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Average Ratings 0 Ratings

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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

Save hours by developing and maintaining ETL/ELT pipelines using an easy-to use environment that allows for effortless debugging. Visualize changes before deployment to simplify development, accelerate testing, and reduce debugging. Work with Python and our simple interface to foster team collaboration and save valuable time during the most difficult development stages. Consolidate data in any format, from any source and any size with no hesitations. Ensure the most accurate data by utilizing error flagging and debugging in real-time within specific data processes as well as across pipelines. Use compute, storage and network bandwidth to auto-scale infrastructure as data volume and speed increase. Real-time data observability can help you identify and pinpoint problems. Zoom in and thoroughly troubleshoot your data pipelines.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

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

Integrations

Azure Databricks No 
Azure Synapse Analytics No 
Datagaps DataOps Suite No 
Microsoft Power BI No 
Oracle Analytics Cloud No 
Salesforce No 
Snowflake No 
Tableau No 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Pricing Details

Free
Credit based pricing system
Free Trial Yes 
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 No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person Yes 

Vendor Details

Company Name

Datagaps

Country

United States

Website

www.datagaps.com/etl-validator/

Vendor Details

Company Name

Datorios

Founded

2020

Country

United States

Website

datorios.com

Product Features

ETL

Data Analysis No 
Data Filtering No 
Data Quality Control No 
Job Scheduling No 
Match & Merge No 
Metadata Management No 
Non-Relational Transformations No 
Version Control No 

Product Features

Data Extraction

Disparate Data Collection No 
Document Extraction No 
Email Address Extraction No 
IP Address Extraction No 
Image Extraction No 
Phone Number Extraction No 
Pricing Extraction No 
Web Data Extraction No 

Data Management

Customer Data No 
Data Analysis No 
Data Capture No 
Data Integration Yes 
Data Migration Yes 
Data Quality Control No 
Data Security No 
Information Governance Yes 
Master Data Management No 
Match & Merge No 

ETL

Data Analysis No 
Data Filtering Yes 
Data Quality Control No 
Job Scheduling Yes 
Match & Merge Yes 
Metadata Management No 
Non-Relational Transformations Yes 
Version Control Yes 

Integration

Dashboard Yes 
ETL - Extract / Transform / Load Yes 
Metadata Management No 
Multiple Data Sources Yes 
Web Services No 

Master Data Management

Data Governance Yes 
Data Masking No 
Data Source Integrations Yes 
Hierarchy Management No 
Match & Merge No 
Metadata Management Yes 
Multi-Domain No 
Process Management Yes 
Relationship Mapping Yes 
Visualization No 

Alternatives

Alternatives

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