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What is Datorios?
Streamline your workflow by creating and managing ETL/ELT pipelines in a user-friendly environment that simplifies debugging processes. Prior to deployment, visualize changes to enhance development, speed up testing, and minimize errors during debugging. Leverage Python along with our intuitive interface to promote collaboration among team members, ultimately conserving precious time during challenging development phases. Integrate data from any format, source, or size without hesitation, ensuring ease of use. Achieve the highest level of data accuracy by employing real-time error flagging and debugging throughout specific processes and across entire pipelines. Automatically scale your infrastructure using compute, storage, and network resources as data volume and velocity increase, ensuring optimal performance. Additionally, real-time data observability enables you to detect and address issues effectively, allowing for a deep dive into your data pipelines for thorough troubleshooting and optimization. This comprehensive approach not only boosts efficiency but also enhances the overall quality of your data management efforts.
What is Datagaps ETL Validator?
DataOps ETL Validator is a comprehensive solution designed for automating the processes of data validation and ETL testing. It provides an effective means for validating ETL/ELT processes, simplifying the testing phases associated with data migration and warehouse projects, and includes a user-friendly interface that supports both low-code and no-code options for creating tests through a convenient drag-and-drop system. The ETL process involves extracting data from various sources, transforming it to align with operational requirements, and ultimately loading it into a specific database or data warehouse. Effective testing within this framework necessitates a meticulous approach to verifying the accuracy, integrity, and completeness of data as it moves through the different stages of the ETL pipeline, ensuring alignment with established business rules and specifications. By utilizing automation tools for ETL testing, companies can streamline data comparison, validation, and transformation processes, which not only speeds up testing but also reduces the reliance on manual efforts. The ETL Validator takes this automation a step further by facilitating the seamless creation of test cases through its intuitive interfaces, enabling teams to concentrate more on strategic planning and analytical tasks rather than getting bogged down by technical details. Consequently, it empowers organizations to enhance their data quality and improve operational efficiency significantly, fostering a culture of data-driven decision-making. Additionally, the tool's capabilities allow for easier collaboration among team members, promoting a more cohesive approach to data management.
Integrations Supported
Azure Databricks
Azure Synapse Analytics
Datagaps DataOps Suite
Microsoft Power BI
Oracle Analytics Cloud
Salesforce
Snowflake
Tableau
Integrations Supported
Azure Databricks
Azure Synapse Analytics
Datagaps DataOps Suite
Microsoft Power BI
Oracle Analytics Cloud
Salesforce
Snowflake
Tableau
API Availability
Has API
API Availability
Has API
Pricing Information
Free
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Datorios
Date Founded
2020
Company Location
United States
Company Website
datorios.com
Company Facts
Organization Name
Datagaps
Company Location
United States
Company Website
www.datagaps.com/etl-validator/
Categories and Features
Data Extraction
Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction
Data Management
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge
ETL
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control
Integration
Dashboard
ETL - Extract / Transform / Load
Metadata Management
Multiple Data Sources
Web Services
Master Data Management
Data Governance
Data Masking
Data Source Integrations
Hierarchy Management
Match & Merge
Metadata Management
Multi-Domain
Process Management
Relationship Mapping
Visualization
Categories and Features
ETL
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control