In the data transition validation tool context, the "Project Global Data" step is part of the initial project setup within data transition validation. This step defines the core, cross-functional parameters, and key information that will apply throughout your entire data transition validation project.
Why is it important?
- Consistency: By entering global data once, you ensure that it is used as a reference throughout all validation steps in your project.
- Efficiency: It saves time because you don’t have to repeatedly enter the same information for different objects or test cases.
- Accuracy: Having one place for core data reduces the risk of errors and miscommunication in your tests and reports.
In every SAP data transition validation project, there are some data entries, like Company Code, Profit Center, or Cost Center, that are commonly required in most, if not all, test specifications. Instead of repeatedly entering these details for every single report or test case, the data transition validation tool allows you to specify this common (global) data once you use the "Project Global Data" step.
This step is necessary as the data is relevant to the entire project. You can use it to define the split parameters in the test specifications.
How Does It Work?
- Project Global Data is defined at the beginning of your data transition validation project.
- Some Global Data fields (like Company Code or Profit Center) come as defaults when the test specifications (pre-delivered content) are imported to the project.
- However, if your process needs additional common data (for example, a new Cost Center), you can easily create new Global Data entries using the Create button.
- When it is set, this Global Data is available in all your test specification reports, so you don’t have to re-enter or maintain this data in multiple places.
Example scenario
If you need to validate a large dataset with a million customer records spanning 10 different company codes, you could leverage the Split parameter to manage smaller chunks of data. Rather than extracting all 1 million records at once for all company codes simultaneously, it's beneficial to divide the records into smaller portions by intelligently defining Project Global Data and applying it to the Split parameter.
In this scenario, instead of extracting records based on a range of company codes, users can specify each Company Code as individual line items in the Project Global Data definition (using the Equal operator). This approach allows the validation tool to process the data in 10 parallel batches, extracting smaller chunks for each Company Code.
In the following exercise, you will learn how to maintain Project Global Data, namely the Company Code.
It is worth mentioning that the Project Global Data is used as the split parameter in the "Define Test Specification" step, as you will discover in the next lesson.
It is also important to understand that, rather than extracting millions of records simultaneously, dividing them into smaller portions is beneficial by intelligently defining the Project Global Data.
Example Scenario
Suppose you need to validate a large dataset with a million customer records spanning over 10 different company codes, instead of extracting records based on a range of company codes. In that case, users can specify each Company Code as an individual line item in the Project Global Data definition (using the Equal operator). This approach allows the validation tool to process the data in 10 parallel batches, extracting smaller chunks of data for each Company Code.
Summary
After this lesson, you can use the Project Global Data step to maintain common data for the whole data transition validation project.