Are you over 18 and want to see adult content?
More Annotations
A complete backup of accountingcpd.net
Are you over 18 and want to see adult content?
A complete backup of boatsonline.com.au
Are you over 18 and want to see adult content?
A complete backup of biggayicecream.com
Are you over 18 and want to see adult content?
A complete backup of oemoffhighway.com
Are you over 18 and want to see adult content?
A complete backup of bordadopap.blogspot.com
Are you over 18 and want to see adult content?
Favourite Annotations
A complete backup of deaucongtaskeva.ga
Are you over 18 and want to see adult content?
A complete backup of cnnphilippines.com
Are you over 18 and want to see adult content?
A complete backup of grillsportverein.de
Are you over 18 and want to see adult content?
A complete backup of tenderlovemaking.com
Are you over 18 and want to see adult content?
Text
ABOUT US | ANODOT
Anodot is an industry leader in Business Monitoring, an AI-driven approach that empowers businesses to safeguard their revenues and costs, digital partners, and audience journey, experience and engagement. By leveraging AI to constantly monitor and correlate business performance, Anodot identifies revenue-critical issues,providing real-time
OSS TELECOM NETWORK MONITORING Monitor network performance in context with AI. Anodot uses a patented ML approach to monitor 100% of your data, learn every metrics’ behavior, and provide spot-on alerts critical failures. Anodot helps telcos to optimize service levels and maximize profitability by ensuring customer loyalty and maintaining overall network performance. INTRODUCING MLWATCHER MLWatcher collects and monitors metrics from machine learning models in production. This open source Python agent is free to use, simply connect to your BI service to visualize the results. To detect anomalies in these metrics, either set rule-based alerting, or sync to an ML anomaly detection solution, such as Anodot, to execute at scale. WHAT IS TIME SERIES DATABASE? A time series database consists of state change information that is indexed by time. It usually consists of a subject, the point in time and the measurements. When writing time series data, high throughput is critical for the database requiring it to be continuous and concurrent. This is important because writes make up roughly 95% ofdatabase
THE COSTS OF POOR DATA QUALITY Erroneous decisions made from bad data are not only inconvenient but also extremely costly. According to Gartner research, “the average financial impact of poor data quality on organizations is $9.7 million per year.”. IBM also discovered that in the US alone, businesses lose $3.1 trillion annually due to WHAT IS AI/ML AND ARE YOU USING IT RIGHT? AI/ML – Are We Using It in the Right Context? by Ira Cohen. There used to be a distinct, technical separation between terms such as AI and machine learning (ML) – but only while these technologies remained largely theoretical. As soon as they became practical in the real world, and then commodifiable into products, the marketersstepped in.
WHAT IS INCIDENT MANAGEMENT Incident management is the process of detecting and resolving unexpected events or performance issues before they negatively impact the end-user. Organizations must have a general framework that empowers teams to detect, respond and recover from each incident. Similarly, once the service is performing at its normal level, eachincident
HOW TO REDUCE FALSE POSITIVES USING MACHINE LEARNING PLATFORM? A drop this small is not really an actionable anomaly, and the ensuing alert would likely be deemed a false positive. This is why you’ll also want to set a minimum absolute delta, to filter out the anomalies where the drop, in absolute terms, shouldn’t trigger any alert (e.g., a drop of one – from 10 to nine). ULTIMATE GUIDE TO BUILDING A MACHINE LEARNING ANOMALY The Definitive Guide For Building An Anomaly Detection System. An introduction to design principles of creating a machine learning based anomaly detection system. ANODOT | ANOMALY DETECTION FOR BUSINESS MONITORINGPRODUCTSOLUTIONSCOMPANYRESOURCESAUTONOMOUS FORECASTINTEGRATIONS Fastest incident detection and correlation. Detect anomalies across the business 15X faster. Cut incident-related costs by 70%. Anodot’s patented inference engine lets you know what is happening, where and why as soon as possible, for lightning-fast resolution. Learn More.ABOUT US | ANODOT
Anodot is an industry leader in Business Monitoring, an AI-driven approach that empowers businesses to safeguard their revenues and costs, digital partners, and audience journey, experience and engagement. By leveraging AI to constantly monitor and correlate business performance, Anodot identifies revenue-critical issues,providing real-time
OSS TELECOM NETWORK MONITORING Monitor network performance in context with AI. Anodot uses a patented ML approach to monitor 100% of your data, learn every metrics’ behavior, and provide spot-on alerts critical failures. Anodot helps telcos to optimize service levels and maximize profitability by ensuring customer loyalty and maintaining overall network performance. INTRODUCING MLWATCHER MLWatcher collects and monitors metrics from machine learning models in production. This open source Python agent is free to use, simply connect to your BI service to visualize the results. To detect anomalies in these metrics, either set rule-based alerting, or sync to an ML anomaly detection solution, such as Anodot, to execute at scale. WHAT IS TIME SERIES DATABASE? A time series database consists of state change information that is indexed by time. It usually consists of a subject, the point in time and the measurements. When writing time series data, high throughput is critical for the database requiring it to be continuous and concurrent. This is important because writes make up roughly 95% ofdatabase
THE COSTS OF POOR DATA QUALITY Erroneous decisions made from bad data are not only inconvenient but also extremely costly. According to Gartner research, “the average financial impact of poor data quality on organizations is $9.7 million per year.”. IBM also discovered that in the US alone, businesses lose $3.1 trillion annually due to WHAT IS AI/ML AND ARE YOU USING IT RIGHT? AI/ML – Are We Using It in the Right Context? by Ira Cohen. There used to be a distinct, technical separation between terms such as AI and machine learning (ML) – but only while these technologies remained largely theoretical. As soon as they became practical in the real world, and then commodifiable into products, the marketersstepped in.
WHAT IS INCIDENT MANAGEMENT Incident management is the process of detecting and resolving unexpected events or performance issues before they negatively impact the end-user. Organizations must have a general framework that empowers teams to detect, respond and recover from each incident. Similarly, once the service is performing at its normal level, eachincident
HOW TO REDUCE FALSE POSITIVES USING MACHINE LEARNING PLATFORM? A drop this small is not really an actionable anomaly, and the ensuing alert would likely be deemed a false positive. This is why you’ll also want to set a minimum absolute delta, to filter out the anomalies where the drop, in absolute terms, shouldn’t trigger any alert (e.g., a drop of one – from 10 to nine). ULTIMATE GUIDE TO BUILDING A MACHINE LEARNING ANOMALY The Definitive Guide For Building An Anomaly Detection System. An introduction to design principles of creating a machine learning based anomaly detection system. ANODOT'S DEEP 360 MONITORING™ TECHNOLOGY No more “dark data". Deep 360 monitoring™ technology leverages AI to both learn the behavior of every single metric in HD quality and map the network of correlations between the metrics in the data. Deep 360 then mines the stream of incoming data to rapidly identify and score anomalies. Backed by four patents, Deep 360 ensures fast and WHAT IS ANOMALY DETECTION? 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 consumerbehavior.
INTRODUCTION TO TIME SERIES METRICS Source: Machine Learning Mastery. Time Series Metrics for Time Series Databases. One common application of time series metrics is for monitoring systems and time series databases (discussed further below). For example, Prometheus is an open-source time series database which offers four core metric types including: Running counter: this is a cumulative metric that represents a single CONSUMER BROADBAND TAKES CENTER STAGE Autonomous monitoring solutions help consumer broadband operators maintain network availability, prevent and mitigate outages and service degradation, and improve the customer experience. SMART AXIATA USES ANODOT TO ENSURE SEAMLESS SERVICE Smart Axiata was for years unable to monitor its tens of thousands of KPIs. Troubleshooting often took hours or even days. In this video, CTO Andrey Kuzin and Senior Data Analyst Ming Jin Siew share how Anodot has helped them improve their monitoring capabilities ENSURE DATA QUALITY WITH AI ANALYTICS Since at the end of the day everything is data, a smarter way to approach data quality problems is through AI analytics, leveraging anomaly detection. Anomaly detection flags “bad” data, identifying suspicious anomalies, that can impact data quality. By tracking and evaluating data, anomaly detection gives critical insights into data IDENTIFYING OUTLIERS IN TIME SERIES DATA How to Calculate and Determine Outliers in Time Series Data: Using Meta-Algorithm is the Key. What an automated system for identifying outliers does for each time series: Classifies the metric and selects a model based on that classification: Is it a “smooth time series” (stationary) or is the distribution multimodal, sparse, discrete, etc. ULTIMATE GUIDE TO BUILDING A MACHINE LEARNING ANOMALY The Definitive Guide For Building An Anomaly Detection System. An introduction to design principles of creating a machine learning based anomaly detection system. SHORTCOMINGS OF TRADITIONAL BI TOOLS 5 Critical Shortcomings of Traditional BI Tools. Business Intelligence (BI) tools have taken the business world by storm. According to new research, companies that adopt advanced visualization, dashboards, and reporting tools are proven to experience a 26 percent increase in sales. However, many companies aren’t bringing in those dashboards THE SUPER BOWL SHOWS HOW BIG DATA IS CHANGING THE GAME The Super Bowl is an exciting game that tens of millions of people around the world will enjoy, and big data is changing the game. Whether it be in terms of trying to predict the most likely winner of the game or how advertising is handled. AI-powered analytics can ensure that advertising platforms, retail customers’ sites andonline
ANODOT | ANOMALY DETECTION FOR BUSINESS MONITORINGPRODUCTSOLUTIONSCOMPANYRESOURCESAUTONOMOUS FORECASTINTEGRATIONS Fastest incident detection and correlation. Detect anomalies across the business 15X faster. Cut incident-related costs by 70%. Anodot’s patented inference engine lets you know what is happening, where and why as soon as possible, for lightning-fast resolution. Learn More. OSS TELECOM NETWORK MONITORING Monitor network performance in context with AI. Anodot uses a patented ML approach to monitor 100% of your data, learn every metrics’ behavior, and provide spot-on alerts critical failures. Anodot helps telcos to optimize service levels and maximize profitability by ensuring customer loyalty and maintaining overall network performance. INTRODUCTION TO TIME SERIES METRICS Source: Machine Learning Mastery. Time Series Metrics for Time Series Databases. One common application of time series metrics is for monitoring systems and time series databases (discussed further below). For example, Prometheus is an open-source time series database which offers four core metric types including: Running counter: this is a cumulative metric that represents a single WHAT IS TIME SERIES DATABASE? A time series database consists of state change information that is indexed by time. It usually consists of a subject, the point in time and the measurements. When writing time series data, high throughput is critical for the database requiring it to be continuous and concurrent. This is important because writes make up roughly 95% ofdatabase
THE COSTS OF POOR DATA QUALITY Erroneous decisions made from bad data are not only inconvenient but also extremely costly. According to Gartner research, “the average financial impact of poor data quality on organizations is $9.7 million per year.”. IBM also discovered that in the US alone, businesses lose $3.1 trillion annually due to ENSURE DATA QUALITY WITH AI ANALYTICS Since at the end of the day everything is data, a smarter way to approach data quality problems is through AI analytics, leveraging anomaly detection. Anomaly detection flags “bad” data, identifying suspicious anomalies, that can impact data quality. By tracking and evaluating data, anomaly detection gives critical insights into data 5G KUBERNETES IS THE NEXT STEP FOR TELCOS 5G networks rely on Kubernetes and cloud native computing, but the transition depends on the confidence telcos can build towards these new technologies by creating the monitoring environment that provides the transparency needed to seamlessly identify and mitigate issues assoon as possible.
INTRODUCING MLWATCHER MLWatcher collects and monitors metrics from machine learning models in production. This open source Python agent is free to use, simply connect to your BI service to visualize the results. To detect anomalies in these metrics, either set rule-based alerting, or sync to an ML anomaly detection solution, such as Anodot, to execute at scale. THE FUTURE OF NETWORK MONITORING As Ira Cohen explains, the short answer is yes. The challenges in network monitoring that T-Mobile and other telcos face are well suited for machine learning. “The biggest reason is the notion of scale,” Cohen said. “With tens of thousands of devices each outputting sensor data, as well as monitoring other types of data such asservices
OUTLIER DETECTION DRAMATICALLY IMPACTS BUSINESS Whether they indicate a substantial business problem or an opportunity for performance and revenue optimization, detecting outliers is mission critical for companies of all sizes. In scouring time series data, knowing how to detect outliers is an important task that cannot be overlooked. Looking for unusual data points by manually examining ANODOT | ANOMALY DETECTION FOR BUSINESS MONITORINGPRODUCTSOLUTIONSCOMPANYRESOURCESAUTONOMOUS FORECASTINTEGRATIONS Fastest incident detection and correlation. Detect anomalies across the business 15X faster. Cut incident-related costs by 70%. Anodot’s patented inference engine lets you know what is happening, where and why as soon as possible, for lightning-fast resolution. Learn More. OSS TELECOM NETWORK MONITORING Monitor network performance in context with AI. Anodot uses a patented ML approach to monitor 100% of your data, learn every metrics’ behavior, and provide spot-on alerts critical failures. Anodot helps telcos to optimize service levels and maximize profitability by ensuring customer loyalty and maintaining overall network performance. INTRODUCTION TO TIME SERIES METRICS Source: Machine Learning Mastery. Time Series Metrics for Time Series Databases. One common application of time series metrics is for monitoring systems and time series databases (discussed further below). For example, Prometheus is an open-source time series database which offers four core metric types including: Running counter: this is a cumulative metric that represents a single WHAT IS TIME SERIES DATABASE? A time series database consists of state change information that is indexed by time. It usually consists of a subject, the point in time and the measurements. When writing time series data, high throughput is critical for the database requiring it to be continuous and concurrent. This is important because writes make up roughly 95% ofdatabase
THE COSTS OF POOR DATA QUALITY Erroneous decisions made from bad data are not only inconvenient but also extremely costly. According to Gartner research, “the average financial impact of poor data quality on organizations is $9.7 million per year.”. IBM also discovered that in the US alone, businesses lose $3.1 trillion annually due to ENSURE DATA QUALITY WITH AI ANALYTICS Since at the end of the day everything is data, a smarter way to approach data quality problems is through AI analytics, leveraging anomaly detection. Anomaly detection flags “bad” data, identifying suspicious anomalies, that can impact data quality. By tracking and evaluating data, anomaly detection gives critical insights into data 5G KUBERNETES IS THE NEXT STEP FOR TELCOS 5G networks rely on Kubernetes and cloud native computing, but the transition depends on the confidence telcos can build towards these new technologies by creating the monitoring environment that provides the transparency needed to seamlessly identify and mitigate issues assoon as possible.
INTRODUCING MLWATCHER MLWatcher collects and monitors metrics from machine learning models in production. This open source Python agent is free to use, simply connect to your BI service to visualize the results. To detect anomalies in these metrics, either set rule-based alerting, or sync to an ML anomaly detection solution, such as Anodot, to execute at scale. THE FUTURE OF NETWORK MONITORING As Ira Cohen explains, the short answer is yes. The challenges in network monitoring that T-Mobile and other telcos face are well suited for machine learning. “The biggest reason is the notion of scale,” Cohen said. “With tens of thousands of devices each outputting sensor data, as well as monitoring other types of data such asservices
OUTLIER DETECTION DRAMATICALLY IMPACTS BUSINESS Whether they indicate a substantial business problem or an opportunity for performance and revenue optimization, detecting outliers is mission critical for companies of all sizes. In scouring time series data, knowing how to detect outliers is an important task that cannot be overlooked. Looking for unusual data points by manually examiningABOUT US | ANODOT
Anodot is an industry leader in Business Monitoring, an AI-driven approach that empowers businesses to safeguard their revenues and costs, digital partners, and audience journey, experience and engagement. By leveraging AI to constantly monitor and correlate business performance, Anodot identifies revenue-critical issues,providing real-time
REAL-TIME TRADING PLATFORM MONITORING Monitor 100% of your trading data in real-time with Anodot. Gain granular visibility into your positions and improve your cash management, order execution, clearing and settlement and riskdecision-making.
REAL-TIME PAYMENT MONITORING SYSTEM The company’s revenue stream is a top KPI, and must be monitored constantly. Companies rely on endpoint APIs to execute payments and must ensure the reliability and consistency of payments across multiple payment entities, networks, geographies and devices. ZERO TOUCH NETWORK MONITORING CSPs use Anodot as the “Brain” on top of their network to help build resilience. Anodot’s platform uses self-learning at scale to constantly monitor and correlate network and service anomalies across the entire telco stack, providing actionable alerts in their context, improving Time to Detect and Time to Resolve incidents by 30% -50%. THE PERFECT CUSTOMER EXPERIENCE MONITORING Many companies also pair these with user experience analytics tools such as Fullstory, Hotjar and Pingdom, to get a fuller understanding. A few of the most common customer experience metrics that companies track include: Net promoter score (NPS): NPS is a short survey that measures how likely someone is to recommend the product or service. CORRELATION ANALYSIS FOR TELECOM MONITORING Written by @InterpretableAI & @IraIraCohen. In the first and second part of the blog series, we discussed the importance of correlation analysis in root cause analysis in general and in the context of promotional marketing. In a similar vein, in this blog we walk through how to leverage correlation analysis to address challenges in the telecom space.. The data deluge experienced in the telecom USING AI FOR BUSINESS FORECASTING AI For Business Forecasting. Regardless of your industry, the countless metrics and KPIs at your disposal is currency you can use to purchase more accurate business forecasting. Machine learning is autonomously powering these forecasts, because of its superior abilities to be accurate, scale, adapt to fluctuating behavior anddeliver results in
INTRODUCING MLWATCHER MLWatcher collects and monitors metrics from machine learning models in production. This open source Python agent is free to use, simply connect to your BI service to visualize the results. To detect anomalies in these metrics, either set rule-based alerting, or sync to an ML anomaly detection solution, such as Anodot, to execute at scale. HOW TO REDUCE FALSE POSITIVES USING MACHINE LEARNING PLATFORM? This particular metric shows the total revenue generated by users from Great Britain using iOS mobile devices. At 4 a.m. on Oct. 18, the value began to dip below the metric’s baseline (the area shaded in blue), which is the range Anodot’s algorithms predict as normal forthis metric.
CLOUD COST MONITORING USING AI AND MACHINE LEARNING Cost monitoring: Instead of just providing generic cloud costs, one of the main advantages of AI-based monitoring is that costs are specific to the service, region, team, and instance type. When anomalies do occur, this level of granularity allows for a much faster time-to-resolution. Usage monitoring: The next layer consists ofmonitoring
ANODOT | ANOMALY DETECTION FOR BUSINESS MONITORINGPRODUCTSOLUTIONSCOMPANYRESOURCESAUTONOMOUS FORECASTINTEGRATIONS Fastest incident detection and correlation. Detect anomalies across the business 15X faster. Cut incident-related costs by 70%. Anodot’s patented inference engine lets you know what is happening, where and why as soon as possible, for lightning-fast resolution. Learn More.ABOUT US | ANODOT
Anodot is an industry leader in Business Monitoring, an AI-driven approach that empowers businesses to safeguard their revenues and costs, digital partners, and audience journey, experience and engagement. By leveraging AI to constantly monitor and correlate business performance, Anodot identifies revenue-critical issues,providing real-time
THE ROUTE TO AUTOMATED REMEDIATION Step 4: Event Correlation. This is one of the steps that connects the detection to the remediation. Correlating anomalies to the events that influence them is a must for root cause analysis. This process identifies relationships between metrics and the events that impact how they behave, for example, connecting site down-time tomaintenance, or
CLOUD COST MONITORING USING AI AND MACHINE LEARNING Cost monitoring: Instead of just providing generic cloud costs, one of the main advantages of AI-based monitoring is that costs are specific to the service, region, team, and instance type. When anomalies do occur, this level of granularity allows for a much faster time-to-resolution. Usage monitoring: The next layer consists ofmonitoring
THE COSTS OF POOR DATA QUALITY Erroneous decisions made from bad data are not only inconvenient but also extremely costly. According to Gartner research, “the average financial impact of poor data quality on organizations is $9.7 million per year.”. IBM also discovered that in the US alone, businesses lose $3.1 trillion annually due to WHAT IS TIME SERIES DATABASE? A time series database consists of state change information that is indexed by time. It usually consists of a subject, the point in time and the measurements. When writing time series data, high throughput is critical for the database requiring it to be continuous and concurrent. This is important because writes make up roughly 95% ofdatabase
SMART AXIATA USES ANODOT TO ENSURE SEAMLESS SERVICE Smart Axiata was for years unable to monitor its tens of thousands of KPIs. Troubleshooting often took hours or even days. In this video, CTO Andrey Kuzin and Senior Data Analyst Ming Jin Siew share how Anodot has helped them improve their monitoring capabilities UNKNOWN UNKNOWNS ARE BIG OPPORTUNITIES Written by Anodot. Anodot is the leader in Autonomous Business Monitoring. Data-driven companies use Anodot's machine learning platform to detect business incidents in real time, helping slash time to detection by as much as 80 percent and reduce alert noise by asmuch as 95 percent.
ULTIMATE GUIDE TO BUILDING A MACHINE LEARNING ANOMALY The Definitive Guide For Building An Anomaly Detection System. An introduction to design principles of creating a machine learning based anomaly detection system. MIGRATING ANGULARJS TO ANGULAR WITHOUT LOSING YOUR HEAD Using angular-ui-router, we simply set React components under a “react” URL root, like so: Our reactCtrl used ng-react to set the React root: Then we set the Angular router to render an Angular controller, which later would render a React component using ng-react. The React router could take control of everything that comes after a“react
ANODOT | ANOMALY DETECTION FOR BUSINESS MONITORINGPRODUCTSOLUTIONSCOMPANYRESOURCESAUTONOMOUS FORECASTINTEGRATIONS Fastest incident detection and correlation. Detect anomalies across the business 15X faster. Cut incident-related costs by 70%. Anodot’s patented inference engine lets you know what is happening, where and why as soon as possible, for lightning-fast resolution. Learn More.ABOUT US | ANODOT
Anodot is an industry leader in Business Monitoring, an AI-driven approach that empowers businesses to safeguard their revenues and costs, digital partners, and audience journey, experience and engagement. By leveraging AI to constantly monitor and correlate business performance, Anodot identifies revenue-critical issues,providing real-time
THE ROUTE TO AUTOMATED REMEDIATION Step 4: Event Correlation. This is one of the steps that connects the detection to the remediation. Correlating anomalies to the events that influence them is a must for root cause analysis. This process identifies relationships between metrics and the events that impact how they behave, for example, connecting site down-time tomaintenance, or
CLOUD COST MONITORING USING AI AND MACHINE LEARNING Cost monitoring: Instead of just providing generic cloud costs, one of the main advantages of AI-based monitoring is that costs are specific to the service, region, team, and instance type. When anomalies do occur, this level of granularity allows for a much faster time-to-resolution. Usage monitoring: The next layer consists ofmonitoring
THE COSTS OF POOR DATA QUALITY Erroneous decisions made from bad data are not only inconvenient but also extremely costly. According to Gartner research, “the average financial impact of poor data quality on organizations is $9.7 million per year.”. IBM also discovered that in the US alone, businesses lose $3.1 trillion annually due to WHAT IS TIME SERIES DATABASE? A time series database consists of state change information that is indexed by time. It usually consists of a subject, the point in time and the measurements. When writing time series data, high throughput is critical for the database requiring it to be continuous and concurrent. This is important because writes make up roughly 95% ofdatabase
SMART AXIATA USES ANODOT TO ENSURE SEAMLESS SERVICE Smart Axiata was for years unable to monitor its tens of thousands of KPIs. Troubleshooting often took hours or even days. In this video, CTO Andrey Kuzin and Senior Data Analyst Ming Jin Siew share how Anodot has helped them improve their monitoring capabilities UNKNOWN UNKNOWNS ARE BIG OPPORTUNITIES Written by Anodot. Anodot is the leader in Autonomous Business Monitoring. Data-driven companies use Anodot's machine learning platform to detect business incidents in real time, helping slash time to detection by as much as 80 percent and reduce alert noise by asmuch as 95 percent.
ULTIMATE GUIDE TO BUILDING A MACHINE LEARNING ANOMALY The Definitive Guide For Building An Anomaly Detection System. An introduction to design principles of creating a machine learning based anomaly detection system. MIGRATING ANGULARJS TO ANGULAR WITHOUT LOSING YOUR HEAD Using angular-ui-router, we simply set React components under a “react” URL root, like so: Our reactCtrl used ng-react to set the React root: Then we set the Angular router to render an Angular controller, which later would render a React component using ng-react. The React router could take control of everything that comes after a“react
REAL-TIME TRADING PLATFORM MONITORING Monitor 100% of your trading data in real-time with Anodot. Gain granular visibility into your positions and improve your cash management, order execution, clearing and settlement and riskdecision-making.
REAL-TIME PAYMENT MONITORING SYSTEM The company’s revenue stream is a top KPI, and must be monitored constantly. Companies rely on endpoint APIs to execute payments and must ensure the reliability and consistency of payments across multiple payment entities, networks, geographies and devices. ZERO TOUCH NETWORK MONITORING CSPs use Anodot as the “Brain” on top of their network to help build resilience. Anodot’s platform uses self-learning at scale to constantly monitor and correlate network and service anomalies across the entire telco stack, providing actionable alerts in their context, improving Time to Detect and Time to Resolve incidents by 30% -50%. TELCO ANALYTICS FOR TELECOM COMPANIES Manual analytics only increase the time to detect. Anodot easily integrates all your data sources in one centralized platform, breaking down silos to identify incidents affecting revenue streams. Our patented correlation engine clearly maps out related metrics andevents
OSS TELECOM NETWORK MONITORING Monitor network performance in context with AI. Anodot uses a patented ML approach to monitor 100% of your data, learn every metrics’ behavior, and provide spot-on alerts critical failures. Anodot helps telcos to optimize service levels and maximize profitability by ensuring customer loyalty and maintaining overall network performance. INTRODUCTION TO TIME SERIES METRICS Source: Machine Learning Mastery. Time Series Metrics for Time Series Databases. One common application of time series metrics is for monitoring systems and time series databases (discussed further below). For example, Prometheus is an open-source time series database which offers four core metric types including: Running counter: this is a cumulative metric that represents a single USING AI FOR BUSINESS FORECASTING AI For Business Forecasting. Regardless of your industry, the countless metrics and KPIs at your disposal is currency you can use to purchase more accurate business forecasting. Machine learning is autonomously powering these forecasts, because of its superior abilities to be accurate, scale, adapt to fluctuating behavior anddeliver results in
ENSURE DATA QUALITY WITH AI ANALYTICS Since at the end of the day everything is data, a smarter way to approach data quality problems is through AI analytics, leveraging anomaly detection. Anomaly detection flags “bad” data, identifying suspicious anomalies, that can impact data quality. By tracking and evaluating data, anomaly detection gives critical insights into data CONSUMER BROADBAND TAKES CENTER STAGE Autonomous monitoring solutions help consumer broadband operators maintain network availability, prevent and mitigate outages and service degradation, and improve the customer experience. WHAT IS AI ANALYTICS? AI analytics refers to a subset of business intelligence that uses machine learning techniques to discover insights, find new patterns and discover relationships in the data. In practice, AI analytics is the process of automating much of the work that a data analyst would normally perform. While the goal is certainly not to replace analysts,AI
* Product
* Autonomous Detection * Autonomous Forecast* Integrations
* Technology
* Solutions __
* Industries __
* Online Business __* eCommerce __
* Fintech __
* Gaming __
* AdTech __
* Telco __
* OSS Telecom __
* BSS Telecom __
* Use Cases __
* Customer Experience __* Partners __
* Revenue and Cost __* See more __
* Company
* About __
* Customers __
* Careers
* News __
* Contact Us __
* Events __
* Patents
* Recognition
* Resources
* All Resources
* Blog
* Documents
* Videos & Podcasts
* Webinars
* Case Studies
* Learning Center
* Support __
* API
* Login
Login Request Demo
* Product
* Autonomous Detection * Autonomous Forecast* Integrations
* Technology
* Solutions __
* Industries __
* Online Business __* eCommerce __
* Fintech __
* Gaming __
* AdTech __
* Telco __
* OSS Telecom __
* BSS Telecom __
* Use Cases __
* Customer Experience __* Partners __
* Revenue and Cost __* See more __
* Company
* About __
* Customers __
* Careers
* News __
* Contact Us __
* Events __
* Patents
* Recognition
* Resources
* All Resources
* Blog
* Documents
* Videos & Podcasts
* Webinars
* Case Studies
* Learning Center
* Support __
* API
* Login
Request demo
WE MONITOR
YOUR BUSINESS.
Anodot monitors all your data in real time for lightning-fast detection of the incidents that impact your revenueWatch Demo
COMPLETE
HIGH-DEFINITION COVERAGE,IN REAL TIME
Anodot is an advanced AI platform, built from the ground up to monitor, analyze and correlate 100% of company data in real-time, dramatically enhancing the performance and reliability of yourbusiness.
JuxtaposeJS
WHAT WE DO
REVENUE MONITORING
Protect your revenue by monitoring all your revenue streams to surface potential issues and opportunities in real-timeRead more
CUSTOMER EXPERIENCE MONITORING Find and fix incidents before they impact your users to drive improved conversions, customer experience, retention and revenuesRead more
DIGITAL PARTNERS
MONITORING
Keep tabs on billions of daily events across all 3rd party tech providers to immediately surface critical anomalies that impact yourbusiness operations
Read more
FASTEST INCIDENT DETECTION AND CORRELATION Detect anomalies across the business 15X faster. Cut incident-related costs by 70%. Anodot’s patented inference engine lets you know what is happening, where and why as soon as possible, for lightning-fastresolution.
Learn More
ONLY THE ALERTS YOU NEED, WHEN YOU NEED THEM Leave alert storms, false positives and false negatives behind. Anodot's autonomous anomaly detection learns the normal behavior of every metric to distill billions of data events into the single, scored, spot-on anomaly alerts that you need to know about right now.Learn More
KNOW WHAT’S COMING Anticipate demand and business results with Anodot’s turn-key AI-powered forecasting. Anodot works on data streams in real-time to provide forecasts in the moment, so that your operation is optimized for every future scenario.Learn More
KING
70% INCIDENT COST REDUCTION “Even with our massive dataflow, Anodot has proven that it can seamlessly correlate data accross millions of real-time metrics - alerting us immediately so we can react instantly.”Nanako Yamagishi
Director of Incident and of Service OperationsLearn More
FULLY AUTONOMOUS MONITORING There’s no need to define what data to look for or when, no manual thresholds to set up or update. Anodot’s patented machine learning creates a next-generation, hands-off analytics experience for all users across the business.Learn More
OUR PATENTS
ANOMALY SCORE
US10061632B2
SEASONALITY
US10061677B2
CORRELATION TECHNOLOGYUS20160210556A1
HD BASELINE AT SCALEPENDING
FEATURED RESOURCES
MACHINE LEARNING 6 min read Don't Treat Your Business Metrics Like Other Metrics Why? Because monitoring machines and monitoring business KPIs are completely different tasks.Read more
BLOG POST 5 min read Atlassian: Anodot is our ‘Safety Net’ Atlassian, the software company behind Jira and Trello, credits Anodot with keeping their employees in touch with product performance and customer experience.Read more
BLOG POST 5 min read The 5 Whys: Why Use Monitoring at All? The market shift in the monitoring space is happening quickly. A top-down data approach and auto-remediation with AI is what will help companies stay ahead in this ever-changing industry.Read more
MACHINE LEARNING 6 min read Don't Treat Your Business Metrics Like Other Metrics Why? Because monitoring machines and monitoring business KPIs are completely different tasks.Read more
BLOG POST 5 min read Atlassian: Anodot is our ‘Safety Net’ Atlassian, the software company behind Jira and Trello, credits Anodot with keeping their employees in touch with product performance and customer experience.Read more
BLOG POST 5 min read The 5 Whys: Why Use Monitoring at All? The market shift in the monitoring space is happening quickly. A top-down data approach and auto-remediation with AI is what will help companies stay ahead in this ever-changing industry.Read more
‹›
AUTONOMOUS BUSINESS MONITORING MONITOR AND FORECAST YOUR BUSINESS PERFORMANCE Anodot’s Deep 360® monitoring technology constantly analyzes the patterns and correlations of all your metrics to provide fast, accurate, and meaningful alerts.Request Demo
PRODUCT
* Autonomous Detection * Autonomous Forecast* Integrations
* Technology
INDUSTRIES
* Online Business
* Ecommerce
* Fintech
* Gaming
* AdTech
* Telco
* OSS Telcom
* BSS Telcom
USE CASES
* Customer Experience* Partners
* Revenue and Cost
* See more
COMPANY
* About
* Customers
* Careers
* News
* Contact Us
* Events
* Patents
* Recognition
RESOURCES
* All Resources
* Blog
* Documents
* Videos & Podcasts
* Webinars
* Case Studies
* Learning Center
* Support
* API
2020 Anodot Ltd. All Rights Reserved Terms of Use Terms Privacy Policy Privacy Security Statement Security StatementDetails
Copyright © 2024 ArchiveBay.com. All rights reserved. Terms of Use | Privacy Policy | DMCA | 2021 | Feedback | Advertising | RSS 2.0