TestBench Data Extraction

Full recreation of complex environments

Powerful record selection

Data sampling

The most powerful data extraction solution for creating logical data sub-sets while maintaining referential integrity.

Large Test Data Environments slow down testing and make it hard to find the data scenarios you need, and limited disk space on test machines means fewer environments than you would like. 

Intelligent Data Extraction enables you to continue to use production data while focusing on the scenarios you want and need for your testing, while maintaining data integrity. A small, focused sub-set of production data means you can find what you are looking for, testing is accelerated, and, consequently, you now have space for more environments.

Data Extraction Definition

Data Extraction Execution

Intelligent Data Extraction

TestBench analyses the relationship between tables in a data environment to ensure that full referential integrity of the data is maintained when an extract is performed. This ensures a usable, working data environment for testing.

Selection & Sampling

Data selection for an extraction is defined by selection and sampling criteria. While selection is standard, sampling extracts data based on combinations of data values, with two or more data elements being used as the criteria for sampling. Sampling enables the creation of test data environments that are small while ensuring all relevant data scenarios are included.

Want to know more about IBM i Data Extraction and how it could help your business? Why not book a slot with one of our technical advisers.

TestBench IBM i Modules

Solutions to cover every aspect of test data management

Stop copying the entire live database and hone in on the data you really need. Select or sample data with full referential integrity preserved.

Simply decide which fields need to be protected and use a variety of obfuscation methods to protect your data.

Track every insert, update and delete including intervening data states. Create rules so that data failures are flagged to you automatically.

Avoid the painful save/restores and stop attempting to explain bad test results based on poor initial data.

Comparing outputs is a well proven method to verify your test results but it is laborious and prone to error.This unique solution can save hours.

Get under the covers and analyse at a program/module level what happens in the database, APIs, parameters, messages and beyond.

We understand

We understand the challenges associated with data extraction. So why not reach out to one of our advisers and explore the options available.

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