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Description
3X Code Conversion is an AI-powered accelerator for converting legacy data engineering code into modern cloud-ready code. The platform automates SQL and ETL migration for enterprises moving from systems such as Teradata, Oracle, Netezza, SQL Server, MySQL, PostgreSQL, and Redshift. It supports target platforms including Snowflake, Databricks, BigQuery, Microsoft Fabric, Synapse, Delta Lake, and other modern cloud data environments. 3X Code Conversion handles SQL scripts, stored procedures, views, ETL jobs, BTEQ scripts, FastLoad jobs, SSIS pipelines, macros, and undocumented legacy codebases. The accelerator parses code semantically, resolves dependencies, scores object complexity, identifies conversion risk, and classifies which objects can be fully automated or need developer review. Its agentic conversion engine rebuilds legacy logic using target-platform patterns rather than relying on simple find-and-replace translation. Built-in validation checks row counts, column mappings, data types, null handling, join logic, and regression quality before deployment. Every flagged object includes developer action items explaining what failed, why it failed, where the issue appears, and what needs to be fixed. By combining automated conversion, refactoring, testing, documentation, and migration reporting, 3X Code Conversion helps enterprises accelerate cloud data modernization with less manual rewrite work.
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
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Screenshots View All
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Integrations
No details available.
Integrations
No details available.
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
3X Data Engineering
Founded
2023
Country
United State
Website
www.3xdataengineering.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