First, create an Azure Storage account if you haven't already. Within this account, create a Blob Container to store your data files. Upload the data files you wish to transfer to Kafka into this Blob Container.

Obtain the necessary connection string or Shared Access Signature (SAS) token for your Blob Storage. This will allow your application to access the data securely. Make sure you have the required permissions to read from the Blob Container.

Install Kafka on your local machine or a server. This involves downloading Kafka and setting up the necessary configurations. Start the Kafka server and a Zookeeper instance, which Kafka relies on to manage cluster coordination.

Develop a Python script (or use another language of your choice) that utilizes the Azure SDK to connect to your Blob Storage account using the connection string or SAS token. The script should read the files from the Blob Container and store them locally or in-memory.

Using the Kafka Python client (such as `kafka-python`), extend your script to produce messages to a Kafka topic. Each message should represent a data record or file content from your Blob Storage. Ensure the Kafka brokers' addresses and topic names are correctly configured in your script.

Ensure that the data being sent to Kafka is serialized appropriately. Depending on the nature of your data, you may choose to serialize it in formats like JSON, Avro, or Protobuf. Implement this serialization in your script before sending the data to the Kafka topic.

Finally, run your script and monitor the Kafka topic to verify that the data has been successfully transferred. Use Kafka consumer clients to read from the topic and ensure that the data matches what was in your Azure Blob Storage. Check for any errors and handle retries if necessary.

By following these steps, you can efficiently move data from Azure Blob Storage to Kafka without relying on any third-party connectors or integrations.