Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Consolidate information from over 100 sources to empower your team to provide enhanced insights swiftly. Integrate data from any data warehouse into the business tools preferred by your teams. Optimize your data operations efficiently through a singular platform uniquely designed to fulfill all the needs of your data teams, potentially reducing your expenses by as much as 75%. If you're looking to avoid the complexities of managing a data warehouse, our platform is the sole solution that provides an integrated managed data warehouse tailored to address all your data management requirements. Choose from an expanding collection of more than 100 fully managed connectors and over 20 destinations, including SaaS applications, databases, data warehouses, and beyond. Enjoy complete and secure control over the specific data you wish to transfer, while scheduling and transforming your data for analytics effortlessly, ensuring it remains in sync with your operational pipelines. Our platform not only simplifies data management but also enhances collaboration across teams, making it a valuable asset for any organization.
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.
API Access
Has API
No
API Access
Has API
No
Integrations
Salesforce
Yes
Snowflake
Yes
Apple Search Ads
Yes
CleverTap
Yes
Facebook
Yes
Gmail
Yes
Google Ad Manager
Yes
Google Analytics
Yes
Instagram
Yes
Keepa
Yes
Integrations
Salesforce
Yes
Snowflake
Yes
Apple Search Ads
No
CleverTap
No
Facebook
No
Gmail
No
Google Ad Manager
No
Google Analytics
No
Instagram
No
Keepa
No
Pricing Details
$250 per month
Free Trial
Yes
Free Version
Yes
Pricing Details
No price information available.
Free Trial
Yes
Free Version
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
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)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
Yes
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
DataChannel
Founded
2020
Country
India
Website
www.datachannel.co
Vendor Details
Company Name
Datagaps
Country
United States
Website
www.datagaps.com/etl-validator/
Product Features
Data Management
Customer Data
No
Data Analysis
No
Data Capture
No
Data Integration
No
Data Migration
No
Data Quality Control
No
Data Security
No
Information Governance
No
Master Data Management
No
Match & Merge
No
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
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