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Description
Auraa is Covasant's innovative, agent-driven data platform designed specifically for Databricks, offering the quickest route to transforming data into AI-ready formats. By utilizing conversational AI features that operate in natural language, businesses can leverage agents to autonomously identify various data sources, construct pipelines, maintain data quality, and register all components in Unity Catalog right from the start. This approach completely removes the need for traditional pipeline code, significantly reduces engineering backlogs, and eliminates months of manual setup efforts. Typically, establishing a data lake on Databricks can take upwards of 18 to 24 months, but with Auraa, the onboarding of the initial data source can be accomplished in less than 15 minutes, the first use case can be launched within hours, and the entire deployment period can be condensed to approximately 8 to 10 weeks, resulting in a cost reduction of up to 70%. Auraa redefines data engineering decisions by managing them as structured, versioned, and governed metadata instead of relying on fragile, hand-coded pipelines. The platform guarantees that the Databricks lakehouse is not only reproducible and auditable but also consistently enhances its capabilities through the use of agents, paving the way for continuous improvement and efficiency in data management.
Description
DQV is the comprehensive data quality and testing platform developed by Kumaran Systems, catering to teams engaged in the movement, masking, or validation of substantial data volumes. This tool meticulously evaluates source and target datasets on a field-by-field basis, identifies discrepancies, and produces mismatch reports, eliminating the need for manual checks using spreadsheets.
The platform encompasses five key functionalities: it performs field-level comparisons while detecting drift, facilitates migration mapping between different schemas, offers deterministic PII masking, conducts record- and table-level validation with the ability for on-the-fly corrections, and generates synthetic data for teams lacking access to production data for testing.
DQV is compatible with a wide range of data sources, including SQL Server, Oracle, MySQL, PostgreSQL, AWS, Azure, GCP, flat files, JSON, XML, and REST APIs, and it seamlessly integrates with tools like Informatica, Databricks, and CI/CD pipelines, or can operate independently as a library or CLI tool.
In real-world applications, DQV has successfully validated an impressive 26.6 million bank records in less than 22 minutes, showcasing its efficiency and speed. Additionally, a free trial is offered, along with various licensing options, including individual, enterprise, and on-premises plans, ensuring flexibility for different organizational needs. This versatile solution not only enhances data integrity but also streamlines the testing process across multiple platforms.
API Access
Has API
API Access
Has API
Screenshots View All
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Screenshots View All
No images available
Integrations
Databricks
Pricing Details
No price information available.
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
Covasant Technologies Private Limited
Country
India
Website
www.covasant.com
Vendor Details
Company Name
Kumaran Systems
Founded
1992
Country
United States
Website
kumaran.com/products/dqv/
Product Features
Product Features
Data Quality
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management