Start your engines. The holiday season has officially begun! With the upcoming shopping frenzy surrounding Black Friday and gift buying, it is one of the most important times of the year to avoid glitches like the ones below.

At the advent of the technological era, developers found themselves wasting hours of valuable resources on manual QA. As software was released, teams manually confirmed that it was bug-free and reliable, all the while testing new features and checking for regression of existing features. Unfortunately, this manual approach was prone to mistakes, created long delays in workflows and was tedious and time-consuming.

Augmented analytics is trending. You’ve read about it, you’ve heard about it, you may even be in the process of acquiring systems running it. But what exactly is it, and how can you recognize it? As the guys building augmented analytics, we’re here to dispel some of the hype. On the highest level, augmented analytics is the machine learning processes geared at making data more accessible and actionable for both data scientists and business users.

The digital era has brought vast cultural transformations – the sharing economy, microtransactions, lightning-fast communication and much more. Much of this has also resulted in considerable innovation in revenue-related areas. Companies from various industries today manage a large number of revenue streams from different revenue models.

If you aren’t frightened enough this Halloween, spend some time reading these tales of glitchy horror! Then, save your company from becoming a ghost story with Anodot’s anomaly detection and keep your platforms running smoothly.