To begin, you'll need to create an Asana personal access token. Log into your Asana account, navigate to "My Profile Settings," and then select the "Apps" tab. Create a new personal access token, which will be used to authenticate and access your Asana data via the Asana API. Make sure to store this token securely as it grants access to your Asana data.

You'll need some libraries to make HTTP requests and parse JSON data. If you're using Python, install the `requests` library to facilitate HTTP requests and `elasticsearch` library for interacting with Elasticsearch. You can do this using pip:
```
pip install requests elasticsearch
```

Use the Asana API to fetch the data you need. You can start by fetching tasks, projects, or any other resources you require. Here's a basic example using Python to fetch tasks:
```python
import requests

headers = {
'Authorization': 'Bearer YOUR_ASANA_ACCESS_TOKEN',
}

response = requests.get('https://app.asana.com/api/1.0/tasks', headers=headers)
tasks = response.json().get('data', [])
```

Process and format the data fetched from Asana into a structure that's compatible with Elasticsearch. Elasticsearch typically requires data to be in JSON format. Ensure each record is well-structured and includes necessary fields. For instance, you might convert Asana task objects into JSON documents:
```python
es_documents = []
for task in tasks:
es_doc = {
'task_id': task['id'],
'name': task['name'],
'completed': task['completed'],
'created_at': task['created_at'],
# Add other necessary fields
}
es_documents.append(es_doc)
```

Ensure that you have Elasticsearch running either locally or on a server. You can download Elasticsearch from the official website and follow instructions for setup. Once running, create an index where you will store the Asana data. You can do this using the Elasticsearch API or Kibana Dev Tools:
```json
PUT /asana_data
{
"mappings": {
"properties": {
"task_id": { "type": "keyword" },
"name": { "type": "text" },
"completed": { "type": "boolean" },
"created_at": { "type": "date" }
}
}
}
```

Use the Elasticsearch client to index the transformed data into your Elasticsearch instance. Here's an example using Python:
```python
from elasticsearch import Elasticsearch

es = Elasticsearch([{'host': 'localhost', 'port': 9200}])

for doc in es_documents:
es.index(index='asana_data', body=doc)
```

After loading the data, verify that the data has been correctly transferred and indexed in Elasticsearch. You can do this by querying the index and checking the documents. Use the Elasticsearch API or Kibana to perform a simple search:
```json
GET /asana_data/_search
{
"query": {
"match_all": {}
}
}
```

By following these steps, you'll be able to move data from Asana to Elasticsearch without relying on third-party connectors or integrations.