First, ensure you have the Google Cloud SDK installed on your local machine. The SDK will provide the command-line tools necessary to interact with Google Cloud services. You can download and install it from the official [Google Cloud SDK page](https://cloud.google.com/sdk/docs/install).

Once the SDK is installed, open your terminal or command prompt and initialize your Google Cloud project by running:
```bash
gcloud init
```
Follow the prompts to select your Google Cloud project, set the default region, and authenticate with your Google account.

In your terminal, create a Pub/Sub topic where the data from BigQuery will be published. Use the following command, replacing `YOUR_TOPIC_NAME` with your desired topic name:
```bash
gcloud pubsub topics create YOUR_TOPIC_NAME
```

You will need to create a Python script that queries your BigQuery dataset and retrieves the data you want to move. Below is a basic example of how to use the BigQuery client library to query data:
```python
from google.cloud import bigquery
def query_bigquery():
client = bigquery.Client()
query = """
SELECT * FROM `your_dataset.your_table`
"""
query_job = client.query(query)
results = query_job.result()
return results
```
Ensure that the Google Cloud SDK is authenticated with your account to allow this script to execute.

Modify your Python script to include the Google Cloud Pub/Sub client library to publish the queried data. Here’s how you can extend the previous script:
```python
from google.cloud import pubsub_v1
def publish_to_pubsub(data):
publisher = pubsub_v1.PublisherClient()
topic_path = publisher.topic_path('your-project-id', 'YOUR_TOPIC_NAME')
for row in data:
message = str(row).encode('utf-8')
future = publisher.publish(topic_path, message)
print(f'Published message ID: {future.result()}')
if __name__ == "__main__":
data = query_bigquery()
publish_to_pubsub(data)
```
Replace `'your-project-id'` with your actual Google Cloud project ID.

Ensure that your Google Cloud environment is authenticated and has the correct permissions to access BigQuery and Pub/Sub. You may need to set environment variables or use a service account key if running the script outside of the Google Cloud environment:
```bash
export GOOGLE_APPLICATION_CREDENTIALS="path/to/your/service-account-file.json"
```
Make sure the service account has the necessary permissions: `BigQuery Data Viewer` and `Pub/Sub Publisher`.

Run your Python script to execute the data transfer process. This will query your BigQuery table and publish each row of data to the specified Pub/Sub topic:
```bash
python your_script.py
```
Confirm that the messages appear in the Pub/Sub topic as expected.
By following these steps, you can successfully move data from BigQuery to Google Pub/Sub using only Google Cloud’s native tools and services, without any third-party connectors or integrations.