First, ensure you have access to your Azure Storage Account. You will need the account name and one of the access keys. Navigate to the Azure portal, go to your storage account, and find these details under the "Access keys" section. This information will be used to authenticate and connect to the Azure Table Storage.

You'll need to install the Azure Storage SDK for Python and DuckDB. Use the following commands in your terminal or command prompt:
```bash
pip install azure-data-tables
pip install duckdb
```
These libraries will enable you to interact with Azure Table Storage and DuckDB through Python.

Use Python to connect to Azure Table Storage and retrieve the data. Here is a basic script to get you started:
```python
from azure.data.tables import TableServiceClient

connection_string = "DefaultEndpointsProtocol=https;AccountName=your_account_name;AccountKey=your_account_key;TableEndpoint=your_table_endpoint;"
table_service = TableServiceClient.from_connection_string(conn_str=connection_string)
table_client = table_service.get_table_client(table_name="your_table_name")

entities = table_client.list_entities()

data = []
for entity in entities:
data.append(entity)
```
Replace placeholders with your actual account and table details. This script will retrieve all entities from the specified table.

Convert the retrieved entities into a format compatible with DuckDB. Typically, this would involve converting entities into a list of dictionaries or a Pandas DataFrame:
```python
import pandas as pd

df = pd.DataFrame(data)
```
Ensure that the data types are consistent and suitable for insertion into DuckDB.

Create a new DuckDB database or connect to an existing one. You can do this using DuckDB's Python API:
```python
import duckdb

conn = duckdb.connect("your_database.duckdb")
```
This establishes a connection to your DuckDB database file.

Use the DuckDB connection to load the data from the Pandas DataFrame:
```python
conn.execute("CREATE TABLE IF NOT EXISTS your_table AS SELECT FROM df")
```
This command creates a new table in DuckDB using the structure and data from the DataFrame. Ensure the table name matches your desired destination table name.

Finally, verify that the data has been successfully transferred by querying the DuckDB table:
```python
result = conn.execute("SELECT FROM your_table").fetchall()
print(result)
```
This step ensures the integrity of your data and allows you to confirm that it has been correctly loaded into DuckDB.

By following these steps, you'll have successfully moved data from Azure Table Storage to DuckDB without relying on third-party connectors or integrations.