Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Minimize false positives and leverage machine learning (ML) to effectively identify anomalies in business performance indicators. Investigate the underlying causes of these anomalies by clustering similar outliers together for analysis. Provide a summary of these root causes and prioritize them based on their impact. Ensure a smooth integration with AWS databases, storage services, and external SaaS platforms for comprehensive metrics monitoring and anomaly detection. Set up automated alerts and responses tailored to the detection of anomalies. Utilize Lookout for Metrics, which employs ML to both discover and analyze anomalies in business and operational datasets. The challenge of recognizing unexpected anomalies is compounded by the limitations of traditional manual methods that are prone to errors. Lookout for Metrics simplifies the detection and diagnosis of data inconsistencies without requiring any expertise in artificial intelligence (AI). Monitor irregular fluctuations in subscriptions, conversion rates, and revenue to remain vigilant about sudden market shifts, ultimately enhancing strategic decision-making capabilities. By adopting these advanced techniques, businesses can improve their overall performance management and response strategies.
Description
Protecting against unseen dangers through user and entity behavior analytics is essential. This approach uncovers irregularities and hidden threats that conventional security measures often overlook. By automating the integration of numerous anomalies into a cohesive threat, security analysts can work more efficiently. Leverage advanced investigative features and robust behavioral baselines applicable to any entity, anomaly, or threat. Employ machine learning to automate threat detection, allowing for a more focused approach to hunting with high-fidelity, behavior-based alerts that facilitate prompt review and resolution. Quickly pinpoint anomalous entities without the need for human intervention. With a diverse array of over 65 anomaly types and more than 25 threat classifications spanning users, accounts, devices, and applications, organizations maximize their ability to identify and address threats and anomalies. This combination of human insight and machine intelligence empowers businesses to enhance their security posture significantly. Ultimately, the integration of these advanced capabilities leads to a more resilient and proactive defense against evolving threats.
API Access
Has API
Yes
API Access
Has API
No
Integrations
Amazon S3
Yes
Amazon Simple Notification Service (SNS)
Yes
AWS Lambda
Yes
Amazon
No
Amazon API Gateway
No
Amazon Chime
No
Amazon SageMaker
No
Amazon Simple Queue Service (SQS)
No
Amazon Web Services (AWS)
No
Cisco Cloudlock
No
Integrations
Amazon S3
Yes
Amazon Simple Notification Service (SNS)
Yes
AWS Lambda
No
Amazon
Yes
Amazon API Gateway
Yes
Amazon Chime
Yes
Amazon SageMaker
Yes
Amazon Simple Queue Service (SQS)
Yes
Amazon Web Services (AWS)
Yes
Cisco Cloudlock
Yes
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
Yes
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Amazon
Founded
1994
Country
United States
Website
aws.amazon.com/lookout-for-metrics/
Vendor Details
Company Name
Cisco
Founded
1984
Country
United States
Website
www.splunk.com/en_us/products/user-behavior-analytics.html
Product Features
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No