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features
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support

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Description

A data lake serves as a comprehensive repository designed for handling extensive data and artificial intelligence operations, accommodating both structured and unstructured data at any volume. It is essential for organizations looking to harness the power of Data Lake Formation (DLF), which simplifies the creation of a cloud-native data lake environment. DLF integrates effortlessly with various computing frameworks while enabling centralized management of metadata and robust enterprise-level permission controls. It systematically gathers structured, semi-structured, and unstructured data, ensuring substantial storage capabilities, and employs a design that decouples computing resources from storage solutions. This architecture allows for on-demand resource planning at minimal costs, significantly enhancing data processing efficiency to adapt to swiftly evolving business needs. Furthermore, DLF is capable of automatically discovering and consolidating metadata from multiple sources, effectively addressing issues related to data silos. Ultimately, this functionality streamlines data management, making it easier for organizations to leverage their data assets.

Description

AI teams encounter obstacles that necessitate the development of innovative technologies, which we specialize in creating. Traditional data warehouses and lakes struggle to accommodate unstructured data types such as text, images, and videos. Our approach integrates AI with software development, specifically designed for data scientists, machine learning engineers, and data engineers alike. Instead of reinventing existing solutions, we provide a swift and cost-effective route to bring your projects into production. Your data remains securely stored under your control, and model training occurs on your own infrastructure. By addressing the limitations of current data handling methods, we ensure that AI teams can effectively meet their challenges. Our Studio functions as an extension of platforms like GitHub, GitLab, or BitBucket, allowing seamless integration. You can choose to sign up for our online SaaS version or reach out for an on-premise installation tailored to your needs. This flexibility allows organizations of all sizes to adopt our solutions effectively.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Alibaba Cloud Yes 
Amazon Web Services (AWS) No 
Bitbucket No 
Git No 
GitHub No 
GitLab No 
Google Cloud Platform No 
Kubernetes No 
Microsoft Azure No 

Integrations

Alibaba Cloud No 
Amazon Web Services (AWS) Yes 
Bitbucket Yes 
Git Yes 
GitHub Yes 
GitLab Yes 
Google Cloud Platform Yes 
Kubernetes Yes 
Microsoft Azure Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version Yes 

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 Yes 
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) No 
Online Support Yes 

Customer Support

Business Hours No 
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 Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Vendor Details

Company Name

Alibaba Cloud

Founded

2008

Country

China

Website

www.alibabacloud.com/es/product/datalake-formation

Vendor Details

Company Name

Iterative

Founded

2018

Country

United States

Website

iterative.ai/

Product Features

Product Features

Artificial Intelligence

Chatbot No 
For Healthcare No 
For Sales No 
For eCommerce No 
Image Recognition No 
Machine Learning No 
Multi-Language No 
Natural Language Processing No 
Predictive Analytics No 
Process/Workflow Automation No 
Rules-Based Automation No 
Virtual Personal Assistant (VPA) No 

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 

Alternatives

Alternatives

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