Udemy - Complete SQL for Data Analytics and Business Intelligence (1.2025)

Creation Time	Aug. 31, 2025, 9:23 a.m.
Last Access Time	Dec. 16, 2025, 6:27 a.m.
File Size	9.5 GB
Keywords	and Complete for 2025 Intelligence - Udemy 1 Analytics SQL Business Data
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Total Files	293
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18. Window Functions/3. The RANK() Window Function.mp4 256.4 MB
19. Common Table Expressions (CTEs)/2. Common Table Expressions (CTEs) In Detail.mp4 170.4 MB
21. Case Study 2 Time Series Analysis with Retail Sales Dataset/6. A Generic and Reusable Date Dimension Table.mp4 165.0 MB
17. Working with JSON Data Type/6. Filtering Records Based on JSON Fields.mp4 156.8 MB
21. Case Study 2 Time Series Analysis with Retail Sales Dataset/5. Date Dimension Table and Fact Table.mp4 151.4 MB
12. Subqueries/8. Correlated Subquery.mp4 150.1 MB
20. SQL for Cleaning Data for Analysis and Reporting/4. Handling Duplicates.mp4 147.1 MB
21. Case Study 2 Time Series Analysis with Retail Sales Dataset/3. Exploratory Data Analysis (EDA).mp4 145.6 MB
12. Subqueries/6. Subquery in JOIN Clause.mp4 143.8 MB
17. Working with JSON Data Type/5. Accessing JSON Fields.mp4 141.8 MB
20. SQL for Cleaning Data for Analysis and Reporting/3. Handling Missing Values.mp4 138.8 MB
21. Case Study 2 Time Series Analysis with Retail Sales Dataset/4. Identifying Sales Trends.mp4 138.2 MB
18. Window Functions/6. The LAG() and LEAD() Window Function.mp4 134.5 MB
21. Case Study 2 Time Series Analysis with Retail Sales Dataset/7. Top Business Categories By Sales.mp4 133.1 MB
21. Case Study 2 Time Series Analysis with Retail Sales Dataset/8. Year-over-Year (YoY) Sales Analysis.mp4 131.4 MB
08. Table Relationships and Constraints/4. Primary Keys.mp4 128.5 MB
20. SQL for Cleaning Data for Analysis and Reporting/1. Section Introduction.mp4 128.4 MB
02. Setting up Local Environment/2. Database Servers and Clients.mp4 128.2 MB
10. Grouping and Aggregating Records/8. Using WHERE and HAVING Together.mp4 124.5 MB
21. Case Study 2 Time Series Analysis with Retail Sales Dataset/2. Importing Data From CSV to PostgreSQL Database.mp4 123.0 MB
05. Reading Data From Table/3. Common String Operators and Functions.mp4 122.5 MB
10. Grouping and Aggregating Records/5. Combining Grouping and Aggregation.mp4 121.6 MB
08. Table Relationships and Constraints/8. Other Column Constraints.mp4 120.3 MB
12. Subqueries/7. Subquery in WHERE Clause.mp4 118.6 MB
16. Working with Array Data Type/8. Array Aggregation.mp4 117.4 MB
13. Case Study 1 Extracting Insights from E-commerce Dataset/15. Solution - Exercise 6.mp4 117.3 MB
09. Joining Tables (SQL Joins)/2. Preparing Dataset.mp4 115.4 MB
10. Grouping and Aggregating Records/2. Aggregate Functions.mp4 114.1 MB
09. Joining Tables (SQL Joins)/5. Left Outer Join.mp4 109.8 MB
09. Joining Tables (SQL Joins)/8. Exercise 1.mp4 107.9 MB
04. Creating Table and Inserting Data into the Table/9. Inserting Data into Table.mp4 107.7 MB
10. Grouping and Aggregating Records/4. Visualizing GROUP BY Operation.mp4 107.1 MB
12. Subqueries/4. Subquery in SELECT Clause.mp4 106.7 MB
08. Table Relationships and Constraints/6. Foreign Key Constraint on Delete.mp4 104.4 MB
08. Table Relationships and Constraints/5. Foreign Keys.mp4 102.8 MB
12. Subqueries/5. Subquery in FROM Clause.mp4 101.8 MB
02. Setting up Local Environment/3. Local Set up - Mac.mp4 101.2 MB
15. Working with Date and Time Data Types/5. Example Truncating Date and Timestamp.mp4 100.1 MB
08. Table Relationships and Constraints/1. Section Introduction.mp4 98.7 MB
09. Joining Tables (SQL Joins)/11. Exercise 3.mp4 93.1 MB
09. Joining Tables (SQL Joins)/4. Inner Join.mp4 91.7 MB
23. Next Steps Roadmap and Career Guidance/1. Data Analyst Data Scientist Roadmap.mp4 91.2 MB
17. Working with JSON Data Type/2. What is JSON.mp4 91.1 MB
13. Case Study 1 Extracting Insights from E-commerce Dataset/8. Exercise 3 Calculate the Average Order Value (AOV).mp4 88.0 MB
18. Window Functions/4. The DENSE_RANK() Window Function.mp4 81.8 MB
15. Working with Date and Time Data Types/3. Time Zone Conversions.mp4 80.6 MB
10. Grouping and Aggregating Records/6. Exercise Using Aggregation with Grouping.mp4 79.9 MB
10. Grouping and Aggregating Records/7. Filtering Groups.mp4 79.6 MB
13. Case Study 1 Extracting Insights from E-commerce Dataset/7. Solution - Exercise 2.mp4 78.8 MB
13. Case Study 1 Extracting Insights from E-commerce Dataset/11. Solution - Exercise 4.mp4 78.5 MB
08. Table Relationships and Constraints/9. Getting Table Schema Information.mp4 78.0 MB
09. Joining Tables (SQL Joins)/12. Exercise 4.mp4 74.0 MB
11. Sorting Records/3. Limiting and Skipping Records.mp4 73.4 MB
18. Window Functions/5. The ROW_NUMBER() Window Function.mp4 71.4 MB
13. Case Study 1 Extracting Insights from E-commerce Dataset/13. Solution - Exercise 5.mp4 70.3 MB
09. Joining Tables (SQL Joins)/6. Right Outer Join.mp4 69.1 MB
20. SQL for Cleaning Data for Analysis and Reporting/5. Handling Outliers.mp4 67.6 MB
09. Joining Tables (SQL Joins)/7. Full Outer Join.mp4 67.3 MB
13. Case Study 1 Extracting Insights from E-commerce Dataset/14. Exercise 6 Show the most recent review for each product.mp4 67.1 MB
10. Grouping and Aggregating Records/3. Why do we group records.mp4 66.1 MB
17. Working with JSON Data Type/7. Constructing JSON Objects.mp4 64.2 MB
16. Working with Array Data Type/9. Exercise Array Aggregation.mp4 61.3 MB
17. Working with JSON Data Type/8. JSON Aggregation.mp4 59.8 MB
20. SQL for Cleaning Data for Analysis and Reporting/8. Consistent Format for Numeric Data.mp4 59.5 MB
09. Joining Tables (SQL Joins)/13. Join with Filter.mp4 57.2 MB
16. Working with Array Data Type/7. Array Functions.mp4 56.8 MB
03. Database Terminologies/4. Creating a Database.mp4 55.9 MB
16. Working with Array Data Type/5. Filtering Records Based on Array Values.mp4 55.5 MB
21. Case Study 2 Time Series Analysis with Retail Sales Dataset/9. Quick Recap of the Key Concepts.mp4 55.4 MB
11. Sorting Records/2. Sorting Records.mp4 52.5 MB
13. Case Study 1 Extracting Insights from E-commerce Dataset/6. Exercise 2 Identify the top selling products.mp4 51.1 MB
02. Setting up Local Environment/4. Local Set up - Windows.mp4 50.7 MB
08. Table Relationships and Constraints/2. One-to-Many and Many-to-One Relationships.mp4 50.6 MB
13. Case Study 1 Extracting Insights from E-commerce Dataset/17. Solution - Exercise 7.mp4 50.0 MB
18. Window Functions/7. LAG() Function - A Practical Use Case.mp4 48.1 MB
14. Type Casting/2. Explicit Type Casting.mp4 48.1 MB
15. Working with Date and Time Data Types/6. Extracting Parts of Date and Timestamp.mp4 47.7 MB
07. Updating and Deleting Records/2. Updating Records in a Table.mp4 47.5 MB
13. Case Study 1 Extracting Insights from E-commerce Dataset/3. Analytics Data Setup.mp4 47.4 MB
09. Joining Tables (SQL Joins)/10. Exercise 2.mp4 47.1 MB
20. SQL for Cleaning Data for Analysis and Reporting/6. Standardizing Values in Categorical Columns.mp4 46.6 MB
02. Setting up Local Environment/5. Getting Familiar with pgAdmin.mp4 46.1 MB
17. Working with JSON Data Type/4. Inserting Data into JSON Columns.mp4 45.2 MB
08. Table Relationships and Constraints/3. One-to-One and Many-to-Many Relationships.mp4 45.0 MB
13. Case Study 1 Extracting Insights from E-commerce Dataset/10. Exercise 4 Calculate the Customer Lifetime Value (CLV).mp4 44.6 MB
06. Filtering Records/2. The WHERE Clause.mp4 44.0 MB
15. Working with Date and Time Data Types/8. Date Math.mp4 42.9 MB
20. SQL for Cleaning Data for Analysis and Reporting/7. Standardizing Text Data.mp4 42.3 MB
15. Working with Date and Time Data Types/4. Truncating Date and Timestamp.mp4 41.9 MB
13. Case Study 1 Extracting Insights from E-commerce Dataset/12. Exercise 5 Identify customers who have not made a purchase in a while.mp4 40.9 MB
04. Creating Table and Inserting Data into the Table/4. Character Data Types.mp4 40.5 MB
03. Database Terminologies/3. Multiple databases and schemas.mp4 40.2 MB
13. Case Study 1 Extracting Insights from E-commerce Dataset/1. Quick Recap!.mp4 40.2 MB
06. Filtering Records/6. Using WHERE with pattern matching.mp4 39.0 MB
19. Common Table Expressions (CTEs)/1. Section Introduction.mp4 38.2 MB
13. Case Study 1 Extracting Insights from E-commerce Dataset/19. Solution - Exercise 8.mp4 37.8 MB
07. Updating and Deleting Records/3. Deleting Records from a Table.mp4 36.8 MB
13. Case Study 1 Extracting Insights from E-commerce Dataset/9. Solution - Exercise 3.mp4 36.3 MB
15. Working with Date and Time Data Types/7. Formatting Date and Timestamp.mp4 35.8 MB
04. Creating Table and Inserting Data into the Table/2. Numeric Data Types.mp4 35.6 MB
06. Filtering Records/3. Comparison operators in WHERE Clause.mp4 35.0 MB
16. Working with Array Data Type/4. Inserting Data into Array Columns.mp4 34.7 MB
12. Subqueries/3. Where is a Subquery Used.mp4 34.7 MB
10. Grouping and Aggregating Records/1. Section Introduction.mp4 34.4 MB
15. Working with Date and Time Data Types/2. Current Date and Time.mp4 34.2 MB
16. Working with Array Data Type/6. Array Indexing.mp4 33.6 MB
13. Case Study 1 Extracting Insights from E-commerce Dataset/16. Exercise 7 Identify the top rated products.mp4 33.4 MB
12. Subqueries/2. What is a Subquery.mp4 33.3 MB
17. Working with JSON Data Type/3. Adding Columns of JSON Data Type.mp4 32.9 MB
06. Filtering Records/5. Using WHERE within a specified range.mp4 32.7 MB
16. Working with Array Data Type/2. What is an Array.mp4 32.6 MB
01. Introduction to Data Analytics/1. Data Roles and Responsibilities.mp4 32.4 MB
16. Working with Array Data Type/3. Adding Columns of Array Data Type.mp4 32.3 MB
21. Case Study 2 Time Series Analysis with Retail Sales Dataset/1. Section Introduction.mp4 31.5 MB
04. Creating Table and Inserting Data into the Table/8. Creating a Table.mp4 30.2 MB
14. Type Casting/3. Implicit Type Casting.mp4 29.6 MB
05. Reading Data From Table/4. Using Comments in SQL.mp4 29.6 MB
13. Case Study 1 Extracting Insights from E-commerce Dataset/2. Section Introduction.mp4 28.9 MB
08. Table Relationships and Constraints/7. Foreign Key Constraint on Insert.mp4 28.5 MB
13. Case Study 1 Extracting Insights from E-commerce Dataset/5. Solution - Exercise 1.mp4 28.0 MB
06. Filtering Records/7. Compound WHERE Clause.mp4 27.8 MB
17. Working with JSON Data Type/1. Section Introduction.mp4 27.8 MB
04. Creating Table and Inserting Data into the Table/7. Other Important Data Types.mp4 27.6 MB
16. Working with Array Data Type/1. Section Introduction.mp4 26.8 MB
13. Case Study 1 Extracting Insights from E-commerce Dataset/18. Exercise 8 Calculate discount based on order value.mp4 26.3 MB
13. Case Study 1 Extracting Insights from E-commerce Dataset/4. Exercise 1 Calculate the total revenue.mp4 26.1 MB
09. Joining Tables (SQL Joins)/9. Table and Column Alias.mp4 26.0 MB
05. Reading Data From Table/2. The SELECT statement.mp4 25.9 MB
06. Filtering Records/4. Using WHERE with a List of Values.mp4 25.8 MB
16. Working with Array Data Type/10. Flattening of Arrays.mp4 25.3 MB
04. Creating Table and Inserting Data into the Table/5. Date and Time Data Types.mp4 21.3 MB
09. Joining Tables (SQL Joins)/3. Why do we need Joins.mp4 20.4 MB
07. Updating and Deleting Records/4. Dropping a Table from Database.mp4 19.8 MB
20. SQL for Cleaning Data for Analysis and Reporting/2. Data Setup.mp4 19.8 MB
14. Type Casting/1. Section Introduction.mp4 19.0 MB
03. Database Terminologies/2. Tables.mp4 16.9 MB
04. Creating Table and Inserting Data into the Table/1. Section Introduction.mp4 16.8 MB
03. Database Terminologies/1. Database and Schema.mp4 16.3 MB
15. Working with Date and Time Data Types/1. Section Introduction.mp4 12.0 MB
09. Joining Tables (SQL Joins)/1. Section Introduction.mp4 11.4 MB
18. Window Functions/2. Data Setup.mp4 10.0 MB
12. Subqueries/1. Section Introduction.mp4 8.1 MB
18. Window Functions/1. Section Introduction.mp4 7.4 MB
11. Sorting Records/1. Section Introduction.mp4 7.3 MB
04. Creating Table and Inserting Data into the Table/6. Boolean Data Type.mp4 6.5 MB
06. Filtering Records/1. Section Introduction.mp4 5.7 MB
07. Updating and Deleting Records/1. Section Introduction.mp4 5.5 MB
05. Reading Data From Table/1. Section Introduction.mp4 5.4 MB
21. Case Study 2 Time Series Analysis with Retail Sales Dataset/2. us_retail_sales.csv 1.3 MB
02. Setting up Local Environment/1. Section Introduction.mp4 1.1 MB
09. Joining Tables (SQL Joins)/7. full_join.png 683.1 KB
09. Joining Tables (SQL Joins)/6. right_join.png 641.4 KB
18. Window Functions/8. 2024-11-21_13-44-00-0eb1e38674b8bf9602a76bf0eac228b2.png 626.4 KB
09. Joining Tables (SQL Joins)/5. left_join.png 626.2 KB
09. Joining Tables (SQL Joins)/4. inner_join.png 577.9 KB
10. Grouping and Aggregating Records/9. 2024-11-10_17-59-04-8600b09d5bdaa0bd281190ac1a380b0a.png 347.5 KB
02. Setting up Local Environment/2. server_client.png 344.4 KB
02. Setting up Local Environment/6. 2024-12-02_14-38-07-ea5fafe8a3a58701a11f427500a28607.png 344.4 KB
13. Case Study 1 Extracting Insights from E-commerce Dataset/1. sql_topics.png 282.9 KB
18. Window Functions/1. window_functions.png 276.0 KB
18. Window Functions/8. 2024-11-21_13-44-00-f4657878fbc6ca7ce6d115a864555b14.png 276.0 KB
16. Working with Array Data Type/11. 2024-11-19_12-03-27-ef3be7da1bf82e66c276e569f9e49097.png 274.3 KB
16. Working with Array Data Type/2. array_datatype.png 274.3 KB
20. SQL for Cleaning Data for Analysis and Reporting/1. analysis_process.png 210.6 KB
20. SQL for Cleaning Data for Analysis and Reporting/9. 2024-11-23_19-58-44-059632582b9adcf9ba495eeec822bced.png 210.6 KB
18. Window Functions/7. lag_ex.png 206.7 KB
13. Case Study 1 Extracting Insights from E-commerce Dataset/1. order_exec.png 183.5 KB
06. Filtering Records/8. 2024-11-05_14-37-46-5a167c0f7681a228041f564c25cd2542.png 100.7 KB
06. Filtering Records/9.6 Comparison Operators and Pattern Matching.html 24.9 KB
08. Table Relationships and Constraints/11.8 Table Relationships and Column Constraints.html 23.0 KB
04. Creating Table and Inserting Data into the Table/11.3 Data Types.html 22.9 KB
09. Joining Tables (SQL Joins)/15.9 Joining Tables.html 22.5 KB
11. Sorting Records/5.11 Sorting, Limiting and Skipping Records.html 21.0 KB
07. Updating and Deleting Records/6.7 Update and Delete Operations.html 20.3 KB
05. Reading Data From Table/6.4 String Operators and Functions.html 19.7 KB
10. Grouping and Aggregating Records/10.10 Grouping and Aggregating Records.html 19.3 KB
12. Subqueries/10.12 Subqueries.html 18.6 KB
03. Database Terminologies/5.1 Database Schema.html 16.6 KB
05. Reading Data From Table/7.5 Alias for column name.html 16.2 KB
04. Creating Table and Inserting Data into the Table/3.2 SERIAL Data Type.html 16.2 KB
20. SQL for Cleaning Data for Analysis and Reporting/9. Lecture Notes.html 9.9 KB
08. Table Relationships and Constraints/10. Lecture Notes.html 9.4 KB
22. Some More Interview Questions From Top Companies/2.15 Interview Question (CVS Health).html 8.6 KB
21. Case Study 2 Time Series Analysis with Retail Sales Dataset/10.13 Interview Question (Wayfair).html 7.8 KB
09. Joining Tables (SQL Joins)/16.2 Interview Question (TikTok).html 7.7 KB
19. Common Table Expressions (CTEs)/4.12 Interview Question (LinkedIn).html 7.7 KB
18. Window Functions/10.11 Interview Question (Amazon).html 7.3 KB
22. Some More Interview Questions From Top Companies/4.17 Interview Question (Facebook).html 7.1 KB
15. Working with Date and Time Data Types/10.9 Interview Question (Microsoft).html 6.9 KB
12. Subqueries/12.8 Interview Question (FAANG).html 6.8 KB
06. Filtering Records/10.1 Interview Question (Tesla).html 6.5 KB
11. Sorting Records/7.6 Interview Question (CVS Health) Part 2.html 6.4 KB
22. Some More Interview Questions From Top Companies/3.16 Interview Question (UnitedHealth Group).html 6.4 KB
22. Some More Interview Questions From Top Companies/1.14 Interview Question (JP Morgan).html 6.2 KB
11. Sorting Records/6.5 Interview Question (CVS Health) Part 1.html 6.1 KB
22. Some More Interview Questions From Top Companies/5.18 Interview Question (Amazon).html 6.0 KB
10. Grouping and Aggregating Records/12.4 Interview Question (New York Times).html 6.0 KB
12. Subqueries/11.7 Interview Question (Facebook).html 6.0 KB
17. Working with JSON Data Type/9. Lecture Notes.html 5.7 KB
18. Window Functions/9.10 Interview Question (Uber).html 5.7 KB
15. Working with Date and Time Data Types/9. Lecture Notes.html 5.5 KB
10. Grouping and Aggregating Records/11.3 Interview Question (LinkedIn).html 5.4 KB
13. Case Study 1 Extracting Insights from E-commerce Dataset/3. analytical_dataset.sql 4.6 KB
04. Creating Table and Inserting Data into the Table/10. Lecture Notes.html 4.5 KB
09. Joining Tables (SQL Joins)/14. Lecture Notes.html 4.2 KB
18. Window Functions/8. Lecture Notes.html 3.7 KB
16. Working with Array Data Type/11. Lecture Notes.html 3.4 KB
10. Grouping and Aggregating Records/9. Lecture Notes.html 3.3 KB
12. Subqueries/9. Lecture Notes.html 2.9 KB
09. Joining Tables (SQL Joins)/2. shopeasy_dataset.sql 2.8 KB
21. Case Study 2 Time Series Analysis with Retail Sales Dataset/9. key_concepts.sql 2.8 KB
17. Working with JSON Data Type/6. filter.sql 1.9 KB
13. Case Study 1 Extracting Insights from E-commerce Dataset/9. 3_average_order_value.sql 1.7 KB
20. SQL for Cleaning Data for Analysis and Reporting/2. data_setup.sql 1.7 KB
11. Sorting Records/4. Lecture Notes.html 1.5 KB
21. Case Study 2 Time Series Analysis with Retail Sales Dataset/6. date_dim_table.sql 1.5 KB
03. Database Terminologies/6. Lecture Notes.html 1.4 KB
21. Case Study 2 Time Series Analysis with Retail Sales Dataset/3. eda.sql 1.4 KB
05. Reading Data From Table/5. Lecture Notes.html 1.3 KB
15. Working with Date and Time Data Types/8. date_math.sql 1.3 KB
19. Common Table Expressions (CTEs)/3. Lecture Notes.html 1.3 KB
07. Updating and Deleting Records/5. Lecture Notes.html 1.3 KB
15. Working with Date and Time Data Types/7. to_char.sql 1.2 KB
06. Filtering Records/8. Lecture Notes.html 1.2 KB
15. Working with Date and Time Data Types/6. extract.sql 1.2 KB
14. Type Casting/4. Lecture Notes.html 1.1 KB
20. SQL for Cleaning Data for Analysis and Reporting/4. removing_duplicates.sql 1.1 KB
13. Case Study 1 Extracting Insights from E-commerce Dataset/15. 6_reviews_in_real_time.sql 1.1 KB
15. Working with Date and Time Data Types/4. date_trunc.sql 1.0 KB
12. Subqueries/7. where_subquery.sql 1005 bytes
15. Working with Date and Time Data Types/6. date_part.sql 1000 bytes
13. Case Study 1 Extracting Insights from E-commerce Dataset/19. 8_discount_order_value.sql 926 bytes
19. Common Table Expressions (CTEs)/2. cte_example.sql 884 bytes
06. Filtering Records/8. filtering_records.sql 883 bytes
17. Working with JSON Data Type/4. insert_data.sql 866 bytes
02. Setting up Local Environment/6. Lecture Notes.html 851 bytes
03. Database Terminologies/7. Interview Questions.html 741 bytes
17. Working with JSON Data Type/5. access.sql 737 bytes
10. Grouping and Aggregating Records/2. aggregate_functions.sql 726 bytes
09. Joining Tables (SQL Joins)/6. right_join.sql 717 bytes
11. Sorting Records/3. limit_offset.sql 713 bytes
13. Case Study 1 Extracting Insights from E-commerce Dataset/13. 5_customers_not_purchased.sql 685 bytes
21. Case Study 2 Time Series Analysis with Retail Sales Dataset/8. yoy_sales_growth.sql 682 bytes
18. Window Functions/6. lag_lead.sql 665 bytes
13. Case Study 1 Extracting Insights from E-commerce Dataset/11. 4_customer_lifetime_value.sql 663 bytes
13. Case Study 1 Extracting Insights from E-commerce Dataset/17. 7_top_rated_products.sql 663 bytes
21. Case Study 2 Time Series Analysis with Retail Sales Dataset/5. date_dim.sql 650 bytes
12. Subqueries/5. from_subquery.sql 633 bytes
18. Window Functions/2. data_setup.sql 614 bytes
15. Working with Date and Time Data Types/2. current_date_time.sql 592 bytes
09. Joining Tables (SQL Joins)/5. left_join.sql 565 bytes
21. Case Study 2 Time Series Analysis with Retail Sales Dataset/7. top_businesses.sql 548 bytes
17. Working with JSON Data Type/7. constructing_json.sql 547 bytes
09. Joining Tables (SQL Joins)/4. inner_join.sql 532 bytes
20. SQL for Cleaning Data for Analysis and Reporting/6. categorical_column.sql 527 bytes
21. Case Study 2 Time Series Analysis with Retail Sales Dataset/2. data_setup.sql 502 bytes
04. Creating Table and Inserting Data into the Table/9. insert_rows.sql 484 bytes
17. Working with JSON Data Type/8. aggregation.sql 471 bytes
20. SQL for Cleaning Data for Analysis and Reporting/3. missing_values.sql 462 bytes
13. Case Study 1 Extracting Insights from E-commerce Dataset/7. 2_top_selling_products.sql 454 bytes
05. Reading Data From Table/3. string_functions.sql 450 bytes
12. Subqueries/8. correlated_subquery.sql 447 bytes
12. Subqueries/4. select_subquery.sql 428 bytes
21. Case Study 2 Time Series Analysis with Retail Sales Dataset/4. trends.sql 416 bytes
20. SQL for Cleaning Data for Analysis and Reporting/5. handling_outliers.sql 413 bytes
09. Joining Tables (SQL Joins)/7. full_outer.sql 399 bytes
13. Case Study 1 Extracting Insights from E-commerce Dataset/5. 1_total_revenue.sql 389 bytes
07. Updating and Deleting Records/2. update_records.sql 374 bytes
16. Working with Array Data Type/7. array_functions.sql 363 bytes
12. Subqueries/6. join_subqueries.sql 350 bytes
14. Type Casting/2. explicit_type_casting.sql 310 bytes
16. Working with Array Data Type/5. filter_records.sql 295 bytes
11. Sorting Records/2. sorting_records.sql 283 bytes
16. Working with Array Data Type/9. array_agg_exercise.sql 282 bytes
15. Working with Date and Time Data Types/5. date_trunc_ex.sql 270 bytes
10. Grouping and Aggregating Records/8. where_having.sql 268 bytes
14. Type Casting/3. implicit_type_casting.sql 262 bytes
18. Window Functions/3. rank.sql 248 bytes
15. Working with Date and Time Data Types/3. time_zone-conversions.sql 239 bytes
18. Window Functions/4. dense_rank.sql 236 bytes
07. Updating and Deleting Records/3. delete_records.sql 207 bytes
04. Creating Table and Inserting Data into the Table/8. create_table.sql 199 bytes
16. Working with Array Data Type/4. insert_data.sql 180 bytes
12. Subqueries/2. subquery_ex1.sql 178 bytes
18. Window Functions/5. row_number.sql 169 bytes
20. SQL for Cleaning Data for Analysis and Reporting/7. text_data.sql 168 bytes
10. Grouping and Aggregating Records/7. having_clause.sql 163 bytes
16. Working with Array Data Type/8. array_agg.sql 140 bytes
17. Working with JSON Data Type/3. add_column.sql 107 bytes
16. Working with Array Data Type/3. add_column.sql 104 bytes
16. Working with Array Data Type/10. array_flat.sql 103 bytes
20. SQL for Cleaning Data for Analysis and Reporting/8. number_format.sql 97 bytes
16. Working with Array Data Type/6. array_index.sql 96 bytes

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