Begin by exporting the data you need from Pipedrive. Log in to your Pipedrive account, navigate to the data you want to export (such as deals, contacts, or organizations), and use the export feature to download the data in CSV format. Ensure you have the necessary permissions to export data.

Once you have the CSV files, open them in a spreadsheet application like Microsoft Excel or Google Sheets. Review the data to ensure it's complete and accurate. Clean up any inconsistencies, such as missing values or incorrect data types, to avoid issues during the import process.

If you haven't already, install PostgreSQL on your system. Once installed, create a new database where the Pipedrive data will be stored. Use the `createdb` command or a tool like pgAdmin to create a database. For example:
```shell
createdb pipedrive_data
```

Based on the structure of your CSV files, define the schema for the tables in PostgreSQL. Use SQL commands to create tables that match the structure of your exported data. For example, if you have a CSV file for contacts, you might use:
```sql
CREATE TABLE contacts (
id SERIAL PRIMARY KEY,
name VARCHAR(255),
email VARCHAR(255),
phone VARCHAR(50)
);
```

Use the `COPY` command to import your CSV data into the PostgreSQL tables. Ensure the CSV file path and table structure match the SQL table definitions. For example:
```sql
COPY contacts(name, email, phone)
FROM '/path/to/contacts.csv'
DELIMITER ','
CSV HEADER;
```
Make sure the CSV file path is correct and accessible by the PostgreSQL server.

After importing the data, verify that it has been correctly transferred by querying the PostgreSQL tables. Use basic SQL queries to check the data integrity and completeness. For example:
```sql
SELECT FROM contacts LIMIT 10;
```

If you need to perform this data transfer regularly, consider automating the process using a scripting language like Python. Write a script that automates the export, preparation, and import steps using libraries like `pandas` for data manipulation and `psycopg2` for PostgreSQL interaction. Schedule the script using a task scheduler like cron (Linux) or Task Scheduler (Windows).

By following these steps, you can efficiently move data from Pipedrive to a PostgreSQL database without relying on third-party connectors.