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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.
What is DataOps DataFlow?
Apache Spark offers a comprehensive component-driven platform that streamlines the automation of Data Reconciliation testing for contemporary Data Lake and Cloud Data Migration initiatives.
DataOps DataFlow serves as an innovative web-based tool designed to facilitate the automation of testing for ETL projects, Data Warehouses, and Data Migrations. You can utilize DataFlow to efficiently load data from diverse sources, perform comparisons, and transfer discrepancies either into S3 or a Database. This enables users to create and execute data flows with remarkable ease. It stands out as a premier testing solution specifically tailored for Big Data Testing.
Moreover, DataOps DataFlow seamlessly integrates with a wide array of both traditional and cutting-edge data sources, encompassing RDBMS, NoSQL databases, as well as cloud-based and file-based systems, ensuring versatility in data handling.
Integrations Supported
Azure Synapse Analytics
Datagaps DataOps Suite
Microsoft Power BI
Snowflake
Tableau
Amazon Redshift
Azure Databricks
Oracle Analytics Cloud
Salesforce
Integrations Supported
Azure Synapse Analytics
Datagaps DataOps Suite
Microsoft Power BI
Snowflake
Tableau
Amazon Redshift
Azure Databricks
Oracle Analytics Cloud
Salesforce
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
Contact us
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
Datagaps
Company Location
United States
Company Website
www.datagaps.com/etl-validator/
Company Facts
Organization Name
Datagaps
Date Founded
2010
Company Location
United States
Company Website
www.datagaps.com/dataops-dataflow/
Categories and Features
ETL
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control
Categories and Features
Data Management
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge