List of 50 real-world SQL tasks to perform in a database application:

Data Manipulation

1. Insert New Records: Add new user or product data to relevant tables.
2. Update Existing Records: Modify user details such as email or address.
3. Delete Records: Remove outdated or incorrect data entries.
4. Bulk Insert: Insert a large dataset in one query.
5. Batch Update: Apply updates to a batch of rows based on a condition.
6. Merge Records: Combine two data sources into one table, updating existing and inserting new data.
7. Upsert (Insert or Update): Add new data if it doesn’t exist, or update if it does.

Data Retrieval

8. Basic SELECT Queries: Retrieve customer order details.
9. JOIN Queries: Combine data from orders and customers tables.
10. Aggregate Functions: Calculate total sales revenue or average purchase price.
11. GROUP BY: Group orders by product category and calculate total sales per category.
12. HAVING Clause: Filter groups with total sales above a certain amount.
13. Subqueries: Retrieve the most recent order for each customer.
14. Window Functions: Rank products based on sales.
15. Common Table Expressions (CTEs): Create temporary result sets for complex queries.
16. Self-Joins: Compare records in a table to find duplicate entries.
17. Recursive CTEs: Handle hierarchical data such as organizational charts.

Data Analysis

18. Pivot Table Queries: Create a pivot table to analyze sales per region.
19. Trend Analysis: Retrieve data to show monthly growth in customer sign-ups.
20. Date Functions: Extract year or month from a date for reports.
21. Advanced Aggregations: Use COUNT, SUM, MIN, MAX, and AVG in complex queries.
22. CASE Statements: Add conditional logic to queries.
23. Percentile Calculations: Use PERCENTILE_CONT to find specific data percentiles.

Data Integrity and Validation

24. Foreign Key Constraints: Ensure referential integrity between orders and customers.
25. Check Constraints: Validate that data values meet specific conditions (e.g., age > 18).
26. Unique Constraints: Ensure no duplicate email addresses in a users table.
27. NULL Handling: Manage queries with NULL values effectively.
28. Data Consistency Checks: Write queries to find inconsistencies, such as missing data in related tables.

Performance Tuning

29. Index Creation: Optimize query performance by creating indexes.
30. Query Optimization: Analyze and rewrite inefficient queries using EXPLAIN.
31. Partition Tables: Split a large table into smaller, more manageable pieces.
32. Analyze Query Execution Plans: Understand query costs and improve performance.
33. Use of Temporary Tables: Speed up complex operations by storing intermediate results.

Security and Access Control

34. Grant and Revoke Permissions: Control user access to tables and views.
35. Create Views: Provide restricted data access through views.
36. Use Role-Based Access Control: Implement roles and grant permissions at the role level.
37. Audit Trail: Track changes with a trigger that logs operations in an audit table.

Stored Procedures and Functions

38. Create Stored Procedures: Automate complex tasks with parameterized procedures.
39. Create User-Defined Functions (UDFs): Simplify complex calculations within queries.
40. Trigger Creation: Automatically perform actions like updating a log table when a record changes.

Advanced Features

41. Full-Text Search: Implement searching within text columns for large data sets.
42. JSON Parsing: Extract and manipulate JSON data stored in columns.
43. XML Parsing: Work with XML data within SQL queries.
44. Dynamic SQL: Create and execute SQL dynamically for flexible querying.

Data Backup and Recovery

45. Backup Databases: Create full and incremental backups for data safety.
46. Restore Databases: Practice restoring from backups to ensure disaster recovery procedures.

Data Migration and Transformation

47. ETL Operations: Extract, transform, and load data from external sources.
48. Data Import/Export: Move data in and out using tools or BULK INSERT.
49. Data Cleaning: Identify and correct errors or inconsistencies in datasets.

Monitoring and Maintenance

50. Database Health Check: Monitor table sizes, index usage, and query performance metrics.

These tasks cover a broad range of operations you'll encounter in real-world SQL database management and application development.