Big Data comes with all that data transported by the Internet of Things. Big Data has little value unless you can tap into it for the information that you need for that decision you need to make in the next hour or two.
Anodot recently contacted me about a new analytics solution it has developed. For most of us, it is sufficient to know that such solution exists. Others may want to see what it’s up to.
The company just exited stealth mode introducing its real-time anomaly detection solution, which the company maintains will disrupt the static nature of today’s Business Intelligence (BI) with patented machine learning algorithms for big data. Pinpointing performance issues and business opportunities in real time, Anodot enables its customers to increase operational efficiency and maximize revenue generation.
The company also announced it closed a $3 million Series A funding round led by Disruptive Partners, bringing total funding in the company to $4.5 million. The company will use the funding to accelerate its product roadmap and expand its sales activity, focusing on the ad tech, e-commerce, IoT and manufacturing industries in the U.S. and EMEA.
Founded in June 2014, Anodot is the only analytics and anomaly detection solution that is data agnostic and automates the discovery of outliers in all business and operational data. Anodot’s platform isolates issues and correlates them across multiple parameters to surface and alert on incidents in real time.
Data analysis lag problem
“I experienced the data analysis lag problem first hand as CTO for Gett,” said Anodot CEO David Drai. “As a mobile taxi app, SMS text orders were dropped by the carrier, but it could take up to three days to spot critical issues and fix them, costing tens of thousands of dollars per incident. That’s where I got the idea for Anodot—to employ the latest advances in machine learning to detect performance problems automatically and in real time, eliminating the latency.”
Data-centric organizations share a common problem—they collect mountains of data, but deriving business value comes long after the actual event and requires data modeling experts using homegrown custom tools in a static and time-consuming process. The resulting delays in getting business insights can cost companies millions of dollars in lost revenue or production.
“There is a huge opportunity to disrupt the BI market by enabling automated and real-time insights into big data pools of metrics and KPIs,” said Tal Barnoach, Anodot board member and general partner at The Disruptive Fund, a privately held Tel Aviv/New York-based venture fund. “We have been with Anodot from the beginning. The team and the technology are terrific, we are impressed with the progress they have made to date and are excited to be participating in this next stage as they scale upward.”
Anodot is led by a proven team of three co-founders with strong credentials as entrepreneurs and technologists with deep experience in data science and global-scale SaaS infrastructures. CEO David Drai was co-founder and CTO of Cotendo for four years when it was acquired by Akamai for $300 million.
Chief Data Scientist Dr. Ira Cohen held the same position at HP Software where he led research and development in machine learning and data mining techniques. R&D VP Shay Lang has led engineering teams for more than 10 years at leading technology companies. On the board of directors, the team also includes Anthony Bettencourt, president and CEO at Imperva and a board member at Proofpoint, and Ben Lorica, O’Reilly Media’s chief data scientist and a top influencer on Twitter, as a board advisor.
Anodot is already being used in production by dozens of organizations, including Avantis (not the one that is part of Schneider Electric Software) that develops the most advanced desktop tools and monetization platforms in the world and Wix, a leading cloud-based Web development platform with millions of users worldwide.
Important issues missed
Before using Anodot, Wix said vast amounts of metrics and KPIs were measured and analyzed manually by data analysts, yet despite spending a great deal of time, important issues sometimes took days to identify.
“With Anodot we are able to detect changes very early and make decisions that have a direct impact on our business,” said Mark Sonis, monitoring team leader at Wix. “We are able to investigate issues in minutes, not hours, and it does its magic every day with little effort on our side. Anodot has become an essential solution across many of our teams including BI, R&D and DevOps.”
According to Doron Ben-David, CTO, VP R&D, Avantis, “Our vision is to enable publishers to focus on creating content, applications and media, while we provide the revenue mechanism. Fulfilling that promise means our core business revolves around numbers—the impressions, downloads, ad shares and other metrics that feed revenues and bottom lines. Anodot gives us the BI tool to track all of the metrics and KPIs that are essential to our success in real time and alerts us to issues as they happen so we can immediately respond before it impacts our customers.”
The use of solutions like Anodot’s with advanced and predictive analytics, including machine learning, will grow 65 percent faster than those without predictive functionality, according to IDC.
Unique features and advantages of Anodot Anomaly Detection include:
- Operates in real time
- Works with any type of metric or KPI and scales to any big data volume
- Uses proprietary patented machine learning algorithms
- Correlates different metrics to help identify root causes of problems and eliminate alert storms
- Simulation capability optimizes alert planning and reduces false positive alerts
- Eliminates the need for time-intensive manual analysis
- Enables non-specialists to gain the insights they want and delivers fast time-to-value
- Provides clear visualizations that help any user to understand what the data is showing them