ETL Validator

ETL Validator, developed by Datagaps, is an ETL testing automation tool designed to streamline the validation process for data migration and data warehouse projects. The vendor states that ETL Validator caters to professionals and industries such as business analysts, data engineers, data architects, data quality managers, data warehouse managers, IT managers, and sectors including financial services, healthcare, retail, and manufacturing.

Key Features

ETL Testing Automation: ETL Validator includes a built-in ETL engine capable of extracting and comparing large volumes of records from multiple data sources, allowing for parallel execution of test cases. According to the vendor, it automates the ETL/ELT validation process, potentially saving time and effort for data engineers and testers.

Visual Test Case Builder: ETL Validator provides a visual test case builder with drag and drop capabilities, simplifying the creation of test cases. The vendor states that it eliminates the need for manual query typing, reducing the reliance on manual coding.

Data Quality Testing: ETL Validator offers a data model-driven interface for defining data rules, aiming to ensure data conformity to quality standards and a range of values. The vendor claims that it enables accurate data validation, duplicate identification, and referential integrity checks during data movement.

Data Profile Testing: ETL Validator allows for the comparison of aggregate data such as counts, sum, and distinct counts between source and target. According to the vendor, this feature focuses on identifying discrepancies in overall data characteristics, providing insights into data profiles.

DB Metadata Testing: ETL Validator simplifies the comparison of database schema across different environments, ensuring consistency and accuracy of metadata such as data types, lengths, and indexes. The vendor highlights that it facilitates the audit of metadata changes, ensuring data infrastructure integrity.

Baselining Capabilities: ETL Validator offers baselining capabilities for testing incremental ETL, slowly changing dimensions, and ETL regression testing. The vendor claims that it enables the comparison of target data against saved baselines, identifying changes or discrepancies and ensuring the reliability of the ETL process.

End-to-End Data Testing: ETL Validator supports the comparison of data across heterogeneous platforms, including popular relational databases, Hadoop, XML, and Flat Files. According to the vendor, it enables comprehensive end-to-end data testing, ensuring data consistency and accuracy throughout the data pipeline.

Flat File Testing: ETL Validator allows users to define rules for automatically validating data in each column of incoming files, ensuring data quality and accuracy. The vendor emphasizes that the built-in file watcher detects new files and initiates tests, simplifying the testing of data in flat files.

Enterprise Collaboration: ETL Validator provides capabilities for assembling and scheduling test plans, along with email notifications, web reporting, and ALM integration. The vendor states that it facilitates collaboration among team members and stakeholders involved in the ETL testing process.

ETL Transformation Testing: ETL Validator supports the testing of ETL transformations through its component test case feature. According to the vendor, it provides a visual test case builder that supports extracting test data from multiple sources in a single test case, accommodating various transformation types such as Source Qualifier, Lookup, Sort, Joiner, and Procedure transformations.