Entity extraction is the process of figuring out which fields a query should target, as opposed to always hitting all fields. For example: how to tell, when the user typed in Apple iPhone, that the intent was to run company:Apple AND product:iPhone?
Many of our users are responsible for monitoring logs to detect sudden changes in volume or to control the budget. To help you with this goal, we’re excited to announce new enhancements to our usage dashboard.
It doesn’t matter what industry you’re in — there’s more data at your fingertips than ever before. And with that data comes an opportunity to make informed decisions that will take your business to new heights. For marketing alone, becoming best-in-class at data analytics can help you generate 20 percent more revenue than your competitors. Those benefits increase exponentially when you bring data-driven decision-making to every aspect of your business.
As Elasticsearch is gradually becoming the standard for textual data indexing (specifically log data) more companies struggle to scale their ELK stack. We decided to pick up the glove and create a series of posts to help you tackle the most common Elasticsearch performance and functional issues. This post will help you in understanding and solving one of the most frustrating Elasticsearch issues – Mapping exceptions.
Elasticsearch, Logstash, and Kibana — the trio better known as Elastic Stack (or ELK, if you prefer a term that is now going out of style), make up a powerful set of tools for searching and analyzing data. Their power derives not just from their technical features, but also the fact that Elastic Stack is an open source platform that anyone can download and set up anywhere.
Elastic Stack Features (formerly X-Pack) is an Elastic Stack extension that bundles security, alerting, monitoring, reporting, and graph capabilities. One could use either all or specific components.
A few weeks ago, BubbleUp came out of Beta. We’ve been getting fantastic user feedback on how BubbleUp helps users speed through the Core Analysis Loop and lets people find things they never could have found before. We’ve also been learning more about how BubbleUp works with Tracing, which unearthed some difficult issues. Today, we’re taking those head on.
A couple of months ago we released the all-new Anodot.com. Following the release, I explored our Google Analytics account to see what had happened post-launch. I have always been ambivalent about Google Analytics. On the one hand, the service has helped shape web analytics as we know it today and is used by nearly every website. Not to mention it’s free and rather easy to consume. On the other hand, GA is never a slam dunk.
