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What is Azure AI Anomaly Detector?

Anticipate challenges before they occur by utilizing the Azure AI anomaly detection service, which integrates time-series anomaly detection capabilities into your applications, enabling quick identification of issues. This AI-driven Anomaly Detector analyzes various time-series datasets and smartly selects the most effective algorithm for anomaly detection, ensuring high accuracy. It can detect anomalies like spikes, drops, deviations from normal patterns, and shifts in trends through univariate and multivariate APIs. Additionally, the service can be customized to recognize different severity levels of anomalies tailored to your requirements. You also have the option to implement the anomaly detection service in the cloud or at the intelligent edge, based on your needs. With a powerful inference engine that assesses your time-series information, the service independently determines the best anomaly detection algorithm for your context, enhancing precision. This automated detection mechanism minimizes the dependency on labeled training data, allowing you to save time and focus on addressing emerging issues, which ultimately leads to enhanced operational efficacy. By harnessing this innovative tool, organizations can take a proactive approach to managing potential interruptions and refine their strategies for response. This capability not only improves organizational resilience but also fosters a culture of continuous improvement in operations.

What is Acryl Data?

Address the challenge of neglected data catalogs with Acryl Cloud, which enhances the realization of value through Shift Left strategies tailored for data creators while providing an intuitive interface for users. This platform allows for the immediate identification of data quality concerns, automates anomaly detection to prevent future complications, and supports quick resolutions when issues do crop up. Acryl Cloud supports both push and pull methods for ingesting metadata, simplifying upkeep while ensuring the information remains trustworthy, up-to-date, and thorough. For smooth operations, data should work effortlessly. Go beyond basic visibility by utilizing automated Metadata Tests that continually uncover insights and highlight new avenues for improvement. By establishing clear asset ownership and applying automatic detection, efficient notifications, and temporal lineage for tracing the origins of issues, organizations can reduce confusion and shorten resolution times. Consequently, this leads to a more streamlined and productive data management framework, fostering a culture of continuous improvement and adaptability.

Media

Media

Integrations Supported

Activate IAM
CTM360
Crestwood Cloud
Microsoft Azure
Sprinklr

Integrations Supported

Amazon Athena
Amazon SageMaker
Apache Hive
Apache Kafka
Apache NiFi
Elasticsearch
Google Cloud BigQuery
Great Expectations
Metabase
MongoDB
MySQL
SAP HANA
Snowflake
Tableau
Vertica

API Availability

Has API

API Availability

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

azure.microsoft.com/en-us/products/ai-services/ai-anomaly-detector/

Company Facts

Organization Name

Acryl Data

Date Founded

2021

Company Website

www.acryldata.io

Categories and Features

AI Observability

Not specified

AI Tools

Not specified

Anomaly Detection

Not specified

Categories and Features

Anomaly Detection

Not specified

Data Catalog

Not specified

Data Governance

Not specified

Metadata Management

Not specified

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