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Description

AWS Data Exchange is a service designed to streamline the process of discovering, subscribing to, and utilizing third-party data within the cloud environment. It features an extensive catalog comprising over 3,500 data sets sourced from more than 300 different data providers, which include a variety of formats such as data files, tables, and APIs. This platform allows users to efficiently manage data procurement and governance by centralizing all third-party data subscriptions in one location while also providing the option to transfer existing subscriptions without incurring additional fees. Furthermore, AWS Data Exchange guarantees secure and compliant data usage by integrating with AWS Identity and Access Management (IAM) and offering data encryption both at rest and during transmission. Users can easily incorporate the subscribed data into their AWS ecosystem, enhancing their capabilities for analytics and machine learning projects. The service accommodates multiple data delivery methods, including direct access to data stored in Amazon S3 buckets managed by data providers, enabling subscribers to leverage these files with AWS solutions such as Amazon Athena and Amazon EMR. This comprehensive approach ensures that organizations can harness the power of third-party data while maintaining control and security throughout the process.

Description

Amazon SageMaker enables the identification of various types of unprocessed data, including images, text documents, and videos, while also allowing for the addition of meaningful labels and the generation of synthetic data to develop high-quality training datasets for machine learning applications. The platform provides two distinct options, namely Amazon SageMaker Ground Truth Plus and Amazon SageMaker Ground Truth, which grant users the capability to either leverage a professional workforce to oversee and execute data labeling workflows or independently manage their own labeling processes. For those seeking greater autonomy in crafting and handling their personal data labeling workflows, SageMaker Ground Truth serves as an effective solution. This service simplifies the data labeling process and offers flexibility by enabling the use of human annotators through Amazon Mechanical Turk, external vendors, or even your own in-house team, thereby accommodating various project needs and preferences. Ultimately, SageMaker's comprehensive approach to data annotation helps streamline the development of machine learning models, making it an invaluable tool for data scientists and organizations alike.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

AWS Identity and Access Management (IAM) Yes 
Alpha Vantage Yes 
Amazon Athena Yes 
Amazon EMR Yes 
Amazon S3 Yes 
Amazon SageMaker No 
Amazon SageMaker Unified Studio No 
Amazon Web Services (AWS) Yes 
Equifax BusinessConnect Yes 
FactSet Yes 
Mindfuel Yes 
Ovation LIMS Yes 
PredictHQ Yes 
ShareThis Yes 
Shutterstock Yes 
Verana Health Yes 
X (Twitter) Yes 
ZenML No 
prognosFACTOR Yes 

Integrations

AWS Identity and Access Management (IAM) No 
Alpha Vantage No 
Amazon Athena No 
Amazon EMR No 
Amazon S3 No 
Amazon SageMaker Yes 
Amazon SageMaker Unified Studio Yes 
Amazon Web Services (AWS) No 
Equifax BusinessConnect No 
FactSet No 
Mindfuel No 
Ovation LIMS No 
PredictHQ No 
ShareThis No 
Shutterstock No 
Verana Health No 
X (Twitter) No 
ZenML Yes 
prognosFACTOR No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

$0.08 per month
Free Trial No 
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 Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/data-exchange/

Vendor Details

Company Name

Amazon Web Services

Founded

2006

Country

United States

Website

aws.amazon.com/es/sagemaker/data-labeling/

Product Features

Product Features

Data Labeling

Human-in-the-loop No 
Labeling Automation No 
Labeling Quality No 
Performance Tracking No 
Polygon, Rectangle, Line, Point No 
SDK No 
Supports Audio Files No 
Task Management No 
Team Collaboration No 
Training Data Management No 

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