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Analytics

AI and Machine Learning in Your Organization

Digital transformation has led to complex environments that continuously generate new data. As a result, organizations are left unsure about how to best use their data to foster growth and edge out the competition. It's not enough to just have mountains of data, it needs to be analyzed and made sense of in a way that best suits the business.

The Importance of Historical Log Data

Centralized log management lets you decide who can access log data without actually having access to the servers. You can also correlate data from different sources, such as the operating system, your applications, and the firewall. Another benefit is that user do not need to log in to hundreds of devices to find out what is happening. You can also use data normalization and enhancement rules to create value for people who might not be familiar with a specific log type.

Metrics At Scale: How to Scale and Manage Millions of Metrics (Part 2)

With businesses collecting millions of metrics, let’s look at how they can efficiently scale and deal with these amounts. As covered in the previous article (A Spike in Sales Is Not Always Good News), analyzing millions of metrics for changes may result in alert storms, notifying users about EVERY change, not just the most significant ones. To bring order to this situation, Anodot groups correlated anomalies together, in a unified alert.

The Complete Guide to the ELK Stack - 2018

With millions of downloads for its various components since first being introduced, the ELK Stack is the world’s most popular log management platform. In contrast, Splunk — the historical leader in the space — self-reports 15,000 customers total. But what exactly is ELK, and why is the software stack seeing such widespread interest and adoption? Let’s take a deeper dive.