XDM

Row Level Processing

Setup test cases easily

A short software development cycle is essential to meet today’s IT objectives. Current software development methods, such as Agile, require the reliable provisioning of test data. That‘s why it is necessary to establish a well-defined, automated procedure for the acquisition and migration of data from production to test, QA, development, and training environments.

Most applications store information in relational databases. Complete copies of a production environment, also known as clones, are often used for pre-production staging. These clones maintain the relational integrity of the source data. While these full copies are suitable for regression, user acceptance and performance testing, they may burden developers in earlier stages of testing with data volume and concerns over the exposure of sensitive information. Developers mostly require a small subset of the data, however, this subset must be made up of cohesive test cases. The major challenge is to extract the required rows from multiple tables in a way that is dependable and repeatable, while at the same time being easy to use. This extraction process must consider both the dependencies defined in the DBMS and those that are embedded in the application logic. You can store information about application-level dependencies inside XDM. This enables it to find related data from parent and child tables and allows you to copy consistent test cases into the target system. Once the start values for the test case (customer name, contract number, etc…) are set, XDM automatically detects which rows from dependent tables must be copied. XDM excels at automating this selection and at replicating test cases, which saves you time, money, and manpower. The copy process itself is divided into multiple repeatable steps and can be easily integrated into a scheduler.

Data Modification
XDM is able to modify data while copying it. Personal, financial or medical data and other sensitive information can be changed before it is written into the target environment. XDM Modification comes with standard methods to modify and mix data, but the user can also add new masking algorithms if desired. This helps to implement a masking process that meets data protection regulations. XDM is also able to handle structural differences between the source and target environment with ease. It is not unusual for a data model to evolve during a development process. If a new field has been introduced, XDM can generate values for it while it copies data. XDM can also convert the source data into a new format automatically if data types have changed in the target. If the changes to a data model are more complex, it is possible to integrate scripts into the copy process that make the required adjustments.

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Web Portal
Testers can request a test data refresh using a web portal. This eliminates the need for a client installation on the testers‘ machines. At the same time, it ensures that only copy processes that have been predefined by DBAs can be executed by end users.

DDL
XDM can replicate the DDL of the environment and create completely new environments. The integrated structure comparison feature can also modify the existing target structures, and create missing objects. Since the copy process is rule based, it does not need to be modified if the structures of the source or target objects change.

Conclusion
XDM Row Level Processing is a user friendly tool for extracting cohesive data from a database system. It allows users to easily populate test, development, and other environments. XDM saves resources while shortening the development cycle through efficient test case provisioning. Sophisticated masking mechanisms help you build copy processes that are compliant with data privacy regulations.