function
Section 7: SQL Multiple Row Functions
44. SQL: GROUP Function
45. SQL: Group Function Rules & Group By, Having Clause
Section 8: SQL Windows Functions
46. SQL: RANK Function
47. SQL: DENSE_RANK Function
48. SQL: ROW_NUMBER Function
49. SQL: LEAD & LAG Function
50. SQL: LISTAGG Function
51. SQL: Partition By Clause
52. SQL: WITH Clause or Common Table Expression (CTE)
53. SQL: Qualify Clause
Section 9: SQL Table Functions
54. SQL: Table Functions
Section 10: SQL System Function
55. SQL: System Function
Section 11: Deep Dive: SQL Joins
56. SQL: The Inner Join Technique
57. SQL: The Right Join Technique
58. SQL: The Left Join Technique
59. SQL: The Full Join Technique
60. SQL: The Cross Join Technique
61. SQL: Joins Frequently asked Interview Question
62. SQL: The Self Join Technique
63. SQL: Multiple tables Join Techniques
Section 12: Subqueries in SQL
64. SQL Essentials: Subquery Introduction
65. SQL Essentials: Scalar Subquery Techniques
66. SQL Essentials: Inline View Subquery Techniques
67. SQL Essentials: Nested Subquery Techniques
68. SQL Essentials: Single Row Subquery Techniques
69. SQL Essentials: Multiple Row Subquery Techniques
70. SQL Essentials: Correlated Subquery Techniques
Section 13: Introduction to Snowflake and DQL
71. The Basics of Data Query Language (DQL)
Section 14: Mastering Snowflake DDL: From Basics to Advanced
72. Introduction to Snowflake and DDL
73. Working with CREATE command
74. Understanding the DATA TYPES
75. Working with ALTER command
76. Working with DROP command
77. Working with COMMENT command
78. Working with DESCRIBE command
79. Working with SHOW command
80. Working with USE command
Section 15: Mastering Snowflake DML
81. Introduction to Snowflake and DML
82. Working with Manual Load
83. Working with Snowsight Load
84. Working with Snowsql Load
85. Working with Internal Stages
86. Working with PUT command
87. Working with LIST command
88. Working with COPY command
89. Practical ELT Process Implementation
90. Practical ETL Process Implementation
91. Working with FORCE command
92. Working with REMOVE command
93. Working with PURGE command
94. Working with GET command
95. Practical Data Ingestion Techniques with AWS
96. Loading Data from AWS to Snowflake with Validation and Validation_mode command
97. Mastering Snowpipe: Efficiently Load and Validate with Pipe Functions
98. Azure Data Loading
99. Azure Data Loading with Snowpipe Implementation
100. Mastering Data Manipulation: The 'UPDATE' Command in Snowflake
101. Mastering Data Manipulation: The 'DELETE' Command in Snowflake
102. Mastering Data Manipulation: 'TRUNCATE' vs 'DELETE' in Snowflake Explained
Section 16: Cracking the Code: Handling Duplicate Removal in Technical Interviews
103. Decoding Duplicates: An Overview of Types and Their Significance
104. Dive Deep into Duplicates: Leveraging Aggregate Functions with 'GROUP BY' Clause
105. Finding Duplicates: Using Analytical Functions
106. Detecting Duplicates: The 'WITH' Clause Approach
107. Finding Duplicates: Using Subqueries
108. Eliminating Duplicates: Aggregate Functions & 'GROUP BY' Technique
109. Clearing Duplicates: Using Analytical Functions
110. De-duplicating Data: The 'WITH' Clause Method
111. Erasing Duplicates: Utilizing Subqueries
112. Pruning Data: Removing Full Column Duplicates
Section 17: Mastering TCL Commands in Snowflake
113. Transaction Essentials: COMMIT, ROLLBACK, and BEGIN in Practice
Section 18: Understanding Constraints in Snowflake
114. Building Solid Foundations: Keys & Constraints Explained
Section 19: Snowflake Architecture Overview
115. Snowflake: Exploring the Database Storage Layer
116. Snowflake: Dive into the Query Processing Layer
117. Snowflake: Understanding the Cloud Service Layer
118. Snowflake: Mastering Resource Monitors
Section 20: Snowflake: Exploring Caching Mechanisms
119. Snowflake Caching: Metadata, Results, and Warehouse Explained
Section 21: Understanding Micro-Partitions
120. Snowflake: Micro-Partition, Cluster Key, and Pruning
Section 22: Understanding Time Travel
121. Snowflake: Time Travel & Fail-Safe Explained
Section 23: Exploring Different Types of Tables
122. Snowflake: Permanent, Temporary, and Transient Tables Explained
123. Snowflake: Introduction to External Tables
Section 24: Snowflake: Mastering Incremental Load Techniques
124. Snowflake: A Beginner's Guide to Incremental Load
125. Snowflake Streams: Optimizing Incremental Data Loads
126. Snowflake Techniques: Subquery-Driven Incremental Loads
127. Snowflake Insights: Full Loads with Dynamic Tables
128. Snowflake Mastery: Incremental Loads with the MERGE Command
Section 25: Getting Started with Tasks
129. Snowflake Tasks: Standalone vs. Tree Structures Explained
Section 26: Diving into Cloning Techniques
130. Snowflake Deep Dive: Cloning vs. Backup Strategies
Section 27: Understanding DCL Operations
131. Snowflake Permissions: Mastering GRANT and REVOKE Commands
Section 28: Crafting and Managing Views
132. Snowflake Views: Comparing Normal and Secure Variants
133. Snowflake Deep Dive: Making the Most of Materialized Views
Section 29: Mastering Data Masking Techniques
134. Snowflake Explained: Unpacking Data Masking Concepts
Section 30: Understanding Sequences
135. Snowflake: Sequence Explained
Section 31: Getting Started with Data Sharing
136. Snowflake: Data Sharing Explained
Section 32: Snowflake: Dive into User-Defined Functions (UDFs)
137. Snowflake: UDFs Explained
Section 33: Understanding Stored Procedures Understanding Data
138. Snowflake: Stored Procedures Explained
Section 34: Understanding Data Warehouses: Foundations and Functionality
139. Deep Dive: Data Warehouse Architecture Explained
140. Data Warehouse Design: Top-Down vs. Bottom-Up Approaches Compared
141. Data Warehouse Foundations: Mastering ERD Modeling
142. Data Warehouse Design: Dive into Dimension Modeling
143. Demystifying Data Warehouse Dimensions: Types and Strategies
144. Mastering Role-Playing Dimensions: A Key to Data Warehouse Success
145. Unlocking Data Consistency: Conformed Dimensions in Data Warehousing
146. Simplify Your Data Warehousing: Exploring Junk Dimensions
147. Simplified Data Warehousing: Degenerated Dimensions Explained
148. Mastering Slowly Changing Dimensions: Your Data Warehouse Guide
149. Adapting to Change: Rapidly Changing Dimensions in Data Warehousing
150. Getting Started with Fact Tables in Data Warehousing
151. Fully Additive Fact Tables Simplified for Data Warehousing
152. Semi-Additive Fact Tables Made Easy in Data Warehousing
153. Understanding Non-Additive Fact Tables in Data Warehousing
154. Decoding Data Warehouse Schemas: An Introduction
155. Demystifying Star Schemas in Data Warehousing
156. Simplified: Snowflake Schema in Data Warehousing
157. Snowflake Schema vs. Snowflake Method: Data Warehouse Showdown
158. Normalization vs. Denormalization Simplified