Before you can interact with AWS services, ensure your AWS credentials are configured. You can do this by setting environment variables `AWS_ACCESS_KEY_ID` and `AWS_SECRET_ACCESS_KEY`, or by using the AWS CLI to configure them globally with `aws configure`.

Use Boto3 to access the S3 bucket and read the data. If your data is stored in a common format like CSV or JSON, you can use Python's built-in libraries to process the file.
```python
import boto3
import csv

s3 = boto3.client('s3')
bucket_name = 'your-bucket-name'
object_key = 'your-object-key.csv'

response = s3.get_object(Bucket=bucket_name, Key=object_key)
data = response['Body'].read().decode('utf-8').splitlines()
csv_reader = csv.DictReader(data)
```

Depending on your data structure and the schema of your DynamoDB table, you may need to transform the data. This could involve changing data types, renaming fields, or filtering records.
```python
transformed_data = []
for row in csv_reader:
# Example transformation
item = {
'PrimaryKey': row['id'],
'Attribute1': row['attribute1'],
# Add additional transformations as needed
}
transformed_data.append(item)
```

Set up a DynamoDB client using Boto3 to enable interaction with your DynamoDB tables.
```python
dynamodb = boto3.resource('dynamodb')
table = dynamodb.Table('your-table-name')
```

Use the `put_item` method to insert data into the DynamoDB table. If you have a large dataset, consider using batch operations to improve efficiency.
```python
for item in transformed_data:
table.put_item(Item=item)
```

If inserting a large dataset, use `BatchWriteItem` for higher throughput. This method allows you to process up to 25 requests simultaneously.
```python
with table.batch_writer() as batch:
for item in transformed_data:
batch.put_item(Item=item)
```

Once the data transfer is complete, verify that the data in DynamoDB matches your expectations. You can do this by querying the table and checking a few sample items.
```python
response = table.scan()
items = response['Items']
print(items) # Ensure data is as expected
```

By following these steps, you can effectively transfer data from an S3 bucket to a DynamoDB table without relying on third-party connectors or integrations. Make sure to handle exceptions and errors in real implementations to ensure robustness and reliability.