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What is DataForge?

DataForge is unique as the only framework that integrates all three essential aspects of data development. By combining distinct features from each element and applying a thorough methodology, it creates an unmatched foundation for effective data design. Its cloud version, DataForge Cloud (DFC), acts as a powerful management service for data platforms, intricately aligned with the DataForge framework. DFC streamlines this framework into efficient automated workflows for developers, enabling data processing on platforms like Databricks and Snowflake. With a combination of structured coding and an event-driven workflow engine, DFC guarantees full automation in establishing necessary processing steps and overseeing dependencies. This standardization of processing phases promotes consistent infrastructure sizing, which boosts efficiency. Furthermore, DFC enhances performance through the dynamic allocation of resources, selecting the best cluster or warehouse at each stage to ensure optimal cost-effectiveness without compromising quality. This innovative strategy not only simplifies the development workflow but also substantially improves the overall user experience, making data management more accessible and efficient for all users. Overall, DataForge and DFC represent a significant advancement in the realm of data development and management.

What is Auraa?

Auraa represents Covasant's cutting-edge, agent-driven data platform tailored exclusively for Databricks, enabling rapid transformation of data into formats suitable for AI applications. Utilizing conversational AI capabilities that function in natural language, organizations can harness agents to autonomously locate diverse data sources, build pipelines, ensure data integrity, and register all elements in Unity Catalog from the outset. This innovative approach entirely eliminates the requirement for conventional pipeline coding, substantially decreases engineering backlogs, and eradicates months of manual setup. Generally, creating a data lake on Databricks may take 18 to 24 months; however, with Auraa, onboarding the initial data source can be achieved in under 15 minutes, the first use case can be operational in mere hours, and the complete deployment timeline can shrink to around 8 to 10 weeks, leading to potential cost savings of up to 70%. By redefining data engineering processes, Auraa manages these as structured, versioned, and governed metadata, moving away from unreliable, hand-coded pipelines. Furthermore, the platform ensures that the Databricks lakehouse remains reproducible and auditable, while continuously improving its functionalities through the deployment of agents, ultimately driving efficiency and innovation in the realm of data management. This transformative capability positions Auraa as an essential tool for organizations aiming to streamline their data operations and accelerate their journey toward AI readiness.

Media

Media

No images available

Integrations Supported

Databricks
Snowflake

Integrations Supported

Databricks
Snowflake

API Availability

Has API

API Availability

Has API

Pricing Information

$2.50 per process
Free Version
Free Trial Offered?

Pricing Information

Pricing not provided
Free Version
Free Trial Offered?

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

DataForge

Date Founded

2023

Company Location

United State

Company Website

www.dataforgelabs.com

Company Facts

Organization Name

Covasant Technologies Private Limited

Company Location

India

Company Website

www.covasant.com

Categories and Features

Data Management

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

Categories and Features

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