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Average Ratings 0 Ratings

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features
design
support

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Write a Review

Description

Amazon SageMaker Model Training streamlines the process of training and fine-tuning machine learning (ML) models at scale, significantly cutting down both time and costs while eliminating the need for infrastructure management. Users can leverage top-tier ML compute infrastructure, benefiting from SageMaker’s capability to seamlessly scale from a single GPU to thousands, adapting to demand as necessary. The pay-as-you-go model enables more effective management of training expenses, making it easier to keep costs in check. To accelerate the training of deep learning models, SageMaker’s distributed training libraries can divide extensive models and datasets across multiple AWS GPU instances, while also supporting third-party libraries like DeepSpeed, Horovod, or Megatron for added flexibility. Additionally, you can efficiently allocate system resources by choosing from a diverse range of GPUs and CPUs, including the powerful P4d.24xl instances, which are currently the fastest cloud training options available. With just one click, you can specify data locations and the desired SageMaker instances, simplifying the entire setup process for users. This user-friendly approach makes it accessible for both newcomers and experienced data scientists to maximize their ML training capabilities.

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 No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Adobe Marketo Engage No 
Amazon SageMaker Yes 
Amazon Web Services (AWS) Yes 
BERT Yes 
CodeGPT Yes 
DALL·E 2 Yes 
Google Analytics No 
Hugging Face Yes 
Microsoft Excel No 
Microsoft Power BI No 
NVIDIA NeMo Megatron Yes 
NetSuite No 
PyTorch Yes 
Sage 500 No 
Salesforce No 
StackHawk No 
Tableau No 
TensorFlow Yes 
Xero No 
Zendesk No 

Integrations

Adobe Marketo Engage Yes 
Amazon SageMaker No 
Amazon Web Services (AWS) No 
BERT No 
CodeGPT No 
DALL·E 2 No 
Google Analytics Yes 
Hugging Face No 
Microsoft Excel Yes 
Microsoft Power BI Yes 
NVIDIA NeMo Megatron No 
NetSuite Yes 
PyTorch No 
Sage 500 Yes 
Salesforce Yes 
StackHawk Yes 
Tableau Yes 
TensorFlow No 
Xero Yes 
Zendesk Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
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 No 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Types of Training

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

Types of Training

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

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/sagemaker/train/

Vendor Details

Company Name

Zap

Founded

2001

Country

Australia

Website

www.zapbi.com

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 

Product Features

Business Intelligence

Ad Hoc Reports Yes 
Benchmarking No 
Budgeting & Forecasting No 
Dashboard Yes 
Data Analysis Yes 
Key Performance Indicators Yes 
Natural Language Generation (NLG) No 
Performance Metrics Yes 
Predictive Analytics Yes 
Profitability Analysis Yes 
Strategic Planning No 
Trend / Problem Indicators Yes 
Visual Analytics Yes 

Alternatives

Alternatives