ETL Validator​

The Most Comprehensive Data Testing Automation Platform.

Flat File Testing, Data Migration Testing, Data Warehouse Testing, Master Data Management (MDM) Testing
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Datagaps ETL Validator Earns Informatica's Seal of Approval

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Key Features

Automate Testing of ETL, Relational, Flat Files, XML, NoSQL, Cloud, and Big Data Sources.

ETL Testing Automation

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

Flat File Testing Capabilities

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.

Data Quality Testing

Provides a Data Model driven interface for defining data rules to verify that the data conforms to standards and range of values.

Data Profile Testing

Compare aggregate data such as counts, sum, distinct counts between source and target instead of comparing large volumes of data.​

Database Metadata Testing

Helps audit changes to the database 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.

Enterprise Collaboration

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

Value Test Case Builder

Has an unique Visual Test Case Builder with drag & drop capabilities and a Query Builder that enables defining tests without manually typing in queries.​

End-to-End Data Testing

Supports comparison of data across heterogeneous platforms including the most popular relational databases, Hadoop, BI (OBIEE), XML and Flat Files.​

Patented ELV Architecture

ETL Validator makes use of Datagaps’ patented ELV Architecture to automate ETL Testing. It supports extraction of test data from multiple sources such as relational databases, XML, Flat Files, BI and Hadoop. The test data is loaded into a workschema (Oracle or PostgreSQL database) so that validations can be run on it. ELV (Extract, Load, Validate) Architecture consists of the following three steps:

  1. Extract test data (and metadata) from heterogeneous data sources.
  2. Load the test data into a workschema (Oracle or PostgreSQL database).
  3. Validate test data by comparing it within the workschema.

Connects to Popular Data Sources

ETL Validator connects to a wide variety of data sources. From time to time, we are constantly adding support for many modern data sources. If you don’t see a data source of yours, please send an email to us with your question.

  • Relational Databases: Oracle, IBM DB2, Microsoft SQL Server, IBM Netezza, HP Vertica, MySQL, PostgreSQL.
  • Flat Files: Delimited Files (eg. CSV), Fixed width Files, XML, Microsoft Excel.
  • Big Data: Hive 2, Hadoop, Cloudera Impala.
  • Business Intelligence: Oracle Business Intelligence (OBIEE).

Wizard Based Test Creation

ETL Validator makes it easy to test most common ETL testing scenarios by providing out-of-the-box support. Comes with an in-built Query Builder.

  • Data Quality Testing: Data Accuracy, Duplicates, Referential Integrity checks.
  • ETL Testing: Source to target data and data profile comparison, Incremental ETL testing.
  • Metadata Testing: Compare metadata across environments, Source to target metadata checks.
  • Business Intelligence Testing: End-to-end testing for BI Reports, Metrics driven testing.

ETL Transformation Testing

Component test case supports testing of ETL transformations by providing a visual test case builder that supports extracting test data from multiple sources in a single test case

  • DB Component: Supports Source Qualifier, Lookup, Sort and Joiner Transformations.
  • Script Component: Supports procedure transformation.
  • Baselining Capability: Target data can be saved as a baseline and used to compare with latest data for regression testing.
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