#GlitchHappens. That’s an unavoidable consequence of the scale and speed of ecommerce today, especially when lines of code set and change prices in seconds. Unavoidable, however, doesn’t have to mean catastrophic, especially if a real-time anomaly detection system is deployed. In two real-world glitch incidents, we’ll see the cost of not employing real-time automated anomaly…
Better Ad Value Begins with Better Tools: Why Ad Tech Needs a Real-Time Anomaly Detection Solution An expanding component of today’s online advertising industry is Ad Tech: the use of technology to automate programmatic advertising – the buying and selling of advertisements on the innumerable digital billboards along the information superhighway. When millions of pixels…
Last weekend, British Airways experienced a major IT glitch that left thousands of travelers stranded. While the system was only down for a few minutes in total, no backup kicked in and so the damage reached into all different departments including booking, baggage handling, mobile apps and check-in desks. In the end, all London Heathrow and…
Top 3 reasons why real-time anomaly detection is critical for e-commerce businesses intelligence Real time anomaly detection is critical for e-commerce companies first and foremost due to the fact that it can detect and alert on costly issues in the time series data of business metrics as they’re happening, long before the effects of lost…
Detection is only the first step: what makes automated anomaly detection truly automated? Throughout this series on ‘why anomaly detection is a business essential,’ we have repeatedly mentioned the main drawback of manual anomaly detection: it simply can’t scale to large numbers of metrics. This is why anomaly detection automation is necessary for real-time anomaly…
The hybrid approach: benefit from both multivariate and univariate anomaly detection techniques In our previous post, we explained what time series data is and provided some details as to how the Anodot time series anomaly detection system is able to spot anomalies in time series data. We also discussed the importance of choosing a model…
Searching for actionable signals: a closer look at time series anomaly detection Simple enough to be embedded in text as a sparkline, but able to speak volumes about your business, time series data is the basic input of Anodot’s automated anomaly detection system. This article begins our three-part series in which we take a closer…
I’m a big fan of maturity models. They help teams clearly articulate their vision and define a path forward. You can tie the product roadmap and projects to the model and justify budgets needed to reach the desired maturity level. Gartner offers the following “Analytics Spectrum” that describes how analytics platforms evolve in two main…
In this final installment of our three-part series, let’s recap our previous discussions of anomalies – what they are and why we need to find them. Our starting point was that every business has many metrics which they record and analyze. Each of these business metrics takes the form of a time series of data…
If you’re one of the many consumers using native apps 90% of the time you’re on your smartphone, you know first hand that mobile apps are big business. So big, in fact, that they are expected to generate 188.9 billion U.S. dollars in revenues via app stores and in-app advertising by 2020. There’s an app for just about…
The Business Case for Real Time Anomaly Detection In the first post ‘What is anomaly detection?’ of our three-part series on why anomaly detection is a business essential, we discussed what anomalies are, how they are detected and why detecting them is so vital for data-driven businesses. In this second post, we’ll discuss the reasons…
