Redwood City, CA, USA
Mar 24, 2021   |  By Bryn Teasdale
It could be argued that consumer broadband networks have historically been poor neighbours of business networks, with CSPs investing more funds in providing better SLAs to their higher paying business customers. But like it did for many of our pre-set ideas, the pandemic turned the tables around for broadband priority. Forced work from home policies, remote learning, and quarantines have effectively turned consumer broadband into business/educational/health broadband services for many.
Mar 23, 2021   |  By Amit Levi
We are often asked what’s the difference between Anodot and Datadog. Since both platforms monitor data at scale, using machine learning to detect anomalies and incidents, the differentiation might be unclear. So we’re using the real estate here to quickly clarify what each platform is built for, and why – despite some overlaps in features – these are two fundamentally different creatures.
Mar 20, 2021   |  By Ira Cohen
Finding relationships between disparate events and patterns can reveal a common thread, an underlying cause of occurrences that, on a surface level, may appear unrelated and unexplainable. The process of discovering the relationships among data metrics is known as correlation analysis. For data scientists and those tasked with monitoring data, correlation analysis is incredibly valuable when used for root cause analysis and reducing time to remediation.
Mar 13, 2021   |  By David Drai
When DevOps teams talk about monitoring a database, the primary motivation is to ensure that the database won’t suffer a performance hiccup. Long queries, timeouts and table scans are among the most popular causes behind lousy customer experience. However, in recent years, more data has been shifted to cloud databases.
Mar 8, 2021   |  By Ira Cohen
The telecom industry is in the midst of a massive shift to new service offerings enabled by 5G and edge computing technologies. With this digital transformation, networks and network services are becoming increasingly complex: RAN, Core and Transport are only a few of the network’s many layers and integrated components. Today’s telecom engineers are expected to handle, manage, optimize, monitor and troubleshoot multi-technology and multi-vendor networks.
Mar 8, 2021   |  By Anodot
An abundance of information can be daunting for any company. If internal teams do not know where the data is, it might hamper their efficiency at the cost of data quality and cleanliness. From a cost-effectiveness viewpoint, organizations are likely to waste excessively by hanging on to redundant data or storing varied data in one location irrespective of their sensitivity level.
Mar 8, 2021   |  By Amir Kupervas
5G is in the process of transforming communications technology, enabling never-before-seen data transfer speeds and high-performance remote computing capabilities.
Mar 3, 2021   |  By Anodot
The idea of uncovering the root cause of a problem has a universal appeal. The systems we are dealing with on a daily basis are complex. When an issue occurs, we naturally opt to resolve the deeper underlying problem rather than settle for treating the symptoms or the downstream effects.
Feb 10, 2021   |  By Anodot
The past twelve months have pushed many communication service providers (CSPs) to the limit. According to financial reports of the last six months, the New Normal brought about by the pandemic has significantly increased network expansion efforts, IoT connections, new broadband customers, and out of bundle voice traffic and mobile data.
Feb 9, 2021   |  By Anodot
The importance of effective data analytics within an organization is widely accepted by business leaders at this point. With use cases for data analysis spanning every department—from IT management, financial planning, marketing analytics, and so on—the right data analytics tools can have a significant impact on a company’s profitability and growth.
Feb 8, 2021   |  By Anodot
Anodot collects AWS real-time usage metrics and AWS CUR files to enable full visibility. Anodot automatically learns each service usage pattern, using patented anomaly detection technology and alert relevant teams to anomalous spikes or drops in real-time. Our patented anomaly detection technology learns the behavior and every service you use - EC2, S3, ELB and the rest, to automatically identify any deviation from the expected usage and cost pattens. Leave alert storms, false positives, and dashboards behind and leverage the power of proactive, autonomous monitoring.
Jan 3, 2021   |  By Anodot
Now there’s an easy way to measure the business impact of every incident. Anodot lets you set a monetary value for each measure you monitor. Once you set the Impact Value, future alerts will show you how much the anomaly has cost you thus far. Anodot is the only monitoring solution built from the ground up to find and fix key business incidents, as they’re happening. As opposed to most monitoring solutions, which focus on machine and system data to track performance, Anodot also monitors the more volatile and less predictable business metrics that directly impact your company’s bottom line.
Dec 8, 2020   |  By Anodot
Time series anomaly detection is a tool that detects unusual behavior, whether it's hurtful or advantageous for the business. In either case, quick outlier detection and outlier analysis can enable you to adjust your course quickly, before you lose customers, revenue, or an opportunity. The first step is knowing what types of outliers you’re up against. Chief Data Scientist Ira Cohen, co-founder of Autonomous Business Monitoring platform Anodot, covers the three main categories of outliers and how you'll see them arise in a business context.
Nov 18, 2020   |  By Anodot
Business metrics are notoriously hard to monitor because of their unique context and volatile nature. Anodot’s Business Monitoring platform uses machine learning to constantly analyze and correlate every business parameter, providing real-time alerts and forecasts in their context. This is machine learning packaged in a turn-key solution – no data science experience needed.
Oct 29, 2020   |  By Anodot
Co-founder and Cheif Data Scientist Dr. Ira Cohen of Anodot will present the challenges in leveraging AI for Autonomous network monitoring. The presentation will review the following topics.
Oct 18, 2020   |  By Anodot
Just 3 easy steps to create an alert on Anodot. Our machine learning-based anomaly detection enables users to simulate alert estimates as you toggle the settings. Choose from multiple business metrics or layer functions on top of your metrics.
Oct 11, 2020   |  By Anodot
What is anomaly detection? Anomaly detection (aka outlier analysis) is a step in data mining that identifies data points, events, and/or observations that deviate from a dataset’s normal behavior. Anomalous data can indicate critical incidents, such as a technical glitch, or potential opportunities, for instance a change in consumer behavior. Machine learning is progressively being used to automate anomaly detection.
Jul 20, 2020   |  By Anodot
Use Anodot to automatically monitor your Amazon Web Services Cost & Usage Reports and catch anomalous changes in your cloud costs.
Jul 15, 2020   |  By Anodot
A 3-minute guide to help you start monitoring your AWS usage on Anodot's machine learning platform. Once it's up and running, Anodot will continuously monitor your AWS usage and deliver real-time alerts when there's an anomalous spike or drop. This powerful capability enables you to act quickly, far before costs get out of hand.
Jun 16, 2020   |  By Anodot
When your partner ecosystem breaks, be the first to know. Anodot monitors and analyzes the third-party tools and systems that support and enable the business, surfacing mission-critical issues immediately.
May 24, 2019   |  By Anodot
This introduction to next-generation analytics includes a step-by-step comparison between legacy BI and Autonomous Analytics, from data integration to anomaly detection and forecasting.
Mar 1, 2019   |  By Anodot
Learn how different industries are using Machine Learning Powered Analytics.
Mar 1, 2019   |  By Anodot
Learn now anomaly detection can remedy urgent problems faster and capture opportunities sooner.
Feb 1, 2019   |  By Anodot
Immediately address data quality problems and save weeks of dealing with inaccurately reported data.
Feb 1, 2019   |  By Anodot
Learn how leading adtechs like Rubicon Project, Uprise, and NetSeer are leveraging the power of machine learning - discovering outliers in time series data and turning them into valuable business insights.
Jan 1, 2019   |  By Anodot
This white paper presents unique insights into the costs, benefits, and complexities associated with anomaly detection systems, including whether it makes more sense for your company to build or to buy, and which will give the best and fastest return on investment.
Dec 1, 2018   |  By Anodot
An introduction to design principles of creating a machine learning based anomaly detection system.

Anodot applies AI to deliver autonomous analytics in real-time, across all data types, at enterprise scale. Unlike the manual limitations of traditional Business Intelligence, we provide analysts mastery over their business with a self-service AI platform that runs continuously to eliminate blind spots, alert incidents, and investigate root causes.

Autonomous Analytics uses machine learning to understand behavioral patterns within time series data, to identify anomalies and to continuously forecast future values. Our alerts operate in real time and offer you context - correlating each incident to similar anomalies, relevant factors and the potential root cause. Detect and diagnose high-impact problems faster than is humanly possible.

Why Autonomous Analytics?

  • Track Every Business Parameter: Anodot uses its patented technology to learn the normal behavior of all your business metrics and constantly monitor their every move. All without configuring a thing.
  • See The Anomalies That Matter: Not all anomalies are created equal. Anodot scores every business abnormality by degree of deviation so you can prioritize and act based on what’s most important to you.
  • Models Automatically Trained For Accuracy: Our solution uses deep learning to automatically optimize forecasts. It selects a model that’s uniquely suited to your metrics from a library of predictive analytics algorithms. Data feedback is used to train your model for the highest possible accuracy.
  • Continuous Forecasting For Operational Agility: Autonomous Forecast is always running. It works on data streams in real time to provide forecasts in the moment. With these capabilities, businesses can anticipate changing conditions and optimize their operations in advance, to improve customer satisfaction and seize opportunities.

The only alerts you need. Just when you need them.