First, ensure you have access to your Azure Table Storage account. Log in to your Azure portal, navigate to your storage account, and locate the access keys. You'll need these keys to authenticate your connection to Azure Table Storage. Ensure you have the necessary permissions to read data from the table.

Set up your local or cloud-based environment where you will execute the data transfer scripts. Install the Azure SDK for Python and Boto3 (the AWS SDK for Python) to interact with Azure Table Storage and DynamoDB, respectively. Use a virtual environment to manage dependencies separately.
```bash
pip install azure-cosmos boto3
```

Write a Python script to connect to Azure Table Storage and fetch the data. Use the `TableService` class from the Azure SDK to authenticate and retrieve data. You can use a loop to fetch all entities if they are paginated.
```python
from azure.cosmosdb.table.tableservice import TableService
account_name = 'your_account_name'
account_key = 'your_account_key'
table_name = 'your_table_name'
table_service = TableService(account_name=account_name, account_key=account_key)
entities = table_service.query_entities(table_name)
data = []
for entity in entities:
data.append(entity)
```

Configure access to your AWS account by setting up AWS credentials. You can either configure your credentials using the AWS CLI or by setting environment variables. Ensure you have the appropriate IAM permissions to write data to DynamoDB.
```bash
aws configure
```

Transform the data fetched from Azure Table Storage into a format suitable for DynamoDB. DynamoDB requires data to be in a specific JSON format, and different data types need to be handled properly (e.g., strings, numbers, etc.).
```python
transformed_data = []
for item in data:
transformed_item = {
'PartitionKey': {'S': item['PartitionKey']},
'RowKey': {'S': item['RowKey']},
# Add other attributes here
}
transformed_data.append(transformed_item)
```

Use Boto3 to connect to DynamoDB and write the transformed data. Use the `batch_write_item` method for efficient insertion of multiple items. Handle any exceptions or errors during the write process to ensure data integrity.
```python
import boto3
dynamodb = boto3.client('dynamodb', region_name='your_region_name')
table_name = 'your_dynamodb_table_name'
with dynamodb.batch_writer(table_name) as batch:
for item in transformed_data:
batch.put_item(Item=item)
```

After the data transfer, verify that the data in DynamoDB matches the original data in Azure Table Storage. You can write a script to sample data from both sources and compare them, or manually check a few entries to ensure accuracy.
```python
# Example: Fetch a sample from DynamoDB and compare
response = dynamodb.get_item(
TableName=table_name,
Key={'PartitionKey': {'S': 'sample_partition_key'}, 'RowKey': {'S': 'sample_row_key'}}
)
print(response['Item'])
```
By following these steps, you can efficiently migrate data from Azure Table Storage to DynamoDB without using third-party connectors or integrations.