Knowi provides native analytics capability into ElasticSearch that goes beyond what Kibana offers. With Knowi, you can explore add-on benefits like blending across multiple indexes, joining across the same or disparate SQL or NoSQL databases, natural language capabilities for self-service analytics, machine-learning anomaly detection, and more.
Knowi’s visualization tools are not only useful for internal reporting, but are also capable of presenting dashboards and widgets to external sources. This can be done through a variety of sharing options but one of the most powerful methods is through embedding. In this blog we will explore the benefits of this feature, the various types of embeds, and a simple 8 step tutorial on how to create a basic embedded widget.
In this tutorial we show how to quickly create visualizations from the dataset, blend data on the fly between Couchbase and a MySQL database, and use search-based analytics to ask questions and gain insights from the data instantly
In this post, we go through the steps of configuring your Knowi Slack integration, getting hands-on with Knowi’s search-based analytics by asking your data questions via Slack, and providing sample questions you can try for yourself.
