Joining Couchbase and SQL data and doing multi-datasource analytics – Tutorial
In this blog, we show how to create visualizations from the dataset, blend data between Couchbase and SQL database, and use search-based analytics.
In this blog, we show how to create visualizations from the dataset, blend data between Couchbase and SQL database, and use search-based analytics.
Natural language processing (NLP) and self-service analytics have been growing needs for businesses as of late. The ability for business users to reliably ask ad-hoc questions against business data using natural language (similar to a google search) could cut down days’ worth of time going back and forth between analysts, data engineers, and data leads …
A Quick Guide on Natural Language Processing and Self-Service Analytics Read More »
Today’s data is massive and disorganized. To evaluate modern data, you need a BI Tool solution that can interact with any data- structured or unstructured without the fuss, or additional cost of moving or transforming it. This is where Knowi saves the day!
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 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.