Documents

ANALYST REPORT: No more Silos – How DataOps Technologies Overcome Enterprise Data Isolationism

This new report from Blue Hill Research takes a closer look at how enterprises deploy DataOps models to establish the free flow of data within their organization. It includes real-world case studies which demonstrate how organizations in various industries from retail and ecommerce to education are leveraging new technologies to break down silos.

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WHITE PAPER: The Build or Buy Dilemma – How to get the Most from an Anomaly Detection System

Leveraging the vast amount of business data available today to better meet customer needs and detect business incidents presents organizations with the challenge of whether to build their own anomaly detection system or buy one ready-made. Before organizations make this critical decision, it is important to weigh the benefits and challenges of each approach.

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WHITE PAPER: Building a Large Scale Machine Learning-Based Anomaly Detection System, Part 3 – Identifying and Correlating Abnormal Behavior

This 20-page white paper – part three of a three-part series – incorporates diagrams and charts to explain the process of identifying, ranking and correlating abnormal behavior.

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WHITE PAPER: Building a Large Scale Machine Learning-Based Anomaly Detection System, Part 2 – Learning the Normal Behavior of Time Series Data

This 20-page white paper – part two of a three-part series – incorporates diagrams and charts to explain the process of learning the normal behavior of time series data. Topics include: A general framework for learning normal behavior, The importance of modeling seasonality, Can a seasonal pattern be assumed?, Example methods to detect seasonality, Real-time detection at scale requires online adaptive learning algorithms, The impact of the learning rate, Adapting the learning rate, and Other methods for learning normal behavioral patterns.

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WHITE PAPER: Building a Large Scale Machine Learning-Based Anomaly Detection System, Part 1 – Design Principles

This 18-page white paper – part one of a three-part series – includes full color charts and use cases and discusses design principles of creating a machine learning-based anomaly detection system. Topics include: Why companies need anomaly detection, Types of machine learning, What is an anomaly, and Design principles.

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WHITE PAPER: Real-Time Correlation of Business Insights for Fintech

In this White Paper, Jason Bloomberg – a leading industry analyst and expert on agile digital transformation – takes a closer look at how real-time anomaly detection based on machine learning is a game changer for fintech companies.

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WHITE PAPER: Real-Time Anomaly Detection and Analytics for Today’s Digital Business

Jason Bloomberg – a leading industry analyst and globally recognized expert on agile digital transformation – takes a closer look at how real-time anomaly detection is a game changer for digital technology companies.

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REAL-TIME ANOMALY DETECTION & ANALYTICS FOR E-COMMERCE

E-commerce sites are click- and usage-driven, and customer engagement and revenue are intricately tied together. Early detection of business incidents translates into an agile site that can respond to changes quickly for increased traffic, sales and revenue, optimized ad campaigns, and satisfied customers.

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REAL-TIME BUSINESS INSIGHTS FOR MEDIA COMPANIES

Gain valuable insights from all of your data in real time, with Anodot time business incident detection and analytics.

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REAL TIME ANOMALY DETECTION AND INSIGHTS FOR ADTECH

In programmatic advertising, every minute translates into tens of thousands of dollars, and Anodot gives advertising technology companies the crucial insights you need in real time.

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REAL-TIME ANOMALY DETECTION & ANALYTICS FOR FINTECH

As a financial technology company, you deal with a vast number of critical data streams that behave in complex ways, such as transactions, payments, money transfers or loans. Performing with the highest standard of availability and reliability is a crucial asset to securing customer trust.

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Network World: Anodot uses real-time analytics and anomaly detection to provide business insight

Linda Musthaler, Principal Analyst with Essential Solutions Corp. delves into the benefits of Anodot for companies that need real time business insights.

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Identify IOT Issues in Real Time with Anodot

A brief brochure about how to use Anodot to receive immediate alerts when things go wrong in factories, industrial settings and connected cars and buildings.

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Got Data? Get Insights. Fast.

A brief brochure about increasing business control with real time business incident detection, anomaly detection and analytics.

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Videos & Podcasts

VIDEO – The App Trap (Strata San Jose 2017)

39:40

In this session at Strata Data San Jose, Ira Cohen, Anodot’s Chief Data Scientist and co-founder, presents how to use anomaly detection to monitor all areas of your mobile app to fully optimize it.

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VIDEO – Rich Galan of Rubicon Project: The Need for Real-Time Anomaly Detection

11:07

Rich Galan of Rubicon Project presents the need for real-time anomaly detection at Innovation Enterprise CTO Conference.

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VIDEO – Disrupt the static nature of BI with Predictive Anomaly Detection – Anodot Meetup

30:22

Anodot’s Uri Moaz discusses how predictive anomaly detection can identify revenue-impacting business incidents in minutes(!) not days or weeks.

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VIDEO – Anomaly Detection on Google Analytics – Anodot Meetup

18:45

Corey Gilmore, Director of Data and Analytics at PMC, a large publishing company, presents how they identify anomalies in their Google Analytics using Anodot.

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VIDEO: Anomaly Detection in Adtech – Anodot Meetup

15:02

Greg Pendler of Netseer presents how his Adtech company is using Anodot to identify anomalies in real time, to keep their business working efficiently.

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PODCAST: The Analytics of Anomaly Detection with Anodot

Josh Bycer from Game Wisdom sat down with Anodot’s Ira Cohen and Rebecca Herson to discuss how things are changing with the mobile market, and the work Anodot is doing in the field of analytics.

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VIDEO: Analytics for Large Scale Time Series & Event Data (Strata New York 2016)

42:37

In this session from the O’Reilly Conference Strata New York, Ira Cohen, Anodot’s Chief Data Scientist and co-founder, outlines a system that performs real-time machine learning and analytics on streams at massive scale.

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DSC Webinar Series: Accurate Anomaly Detection with Machine Learning

DSC webinar hosted by Bill Vorhies, Data Science Central Editorial Director and featuring Ira Cohen, Anodot Chief Data Scientist discussing fundamental machine learning techniques for anomaly detection, requirements of an anomaly detection system in various use cases, issues and pitfalls to watch out for when implementing anomaly detection, and common use cases and examples.

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VIDEO: Berlin Buzzwords interview with Ira Cohen, Anodot Chief Data Scientist

03:53

Darya Niknamian, Dataconomy Media Content Marketing Manager, sat down with Ira Cohen, Anodot Chief Data Scientist, at Berlin Buzzwords 2016 and talked about his work, data science, robots, smart phones and VR glasses among other things.

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PODCAST: Semi-Supervised, Unsupervised, and Adaptive Algorithms for Large-Scale Time Series

O’Reilly Data’s Ben Lorica interviews Dr. Ira Cohen, Anodot’s co-founder and Chief Data Scientist about the challenges in building an advanced analytics system for intelligent applications at extremely large scale.

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VIDEO: Anodot Real Time Anomaly Detection

(1:29 minutes)

Brief explanation of Anodot’s Technology, demonstrating how even if you are an octopus you can’t access real time business insights using standard business intelligence tools.

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VIDEO: Anomaly Detection 101

(27 minutes)

Anodot’s Uri Maoz explains how real time anomaly detection can save your company millions of dollars, and what you should look for in this type of monitoring system for both your technical and your business metrics. Recorded at the CTO Summit.

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VIDEO: Discovering Real Time Anomalies in Large Scale Time Series Signals

(20:25 minutes)

Dr. Ira Cohen, Anodot’s co-founder and Chief Data Scientist presents at IGTcloud – Big Data, Analytics & Applied Machine Learning – Israeli Innovation Conference.

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VIDEO: Eliminating Insight Latency, One Anomaly at a Time

(9:34 minutes)

Dr. Ira Cohen, Anodot’s co-founder and Chief Data Scientist presents at DATO Conference 2015 & Data Science Summit.

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