def METHOD_NAME(
    self,
    query: str = None,
    dataset_name: str = None,
    table_name: str = None,
    date_column_name: str = "date",
    start_date: str = None,
    end_date: str = None,
    credentials_key: str = None,
    vault_name: str = None,
    **kwargs: Dict[str, Any],
) -> None:
    credentials = None
    if credentials_key:
        credentials_str = AzureKeyVaultSecret(
            secret=credentials_key, vault_name=vault_name
        ).METHOD_NAME()
        credentials = json.loads(credentials_str)
    bigquery = BigQuery(credentials_key=credentials_key, credentials=credentials)
    project = bigquery.get_project_id()
    if query is None:
        try:
            table_columns = bigquery.list_columns(
                dataset_name=dataset_name, table_name=table_name
            )
            if date_column_name not in table_columns:
                logger.warning(
                    f"'{date_column_name}' column is not recognized. Downloading all the data from '{table_name}'."
                )
                query = f"SELECT * FROM `{project}.{dataset_name}.{table_name}`"
                df = bigquery.query_to_df(query)
            else:
                if start_date is not None and end_date is not None:
                    query = f"""SELECT * FROM `{project}.{dataset_name}.{table_name}` 
                    where {date_column_name} between PARSE_DATE("%Y-%m-%d", "{start_date}") and PARSE_DATE("%Y-%m-%d", "{end_date}") 
                    order by {date_column_name} desc"""
                else:
                    query = f"""SELECT * FROM `{project}.{dataset_name}.{table_name}` 
                    where {date_column_name} < CURRENT_DATE() 
                    order by {date_column_name} desc"""
                df = bigquery.query_to_df(query)
                logger.info(
                    f"Downloaded the data from the '{table_name}' table into the data frame."
                )
        except DBDataAccessError:
            logger.warning(
                f"Table name '{table_name}' or dataset '{dataset_name}' not recognized. Returning empty data frame."
            )
            df = pd.DataFrame()
        return df
    else:
        try:
            df = bigquery.query_to_df(query)
        except Exception as e:
            logger.warning(
                f"The query is invalid. Please enter a valid query. Returning an empty dataframe."
            )
            df = pd.DataFrame()
        return df