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Anodot

3 Reasons Why Machine Learning Anomaly Detection is Critical for eCommerce

Do you still find yourself visually monitoring dashboards for anomalies? That leaves catching revenue-related issues to chance. It’s become humanly impossible to catch incidents on streaming data. This is why many eCommerce and data-driven companies have adopted automated anomaly detection.

This is the Single Most Important Business KPI You Probably Aren't Even Monitoring

Having spoken with many companies, I’ve learned that while they all monitor their application performance, infrastructure, product usage, conversion rates and a variety of other user experience parameters, very few monitor the actual transactions from their payment provider.

Business Monitoring: If You Can't Measure It, You Can't Improve It

“If you can’t measure it, you can’t improve it” …this quote by Peter Drucker and the philosophy behind it is a key driving force behind modern management and the introduction of BI solutions to support the scaling and increased complexity of businesses. Analytics tools were developed to enable metric measurement and business monitoring across large scale, complex systems and to enable continuous improvements of business performance.

Performance Monitoring: Are All Ecommerce Metrics Created Equal?

Number of sessions, total sales, number of transactions, competitor pricing, clicks by search query, cart abandonment rate, total cart value…the analytics tools commonly used by eCommerce companies for performance monitoring can’t include every metric, and even if they did the analysts using them wouldn’t be able to keep up with the amounts of changing data.

How Businesses are Using Machine Learning Anomaly Detection to Scale Partner and Affiliate Tracking

Today’s business needs make it virtually impossible to function without relying on an extensive network of partners and third-party providers. An IBM study found that 70 percent of businesses were looking to increase their external partnerships.

The Key Principles of a Successful Time Series Forecasting System for Business

An emerging field of data science uses time series metrics to develop an educated estimate of future developments in business such as revenue, sales, and demand for resources and product deliverables. A forecast is based on historical data of a given metric plus other relevant factors. Accurate forecasts are an important aspect of corporate planning.

The Top 10 Anomalies of the Last Decade

As a company known for our anomaly detection, we know a thing or two about spotting irregularities. So as we reached the end of 2019, we couldn’t help but think back on the 2010s and the anomalies that shook the world. Once we got to listing them, it really became tough to pick just 10. Ultimately, after much debate, we ranked them based on their impact, newsworthiness and how utterly unexpected they were.

The Missing Functionalities of Service Mesh Technologies - Native Anomaly Detection and Incident Correlation

Rapid software release is the new norm – and that has pushed many companies to ditch their monolithic software development approach in favor of SOA. More companies are embracing microservices – an SOA-style approach for developing and deploying business logic as small, independently deployed services – for a number of reasons: it reduces risk, is faster to deploy and it easily scales.