Begin by extracting the data you need from Apify. Access your Apify account and navigate to the specific Actor or Task that contains the data. Use Apify"s API to export the data. You can use a HTTP GET request to retrieve the dataset in a format like JSON or CSV. For example, use `https://api.apify.com/v2/datasets/[DATASET_ID]/items?format=json` to pull the data in JSON format.

After extracting the data, save it locally on your machine. You can use a script in a programming language such as Python to send a request to the Apify API and save the response data into a file. For JSON data, you might use Python"s `json` library to write the data to a `.json` file. Make sure to handle any necessary data transformations or cleaning required for your dataset.

Before importing data into Teradata, ensure it is in a compatible format. Teradata can handle various data file types, but CSV is commonly used. If your data is in JSON, convert it to CSV using a script. Validate the data types and ensure that the data structure aligns with the schema in the Teradata database.

Ensure that you have access to the Teradata environment. This involves having the necessary credentials (username and password) and the Teradata tools installed on your machine, such as Teradata SQL Assistant or Teradata Studio.

Prepare a table in Teradata where the data will be loaded. Use SQL to create a table with a schema that matches the structure of your data. For example, you might use a SQL statement like:
```sql
CREATE TABLE my_table (
id INT,
name VARCHAR(255),
value FLOAT
);
```
Modify the column names and data types according to your data.

Use Teradata's native utilities or SQL commands to load the data file into the table. One common method is to use the `BTEQ` utility to execute an `INSERT` statement that reads from your CSV file. Alternatively, `FASTLOAD` can be used for efficient loading of large datasets. Ensure you handle any errors during this process by checking the return codes or logs.

After loading the data, verify that it has been transferred correctly. Run SQL queries to check the number of records and perform spot checks on the data values. Compare these against the original dataset from Apify to ensure completeness and accuracy. This step helps in identifying any discrepancies or issues that occurred during the data transfer process.

By following these steps, you can manually move data from Apify to Teradata without relying on third-party connectors or integrations.