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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

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

Amazon SageMaker Data Wrangler significantly shortens the data aggregation and preparation timeline for machine learning tasks from several weeks to just minutes. This tool streamlines data preparation and feature engineering, allowing you to execute every phase of the data preparation process—such as data selection, cleansing, exploration, visualization, and large-scale processing—through a unified visual interface. You can effortlessly select data from diverse sources using SQL, enabling rapid imports. Following this, the Data Quality and Insights report serves to automatically assess data integrity and identify issues like duplicate entries and target leakage. With over 300 pre-built data transformations available, SageMaker Data Wrangler allows for quick data modification without the need for coding. After finalizing your data preparation, you can scale the workflow to encompass your complete datasets, facilitating model training, tuning, and deployment in a seamless manner. This comprehensive approach not only enhances efficiency but also empowers users to focus on deriving insights from their data rather than getting bogged down in the preparation phase.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon Redshift
Amazon S3
AWS Lambda
Amazon EMR
Amazon SageMaker
Amazon SageMaker Feature Store
Amazon SageMaker Studio
Amazon SageMaker Unified Studio
Amazon Simple Notification Service (SNS)
Amazon Web Services (AWS)
Apache Parquet
Apache Spark
Facebook Ads
Google Analytics
JSON
PySpark
SAP Cloud Platform
Salesforce
Snowflake
pandas

Integrations

Amazon Redshift
Amazon S3
AWS Lambda
Amazon EMR
Amazon SageMaker
Amazon SageMaker Feature Store
Amazon SageMaker Studio
Amazon SageMaker Unified Studio
Amazon Simple Notification Service (SNS)
Amazon Web Services (AWS)
Apache Parquet
Apache Spark
Facebook Ads
Google Analytics
JSON
PySpark
SAP Cloud Platform
Salesforce
Snowflake
pandas

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/lookout-for-metrics/

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/sagemaker/data-wrangler/

Product Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Product Features

Data Preparation

Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

Alternatives

Alternatives