In the third part of the correlation series, we examine how telcos can leverage correlation analysis in their anomaly detection to surface hard-to-detect network incidents and prevent customer churn.

In this article, we’ve put together a list of our top ten favorite podcasts (in no particular order) related to data science, AI and machine learning.

Gong, AppsFlyer and Anodot get candid about managing spend, preferred attribution models, the KPIs and alerts we monitor most, and optimization success stories.

Alicorn Global Ventures has completed an investment of $3 million in Anodot, a global software company recently included in Forbes’ Top 20 Machine Learning Startups to Watch and a leading vendor in the fast-expanding AI analytics space.

Amazon Web Services joins Xandr CTO Ben John and Anodot CEO David Drai to discusses the shift to machine learning-based anomaly detection in business monitoring.

If you are in the market for AIOps technology, these are the 6 key areas to evaluate to reap the full benefits of the platform for your business. Feel free to download our AIOps Request for Proposal (RFP) document to help guide your decision making process. 

Learn how to evaluate anomaly detection solutions: why you need an RFP template, key topics that you should cover and why they’re important. Download an RFP template here.

We continue our series on correlation analysis by examining use cases in eCommerce, especially in optimizing promotions and ad spend.

The first article in a three-part series on correlation analysis, and why pairing it with anomaly detection greatly facilitates root cause analysis, reducing time to detection (TTD) and time to remediation (TTR), as well as alleviating alert fatigue.