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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

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.

Description

Finance teams cannot trust reports built on data their BI tool never validated. Power BI and OneLake do not enforce primary keys, so duplicate records reach financial statements silently. Zap Data Hub fixes that at the warehouse layer. It runs on Azure SQL, an ACID-compliant engine with enforced keys, and generates a star schema tuned for accounting structures. Delta processing applies only changed rows instead of reloading whole tables, which cuts both refresh windows and compute spend. A governed semantic layer keeps every consuming tool reading identical definitions. Sources covered: Sage X3, 100, 300 and Intacct; SAP Business One; Syspro; Dynamics 365 Business Central and Finance & Operations; Dynamics AX and NAV; Wiise; Xero. REST connectors reach further systems. Shipped as a fully managed cloud service on Microsoft Azure, certified to ISO/IEC 27001:2022.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Adobe Marketo Engage
Amazon SageMaker
Amazon SageMaker Unified Studio
Google Analytics
Microsoft Excel
Microsoft Power BI
NetSuite
Sage 500
Salesforce
StackHawk
Tableau
Xero
ZenML
Zendesk

Integrations

Adobe Marketo Engage
Amazon SageMaker
Amazon SageMaker Unified Studio
Google Analytics
Microsoft Excel
Microsoft Power BI
NetSuite
Sage 500
Salesforce
StackHawk
Tableau
Xero
ZenML
Zendesk

Pricing Details

$0.08 per month
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 Web Services

Founded

2006

Country

United States

Website

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

Vendor Details

Company Name

Zap

Founded

2001

Country

Australia

Website

www.zapbi.com

Product Features

Data Labeling

Human-in-the-loop
Labeling Automation
Labeling Quality
Performance Tracking
Polygon, Rectangle, Line, Point
SDK
Supports Audio Files
Task Management
Team Collaboration
Training Data Management

Product Features

Business Intelligence

Ad Hoc Reports
Benchmarking
Budgeting & Forecasting
Dashboard
Data Analysis
Key Performance Indicators
Natural Language Generation (NLG)
Performance Metrics
Predictive Analytics
Profitability Analysis
Strategic Planning
Trend / Problem Indicators
Visual Analytics

Alternatives