Idea behind this application is to implement self-service data intelligence.
- Connect to your datastore.
- Get to know all the possible questions in a natural language that your data can answer.
- Ask the question and get back the answer.
git clone
this repository and go to params-di folder.pip install -r requirements.txt
- Setup flask app environment variable
export FLASK_APP=params-di.py
- Run the server: flask run [--host=]
- Go to http://ip:5000 on web browser and start using application
Question: For last 90d return average for value where product = "bat" ( Index reference: sales )
Answer:
Elasticsearch response:
{"hits": {"hits": [], "total": 90, "max_score": 0.0}, "_shards": {"successful": 5, "failed": 0, "total": 5}, "took": 124, "aggregations": {"string_field_agg": {"numeric": {"value": 140}, "doc_count": 90}}, "timed_out": false}
- Tabify the response for better visualization
- Handling of elasticsearch's error response
- Optimization of the questions generated.