Begin by logging into tplcentral's database. This will typically require credentials such as a username and password, which you should have as part of your access permissions. Ensure you have the necessary read permissions to access the data you intend to export.

Determine the specific data tables or datasets you want to export to a CSV file. This might involve understanding the schema, tables, and columns involved. Knowing exactly what data you need will help streamline the export process and ensure you only retrieve necessary information.

Use SQL queries to extract data from tplcentral. Open a query editor or terminal connected to the database and write a SELECT statement to fetch the required data. For example:
```sql
SELECT * FROM your_table_name;
```
Make sure the query is optimized to prevent any performance issues, especially if dealing with large datasets.

Once your query is ready and returns the expected results, use a command or feature provided by the database to export the data to a local file. Most databases support exporting query results directly to a file format, such as CSV. Use a command similar to:
```sql
COPY (SELECT * FROM your_table_name) TO '/path/to/your/localfile.csv' DELIMITER ',' CSV HEADER;
```
Adjust the file path and table name accordingly. Ensure that the path is accessible and writable by your database user.

After exporting, open the CSV file using a text editor or spreadsheet program to verify the accuracy of the data. Check for correct delimiters, headers, and data integrity. Ensure there are no missing values or formatting issues.

If your data contains special characters or requires specific encoding, ensure that the CSV file is saved with the appropriate character set (e.g., UTF-8). Adjust your query or export settings to handle special characters correctly, preventing data corruption.

Once verified, securely store the CSV file in a location with appropriate access controls to protect sensitive data. Consider creating a backup of the file in a different location or using version control if the data is critical or might be subject to further analysis or modification.