Analyze Elasticsearch data in Jupyter.
Load your Elasticsearch data to your data warehouse to run custom SQL queries on your customer data and to generate reports and dashboards using Jupyter. Combine your Elasticsearch data with data from other sources to make it even more valuable.
How to connect Elasticsearch to Jupyter
Simple. By leveraging the Alooma enterprise data pipeline, you can easily integrate, connect, and watch your Elasticsearch data flow into Jupyter.
Integrate
Add Elasticsearch as a data source.
Connect
Map Elasticsearch data to Jupyter.
Watch
See Elasticsearch data flow into Jupyter.
Export your Elasticsearch data along with all of
your other data sources to Jupyter.
Elasticsearch is an open-source search server based on Lucene. It provides a distributed, multitenant-capable full-text search engine with a RESTful web interface and schema-free JSON documents.
The Jupyter Notebook is a web application that allows you to create and share documents that contain live code, equations, visualizations and explanatory text.
Ready to move Elasticsearch data to your warehouse?
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