Knowi Blog | Turning data into action
You can think of search-based analytics as a search engine for your company data. Search-based analytics is the ability to ask questions like “what was our net revenue last quarter” or “show me how many people downloaded our app in the last 30 days sorted by week” and get back actionable data and charts.
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.
This article looks at how to use Snowflake monitoring to manage, optimize, and reduce the cost of credit usage.
Use Knowi to connect to Elasticsearch, query and visualize your data, and use search-based analytics to ask more questions of your data.
When people ask, “what is Elasticsearch?”, some may answer that it’s “an index”, “a search engine”, an “analytics database”, “a big data solution”, that “it’s fast and scalable”, or that “it’s kind of like Google”. Depending on your level of familiarity with this technology, these answers may either bring you closer to an ah-ha moment or further confuse you. But the truth is, all of these answers are correct and that’s part of the appeal of Elasticsearch.
In this post, we’ll give a hands-on, end-to-end tutorial on using Knowi to connect to data in MongoDB Atlas and build visualizations from it in minutes, demonstrate how you can blend data on the fly from SQL and NoSQL data sources, and explore its other advanced features like Natural Language Processing (NLP) and Integrated Machine Learning.