SQL Data Analyst-SQL Query Generation

Example

SELECT * FROM sales WHERE region = 'East' AND sales_date BETWEEN '2023-01-01' AND '2023-01-31';

Scenario

A user needs to retrieve all sales records for the Eastern region for January 2023. SQL Data Analyst generates the precise query to fetch this data.

Example

Understanding table relationships and foreign key constraints from a JSON or SQL schema input.

Scenario

A user provides a database schema. SQL Data Analyst analyzes it to identify how tables are related, which is essential for generating accurate joins in queries.

Example

Using indexes and optimizing joins for better query performance.

Scenario

For a complex query that joins multiple tables, SQL Data Analyst suggests using specific indexes or rewriting the query to reduce execution time.

Example

Generating queries compatible with MySQL, PostgreSQL, and others.

Scenario

A user with a PostgreSQL database needs to write a query. SQL Data Analyst ensures the syntax matches PostgreSQL's requirements.

Example

Creating Python code snippets using Pandas and Matplotlib for query result visualization.

Scenario

After retrieving sales data, a user wants to visualize trends. SQL Data Analyst generates Python code to create graphs from the query results.