Datagaps ETL Validator

ETL Validator - Automate your Data Reconciliation & ETL/ELT testing, DataOps ETL Validator is the most comprehensive Data Validation & ETL Testing Automation Tool

Benefits of End-to-End Data & ETL Validation using ETL Validator

Comprehensive ETL/ELT validation tool to automate the testing of data migration and data warehouse projects with easy to use Low-code, No-code Component based test creation and Drag & Drop User Interface. Data Validation automation for Relational, Flat Files, XML, NoSQL, Cloud, and Big Data Sources.

Connects to over 40+ Data Sources

Supports access to all legacy and modern data sources such as Snowflake, Synapse and file based data sources such as AWS S3, ADLS and GCS.

No-code/Low-code based ETL transformation testing

Supports the ability to transform data using built-in processor components or use Python for more complex needs.

AI-powered Data Quality assessment

Compare billions of records between your source and target to validate your ETL project. Leverage AI for data quality testing - embrace data observability.

ETL Testing Automation

Comes with an inbuilt ETL engine capable of extracting & comparing billions of records from multiple data sources while executing test cases in parallel.

Visual Test Case Builder

Has a unique visual test case builder with drag & drop capabilities and a query builder that enables defining tests without manually typing in queries

Data Quality Testing

Provides built-in data quality test for common data quality checks with the ability to create complex data quality rules from scratch or by using our Query Builder to define rules to verify that the data conforms to your quality standards.

Data Profile Testing

Compare aggregate data such as counts, sums, patterns, and distinct counts of any data asset. Profiles can be compared to highlight aggregate deltas between a source and target to decide if further testing is required. ?Our unique AI capabilities can be enabled to view historical trends to find anomalies through observability.?

DB Metadata Testing

Helps audit changes to the metadata – data types, lengths, indexes. Simplifies comparison of database schema across environments.?

Baselining Capabilities

This powerful feature can be used for testing of incremental ETL, slowly changing dimensions and ETL regression testing.

End-to-End Data Testing

Supports data comparison across heterogeneous platforms, including the most popular relational databases, Snowflake, XML, JSON and other file or DB structures.

Flat File Testing

Define rules for automatically validating data in each column in the incoming file. Has a builtin file watcher that automatically detects new files and kicks off tests.

Enterprise Collaboration

Capability to assemble and schedule test plans. Email notification, web reporting and ALM integration enables sharing of test results.