Before you begin transferring data, familiarize yourself with the tables and the schema in Dremio. Use Dremio’s SQL editor to explore the data, noting down details such as table names, column names, data types, and any constraints. Ensure you understand the relationships and dependencies between tables.

Use Dremio's built-in export functionality to download data. Execute a SQL query to select the desired data, then export it to a CSV or JSON file. This can typically be done through Dremio's web interface by executing a query and using the export options. Make sure to export data from each table you want to transfer to MySQL.

Set up your MySQL database if it is not already prepared. Create a new database and define tables that mirror the structure of your Dremio data. Use the MySQL `CREATE TABLE` command to ensure your tables have the same columns and data types as those in Dremio. Pay special attention to data type compatibility and constraints.

Open the exported CSV or JSON files and ensure they match the structure of your MySQL tables. This may require cleaning the data, such as handling null values or converting data types to match MySQL requirements. Use tools like Python scripts or spreadsheet software for data cleaning and formatting.

Use MySQL’s `LOAD DATA INFILE` command for CSV files or `JSON_TABLE` for JSON files to import data into your tables. For example, if using CSV:
```sql
LOAD DATA INFILE '/path/to/your/file.csv'
INTO TABLE your_table
FIELDS TERMINATED BY ','
ENCLOSED BY '"'
LINES TERMINATED BY '\n'
IGNORE 1 ROWS;
```
Ensure the file path is accessible by MySQL and that the file permissions allow reading.

After loading data, perform integrity checks to ensure the data in MySQL matches the source data from Dremio. Use SQL queries to compare record counts, check for data consistency, and validate key constraints. Debug and resolve any discrepancies found during this verification step.

Once the data is verified, optimize the performance of your MySQL database by creating indexes on frequently queried columns. Use the `CREATE INDEX` command to add indexes and consider other optimizations like partitioning for large datasets. This step ensures that your data is not only transferred but also ready for efficient querying and analysis in MySQL.