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

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

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种子哈希：1100193c75dfa90c77ae198576f0cee6be29eec7
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收录时间：2025-09-01
最近下载：2025-09-02

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文件列表

  • 18. Window Functions/3. The RANK() Window Function.mp4 268.8 MB
  • 19. Common Table Expressions (CTEs)/2. Common Table Expressions (CTEs) In Detail.mp4 178.6 MB
  • 21. Case Study 2 Time Series Analysis with Retail Sales Dataset/6. A Generic and Reusable Date Dimension Table.mp4 173.0 MB
  • 17. Working with JSON Data Type/6. Filtering Records Based on JSON Fields.mp4 164.5 MB
  • 21. Case Study 2 Time Series Analysis with Retail Sales Dataset/5. Date Dimension Table and Fact Table.mp4 158.7 MB
  • 12. Subqueries/8. Correlated Subquery.mp4 157.4 MB
  • 20. SQL for Cleaning Data for Analysis and Reporting/4. Handling Duplicates.mp4 154.2 MB
  • 21. Case Study 2 Time Series Analysis with Retail Sales Dataset/3. Exploratory Data Analysis (EDA).mp4 152.7 MB
  • 12. Subqueries/6. Subquery in JOIN Clause.mp4 150.8 MB
  • 17. Working with JSON Data Type/5. Accessing JSON Fields.mp4 148.7 MB
  • 20. SQL for Cleaning Data for Analysis and Reporting/3. Handling Missing Values.mp4 145.6 MB
  • 21. Case Study 2 Time Series Analysis with Retail Sales Dataset/4. Identifying Sales Trends.mp4 144.9 MB
  • 18. Window Functions/6. The LAG() and LEAD() Window Function.mp4 141.1 MB
  • 21. Case Study 2 Time Series Analysis with Retail Sales Dataset/7. Top Business Categories By Sales.mp4 139.6 MB
  • 21. Case Study 2 Time Series Analysis with Retail Sales Dataset/8. Year-over-Year (YoY) Sales Analysis.mp4 137.8 MB
  • 08. Table Relationships and Constraints/4. Primary Keys.mp4 134.7 MB
  • 20. SQL for Cleaning Data for Analysis and Reporting/1. Section Introduction.mp4 134.7 MB
  • 02. Setting up Local Environment/2. Database Servers and Clients.mp4 134.4 MB
  • 10. Grouping and Aggregating Records/8. Using WHERE and HAVING Together.mp4 130.5 MB
  • 21. Case Study 2 Time Series Analysis with Retail Sales Dataset/2. Importing Data From CSV to PostgreSQL Database.mp4 128.9 MB
  • 05. Reading Data From Table/3. Common String Operators and Functions.mp4 128.4 MB
  • 10. Grouping and Aggregating Records/5. Combining Grouping and Aggregation.mp4 127.5 MB
  • 08. Table Relationships and Constraints/8. Other Column Constraints.mp4 126.1 MB
  • 12. Subqueries/7. Subquery in WHERE Clause.mp4 124.3 MB
  • 16. Working with Array Data Type/8. Array Aggregation.mp4 123.1 MB
  • 13. Case Study 1 Extracting Insights from E-commerce Dataset/15. Solution - Exercise 6.mp4 123.0 MB
  • 09. Joining Tables (SQL Joins)/2. Preparing Dataset.mp4 121.0 MB
  • 10. Grouping and Aggregating Records/2. Aggregate Functions.mp4 119.6 MB
  • 09. Joining Tables (SQL Joins)/5. Left Outer Join.mp4 115.1 MB
  • 09. Joining Tables (SQL Joins)/8. Exercise 1.mp4 113.1 MB
  • 04. Creating Table and Inserting Data into the Table/9. Inserting Data into Table.mp4 113.0 MB
  • 10. Grouping and Aggregating Records/4. Visualizing GROUP BY Operation.mp4 112.3 MB
  • 12. Subqueries/4. Subquery in SELECT Clause.mp4 111.9 MB
  • 08. Table Relationships and Constraints/6. Foreign Key Constraint on Delete.mp4 109.5 MB
  • 08. Table Relationships and Constraints/5. Foreign Keys.mp4 107.8 MB
  • 12. Subqueries/5. Subquery in FROM Clause.mp4 106.7 MB
  • 02. Setting up Local Environment/3. Local Set up - Mac.mp4 106.1 MB
  • 15. Working with Date and Time Data Types/5. Example Truncating Date and Timestamp.mp4 105.0 MB
  • 08. Table Relationships and Constraints/1. Section Introduction.mp4 103.4 MB
  • 09. Joining Tables (SQL Joins)/11. Exercise 3.mp4 97.6 MB
  • 09. Joining Tables (SQL Joins)/4. Inner Join.mp4 96.1 MB
  • 23. Next Steps Roadmap and Career Guidance/1. Data Analyst Data Scientist Roadmap.mp4 95.6 MB
  • 17. Working with JSON Data Type/2. What is JSON.mp4 95.5 MB
  • 13. Case Study 1 Extracting Insights from E-commerce Dataset/8. Exercise 3 Calculate the Average Order Value (AOV).mp4 92.2 MB
  • 18. Window Functions/4. The DENSE_RANK() Window Function.mp4 85.8 MB
  • 15. Working with Date and Time Data Types/3. Time Zone Conversions.mp4 84.5 MB
  • 10. Grouping and Aggregating Records/6. Exercise Using Aggregation with Grouping.mp4 83.8 MB
  • 10. Grouping and Aggregating Records/7. Filtering Groups.mp4 83.5 MB
  • 13. Case Study 1 Extracting Insights from E-commerce Dataset/7. Solution - Exercise 2.mp4 82.7 MB
  • 13. Case Study 1 Extracting Insights from E-commerce Dataset/11. Solution - Exercise 4.mp4 82.3 MB
  • 08. Table Relationships and Constraints/9. Getting Table Schema Information.mp4 81.7 MB
  • 09. Joining Tables (SQL Joins)/12. Exercise 4.mp4 77.6 MB
  • 11. Sorting Records/3. Limiting and Skipping Records.mp4 76.9 MB
  • 18. Window Functions/5. The ROW_NUMBER() Window Function.mp4 74.9 MB
  • 13. Case Study 1 Extracting Insights from E-commerce Dataset/13. Solution - Exercise 5.mp4 73.7 MB
  • 09. Joining Tables (SQL Joins)/6. Right Outer Join.mp4 72.5 MB
  • 20. SQL for Cleaning Data for Analysis and Reporting/5. Handling Outliers.mp4 70.9 MB
  • 09. Joining Tables (SQL Joins)/7. Full Outer Join.mp4 70.6 MB
  • 13. Case Study 1 Extracting Insights from E-commerce Dataset/14. Exercise 6 Show the most recent review for each product.mp4 70.4 MB
  • 10. Grouping and Aggregating Records/3. Why do we group records.mp4 69.3 MB
  • 17. Working with JSON Data Type/7. Constructing JSON Objects.mp4 67.4 MB
  • 16. Working with Array Data Type/9. Exercise Array Aggregation.mp4 64.3 MB
  • 17. Working with JSON Data Type/8. JSON Aggregation.mp4 62.7 MB
  • 20. SQL for Cleaning Data for Analysis and Reporting/8. Consistent Format for Numeric Data.mp4 62.4 MB
  • 09. Joining Tables (SQL Joins)/13. Join with Filter.mp4 60.0 MB
  • 16. Working with Array Data Type/7. Array Functions.mp4 59.6 MB
  • 03. Database Terminologies/4. Creating a Database.mp4 58.6 MB
  • 16. Working with Array Data Type/5. Filtering Records Based on Array Values.mp4 58.2 MB
  • 21. Case Study 2 Time Series Analysis with Retail Sales Dataset/9. Quick Recap of the Key Concepts.mp4 58.1 MB
  • 11. Sorting Records/2. Sorting Records.mp4 55.1 MB
  • 13. Case Study 1 Extracting Insights from E-commerce Dataset/6. Exercise 2 Identify the top selling products.mp4 53.5 MB
  • 02. Setting up Local Environment/4. Local Set up - Windows.mp4 53.1 MB
  • 08. Table Relationships and Constraints/2. One-to-Many and Many-to-One Relationships.mp4 53.0 MB
  • 13. Case Study 1 Extracting Insights from E-commerce Dataset/17. Solution - Exercise 7.mp4 52.4 MB
  • 18. Window Functions/7. LAG() Function - A Practical Use Case.mp4 50.5 MB
  • 14. Type Casting/2. Explicit Type Casting.mp4 50.4 MB
  • 15. Working with Date and Time Data Types/6. Extracting Parts of Date and Timestamp.mp4 50.0 MB
  • 07. Updating and Deleting Records/2. Updating Records in a Table.mp4 49.8 MB
  • 13. Case Study 1 Extracting Insights from E-commerce Dataset/3. Analytics Data Setup.mp4 49.7 MB
  • 09. Joining Tables (SQL Joins)/10. Exercise 2.mp4 49.4 MB
  • 20. SQL for Cleaning Data for Analysis and Reporting/6. Standardizing Values in Categorical Columns.mp4 48.8 MB
  • 02. Setting up Local Environment/5. Getting Familiar with pgAdmin.mp4 48.4 MB
  • 17. Working with JSON Data Type/4. Inserting Data into JSON Columns.mp4 47.4 MB
  • 08. Table Relationships and Constraints/3. One-to-One and Many-to-Many Relationships.mp4 47.2 MB
  • 13. Case Study 1 Extracting Insights from E-commerce Dataset/10. Exercise 4 Calculate the Customer Lifetime Value (CLV).mp4 46.7 MB
  • 06. Filtering Records/2. The WHERE Clause.mp4 46.2 MB
  • 15. Working with Date and Time Data Types/8. Date Math.mp4 45.0 MB
  • 20. SQL for Cleaning Data for Analysis and Reporting/7. Standardizing Text Data.mp4 44.4 MB
  • 15. Working with Date and Time Data Types/4. Truncating Date and Timestamp.mp4 43.9 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 42.9 MB
  • 04. Creating Table and Inserting Data into the Table/4. Character Data Types.mp4 42.5 MB
  • 03. Database Terminologies/3. Multiple databases and schemas.mp4 42.1 MB
  • 13. Case Study 1 Extracting Insights from E-commerce Dataset/1. Quick Recap!.mp4 42.1 MB
  • 06. Filtering Records/6. Using WHERE with pattern matching.mp4 40.9 MB
  • 19. Common Table Expressions (CTEs)/1. Section Introduction.mp4 40.0 MB
  • 13. Case Study 1 Extracting Insights from E-commerce Dataset/19. Solution - Exercise 8.mp4 39.7 MB
  • 07. Updating and Deleting Records/3. Deleting Records from a Table.mp4 38.6 MB
  • 13. Case Study 1 Extracting Insights from E-commerce Dataset/9. Solution - Exercise 3.mp4 38.0 MB
  • 15. Working with Date and Time Data Types/7. Formatting Date and Timestamp.mp4 37.5 MB
  • 04. Creating Table and Inserting Data into the Table/2. Numeric Data Types.mp4 37.3 MB
  • 06. Filtering Records/3. Comparison operators in WHERE Clause.mp4 36.7 MB
  • 16. Working with Array Data Type/4. Inserting Data into Array Columns.mp4 36.4 MB
  • 12. Subqueries/3. Where is a Subquery Used.mp4 36.4 MB
  • 10. Grouping and Aggregating Records/1. Section Introduction.mp4 36.1 MB
  • 15. Working with Date and Time Data Types/2. Current Date and Time.mp4 35.9 MB
  • 16. Working with Array Data Type/6. Array Indexing.mp4 35.2 MB
  • 13. Case Study 1 Extracting Insights from E-commerce Dataset/16. Exercise 7 Identify the top rated products.mp4 35.0 MB
  • 12. Subqueries/2. What is a Subquery.mp4 34.9 MB
  • 17. Working with JSON Data Type/3. Adding Columns of JSON Data Type.mp4 34.5 MB
  • 06. Filtering Records/5. Using WHERE within a specified range.mp4 34.3 MB
  • 16. Working with Array Data Type/2. What is an Array.mp4 34.1 MB
  • 01. Introduction to Data Analytics/1. Data Roles and Responsibilities.mp4 34.0 MB
  • 16. Working with Array Data Type/3. Adding Columns of Array Data Type.mp4 33.9 MB
  • 21. Case Study 2 Time Series Analysis with Retail Sales Dataset/1. Section Introduction.mp4 33.0 MB
  • 04. Creating Table and Inserting Data into the Table/8. Creating a Table.mp4 31.7 MB
  • 14. Type Casting/3. Implicit Type Casting.mp4 31.1 MB
  • 05. Reading Data From Table/4. Using Comments in SQL.mp4 31.0 MB
  • 13. Case Study 1 Extracting Insights from E-commerce Dataset/2. Section Introduction.mp4 30.3 MB
  • 08. Table Relationships and Constraints/7. Foreign Key Constraint on Insert.mp4 29.9 MB
  • 13. Case Study 1 Extracting Insights from E-commerce Dataset/5. Solution - Exercise 1.mp4 29.3 MB
  • 06. Filtering Records/7. Compound WHERE Clause.mp4 29.2 MB
  • 17. Working with JSON Data Type/1. Section Introduction.mp4 29.2 MB
  • 04. Creating Table and Inserting Data into the Table/7. Other Important Data Types.mp4 28.9 MB
  • 16. Working with Array Data Type/1. Section Introduction.mp4 28.1 MB
  • 13. Case Study 1 Extracting Insights from E-commerce Dataset/18. Exercise 8 Calculate discount based on order value.mp4 27.6 MB
  • 13. Case Study 1 Extracting Insights from E-commerce Dataset/4. Exercise 1 Calculate the total revenue.mp4 27.4 MB
  • 09. Joining Tables (SQL Joins)/9. Table and Column Alias.mp4 27.2 MB
  • 05. Reading Data From Table/2. The SELECT statement.mp4 27.2 MB
  • 06. Filtering Records/4. Using WHERE with a List of Values.mp4 27.1 MB
  • 16. Working with Array Data Type/10. Flattening of Arrays.mp4 26.5 MB
  • 04. Creating Table and Inserting Data into the Table/5. Date and Time Data Types.mp4 22.3 MB
  • 09. Joining Tables (SQL Joins)/3. Why do we need Joins.mp4 21.4 MB
  • 07. Updating and Deleting Records/4. Dropping a Table from Database.mp4 20.8 MB
  • 20. SQL for Cleaning Data for Analysis and Reporting/2. Data Setup.mp4 20.7 MB
  • 14. Type Casting/1. Section Introduction.mp4 19.9 MB
  • 03. Database Terminologies/2. Tables.mp4 17.7 MB
  • 04. Creating Table and Inserting Data into the Table/1. Section Introduction.mp4 17.6 MB
  • 03. Database Terminologies/1. Database and Schema.mp4 17.1 MB
  • 15. Working with Date and Time Data Types/1. Section Introduction.mp4 12.5 MB
  • 09. Joining Tables (SQL Joins)/1. Section Introduction.mp4 12.0 MB
  • 18. Window Functions/2. Data Setup.mp4 10.5 MB
  • 12. Subqueries/1. Section Introduction.mp4 8.5 MB
  • 18. Window Functions/1. Section Introduction.mp4 7.8 MB
  • 11. Sorting Records/1. Section Introduction.mp4 7.7 MB
  • 04. Creating Table and Inserting Data into the Table/6. Boolean Data Type.mp4 6.8 MB
  • 06. Filtering Records/1. Section Introduction.mp4 6.0 MB
  • 07. Updating and Deleting Records/1. Section Introduction.mp4 5.8 MB
  • 05. Reading Data From Table/1. Section Introduction.mp4 5.6 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 1.2 MB
  • 09. Joining Tables (SQL Joins)/7. full_join.png 699.5 kB
  • 09. Joining Tables (SQL Joins)/6. right_join.png 656.8 kB
  • 18. Window Functions/8. 2024-11-21_13-44-00-0eb1e38674b8bf9602a76bf0eac228b2.png 641.4 kB
  • 09. Joining Tables (SQL Joins)/5. left_join.png 641.2 kB
  • 09. Joining Tables (SQL Joins)/4. inner_join.png 591.7 kB
  • 10. Grouping and Aggregating Records/9. 2024-11-10_17-59-04-8600b09d5bdaa0bd281190ac1a380b0a.png 355.8 kB
  • 02. Setting up Local Environment/2. server_client.png 352.7 kB
  • 02. Setting up Local Environment/6. 2024-12-02_14-38-07-ea5fafe8a3a58701a11f427500a28607.png 352.7 kB
  • 13. Case Study 1 Extracting Insights from E-commerce Dataset/1. sql_topics.png 289.7 kB
  • 18. Window Functions/1. window_functions.png 282.7 kB
  • 18. Window Functions/8. 2024-11-21_13-44-00-f4657878fbc6ca7ce6d115a864555b14.png 282.7 kB
  • 16. Working with Array Data Type/11. 2024-11-19_12-03-27-ef3be7da1bf82e66c276e569f9e49097.png 280.9 kB
  • 16. Working with Array Data Type/2. array_datatype.png 280.9 kB
  • 20. SQL for Cleaning Data for Analysis and Reporting/1. analysis_process.png 215.7 kB
  • 20. SQL for Cleaning Data for Analysis and Reporting/9. 2024-11-23_19-58-44-059632582b9adcf9ba495eeec822bced.png 215.7 kB
  • 18. Window Functions/7. lag_ex.png 211.7 kB
  • 13. Case Study 1 Extracting Insights from E-commerce Dataset/1. order_exec.png 188.0 kB
  • 06. Filtering Records/8. 2024-11-05_14-37-46-5a167c0f7681a228041f564c25cd2542.png 103.1 kB
  • 06. Filtering Records/9.6 Comparison Operators and Pattern Matching.html 25.5 kB
  • 08. Table Relationships and Constraints/11.8 Table Relationships and Column Constraints.html 23.6 kB
  • 04. Creating Table and Inserting Data into the Table/11.3 Data Types.html 23.5 kB
  • 09. Joining Tables (SQL Joins)/15.9 Joining Tables.html 23.1 kB
  • 11. Sorting Records/5.11 Sorting, Limiting and Skipping Records.html 21.5 kB
  • 07. Updating and Deleting Records/6.7 Update and Delete Operations.html 20.8 kB
  • 05. Reading Data From Table/6.4 String Operators and Functions.html 20.2 kB
  • 10. Grouping and Aggregating Records/10.10 Grouping and Aggregating Records.html 19.7 kB
  • 12. Subqueries/10.12 Subqueries.html 19.0 kB
  • 03. Database Terminologies/5.1 Database Schema.html 17.0 kB
  • 05. Reading Data From Table/7.5 Alias for column name.html 16.6 kB
  • 04. Creating Table and Inserting Data into the Table/3.2 SERIAL Data Type.html 16.5 kB
  • 20. SQL for Cleaning Data for Analysis and Reporting/9. Lecture Notes.html 10.2 kB
  • 08. Table Relationships and Constraints/10. Lecture Notes.html 9.6 kB
  • 22. Some More Interview Questions From Top Companies/2.15 Interview Question (CVS Health).html 8.8 kB
  • 21. Case Study 2 Time Series Analysis with Retail Sales Dataset/10.13 Interview Question (Wayfair).html 8.0 kB
  • 09. Joining Tables (SQL Joins)/16.2 Interview Question (TikTok).html 7.9 kB
  • 19. Common Table Expressions (CTEs)/4.12 Interview Question (LinkedIn).html 7.9 kB
  • 18. Window Functions/10.11 Interview Question (Amazon).html 7.4 kB
  • 22. Some More Interview Questions From Top Companies/4.17 Interview Question (Facebook).html 7.3 kB
  • 15. Working with Date and Time Data Types/10.9 Interview Question (Microsoft).html 7.0 kB
  • 12. Subqueries/12.8 Interview Question (FAANG).html 6.9 kB
  • 06. Filtering Records/10.1 Interview Question (Tesla).html 6.7 kB
  • 11. Sorting Records/7.6 Interview Question (CVS Health) Part 2.html 6.6 kB
  • 22. Some More Interview Questions From Top Companies/3.16 Interview Question (UnitedHealth Group).html 6.6 kB
  • 22. Some More Interview Questions From Top Companies/1.14 Interview Question (JP Morgan).html 6.4 kB
  • 11. Sorting Records/6.5 Interview Question (CVS Health) Part 1.html 6.3 kB
  • 22. Some More Interview Questions From Top Companies/5.18 Interview Question (Amazon).html 6.2 kB
  • 10. Grouping and Aggregating Records/12.4 Interview Question (New York Times).html 6.2 kB
  • 12. Subqueries/11.7 Interview Question (Facebook).html 6.1 kB
  • 17. Working with JSON Data Type/9. Lecture Notes.html 5.8 kB
  • 18. Window Functions/9.10 Interview Question (Uber).html 5.8 kB
  • 15. Working with Date and Time Data Types/9. Lecture Notes.html 5.6 kB
  • 10. Grouping and Aggregating Records/11.3 Interview Question (LinkedIn).html 5.6 kB
  • 13. Case Study 1 Extracting Insights from E-commerce Dataset/3. analytical_dataset.sql 4.7 kB
  • 04. Creating Table and Inserting Data into the Table/10. Lecture Notes.html 4.7 kB
  • 09. Joining Tables (SQL Joins)/14. Lecture Notes.html 4.3 kB
  • 18. Window Functions/8. Lecture Notes.html 3.8 kB
  • 16. Working with Array Data Type/11. Lecture Notes.html 3.5 kB
  • 10. Grouping and Aggregating Records/9. Lecture Notes.html 3.4 kB
  • 12. Subqueries/9. Lecture Notes.html 3.0 kB
  • 09. Joining Tables (SQL Joins)/2. shopeasy_dataset.sql 2.9 kB
  • 21. Case Study 2 Time Series Analysis with Retail Sales Dataset/9. key_concepts.sql 2.9 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 1.8 kB
  • 20. SQL for Cleaning Data for Analysis and Reporting/2. data_setup.sql 1.8 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 1.4 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 1.2 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 1.0 kB
  • 15. Working with Date and Time Data Types/6. date_part.sql 1.0 kB
  • 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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