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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

DataOps ETL Validator stands out as an all-encompassing tool for automating data validation and ETL testing. It serves as an efficient ETL/ELT validation solution that streamlines the testing processes of data migration and data warehouse initiatives, featuring a user-friendly, low-code, no-code interface with component-based test creation and a convenient drag-and-drop functionality. The ETL process comprises extracting data from diverse sources, applying transformations to meet operational requirements, and subsequently loading the data into a designated database or data warehouse. Testing within the ETL framework requires thorough verification of the data's accuracy, integrity, and completeness as it transitions through the various stages of the ETL pipeline to ensure compliance with business rules and specifications. By employing automation tools for ETL testing, organizations can facilitate data comparison, validation, and transformation tests, which not only accelerates the testing process but also minimizes the need for manual intervention. The ETL Validator enhances this automated testing by offering user-friendly interfaces for the effortless creation of test cases, thereby allowing teams to focus more on strategy and analysis rather than technical intricacies. In doing so, it empowers organizations to achieve higher levels of data quality and operational efficiency.

Description

Our cutting-edge data migration solution is meticulously crafted to seamlessly transfer and convert data from outdated legacy systems to modern frameworks, featuring robust data validation processes and instant reporting capabilities. Frequently, during the data migration journey, critical information may be lost or compromised, leading to significant challenges. The transition from older systems to newer ones entails a complicated and lengthy procedure. While it might be tempting to take shortcuts or to merge data without the necessary tools, such approaches often lead to expensive and prolonged frustrations. For institutions like State Agencies, the stakes are too high to risk errors during the initial transfer. This phase is notoriously difficult, and many organizations struggle to execute it successfully. A successful data migration initiative relies heavily on a solid initial design, which serves as the blueprint for the entire project. This stage involves carefully crafting and coding the rules needed to process various data types according to your unique requirements, ensuring a smoother migration experience. Ultimately, investing time and resources at this stage can significantly enhance the overall efficiency and accuracy of the migration process.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Azure Databricks
Azure Synapse Analytics
Datagaps DataOps Suite
Microsoft Power BI
Oracle Analytics Cloud
Salesforce
Snowflake
Tableau

Integrations

Azure Databricks
Azure Synapse Analytics
Datagaps DataOps Suite
Microsoft Power BI
Oracle Analytics Cloud
Salesforce
Snowflake
Tableau

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

Datagaps

Country

United States

Website

www.datagaps.com/etl-validator/

Vendor Details

Company Name

Pritna

Founded

2015

Country

United States

Website

pritna.com/products/data-migration-tool/

Product Features

ETL

Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control

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