Begin by logging into your SurveySparrow account. Navigate to the survey from which you want to export data. Use the 'Export' option to download the survey data in a CSV or JSON format. Ensure that all necessary fields are included in the export.

Once you have the data file, clean and format it to match Elasticsearch's requirements. Ensure that each survey response is structured in a JSON format, with keys corresponding to Elasticsearch field names. Check for any data inconsistencies or missing fields.

If you haven't already, download and install Elasticsearch on your local machine or server. Follow the official Elasticsearch installation guide for your operating system. Ensure that Elasticsearch is running by accessing `http://localhost:9200` in your web browser.

Use the Elasticsearch API to create an index where the survey data will be stored. Open a terminal or command prompt, and use the following command to create an index (replace `survey_index` with your desired index name):
```bash
curl -X PUT "localhost:9200/survey_index" -H 'Content-Type: application/json' -d'
{
"mappings": {
"properties": {
"field1": { "type": "text" },
"field2": { "type": "date" },
...
}
}
}'
```
Define the appropriate mappings for each field to ensure proper data indexing.

Write a script in a programming language like Python to read the prepared JSON file and send the data to Elasticsearch. Use the `requests` library to handle HTTP requests. Here is a basic example in Python:
```python
import json
import requests

# Load your data from the JSON file
with open('survey_data.json', 'r') as file:
data = json.load(file)

# Define the Elasticsearch endpoint
es_endpoint = "http://localhost:9200/survey_index/_doc"

# Iterate over each survey response and send it to Elasticsearch
for response in data:
response = json.dumps(response)
headers = {'Content-Type': 'application/json'}
requests.post(es_endpoint, headers=headers, data=response)
```

After running your script, verify that the data has been uploaded to Elasticsearch. Use the following command to check the number of documents in the index:
```bash
curl -X GET "localhost:9200/survey_index/_count"
```
Confirm that the count matches the number of records you intended to upload.

Now that your data is successfully uploaded to Elasticsearch, use Elasticsearch's powerful query language to search and analyze your survey data. You can perform operations like aggregations, full-text search, and more using the Elasticsearch Query DSL. Access the data using a tool like Kibana for advanced visualization if needed.

By following these steps, you can efficiently transfer data from SurveySparrow to Elasticsearch without relying on any third-party connectors or integrations.