Object Extractor™ for SAP systems

Test Automation data feed

When automating testing as part of a project, or during normal operations, you want to ensure the processes occurring every day on Production will work with the latest changes to the configuration and master data.

By leveraging Object Extractor, you can take all the key characteristics of a process flow and write them periodically to your test automation solution via API. Enabling 'lights out testing'; the owners of the testing can track and see where changes may be breaking Production flows temporarily, and monitor to see that they are being rectified, or step in if not.

It also means the constant building of a historical library of real activity from Production that can be used for larger regression tests in projects simply by picking when data that is suitable would have happened in the live system.

S/4HANA Migration Cockpit loading

Decommissioning SAP^® systems is not something most people want to take on. Many companies will retain their old outdated legacy SAP systems, fearing that they would need the data for auditing or referencing in the future. This becomes very expensive. Maintenance contracts on legacy systems – together with the risk of unsupported hardware failures – result in escalating costs.

The SAP environment is also changing, and there are large incentives to move to S/4HANA^® technology, or to look at SAP SuccessFactors^® to leverage the cloud. Moving to different ERP systems, other than SAP, is another possibility.

AI Learning platforms

AI Training requires as much accurate data as possible. It also needs the semantic meaning of the fields, not simply five-digit codes from a technical table definition.

EPI-USE Labs’ Object Extractor can provide one-off or periodic snapshots of complex SAP data with the real-world meaning of the field contents tagged correctly.

If you're going to S/4HANA via a greenfield migration and you're bringing data from one or more legacy SAP systems, you might be familiar with the templates that are provided for the s four migration cockpit. In these sheets, you need to provide the data based on the specific tables that's come from the source system the columns in order to match what's required for the load process. What we can do with our new Object Extractor capability is actually bring the data from legacy systems in exactly the format you need. So in here, I can go and choose a particular type of data that I want to work with. In this example, I'll choose materials. And then I can enter the selection criteria. So perhaps we don't want to take all of our materials with us. We're going to pick the ones that are still valid. We can use the extended selection to upload a list or we may have, another mechanism to choose. I'm just going to put one star in. So I'll take all the materials that begin with a one. We then have the data groups and this allows us to filter what we want to bring across. So if you're migrating but you're not taking maybe some plants that are no longer active, you can simply exclude those in the selection here. Then in the integration tree, I can pick up related data that is referenced by the materials. So if I only want to bring across classifications and characteristics that are actually used with my materials, I can get them through this process rather than doing a separate extract for them. We can then preview the data and see in here that's two hundred and forty two materials that have been found. We have the ability to run transformation on the data as well as part of the extract process. And then if we come to the execution options, we can see we have a basic JSON format. We've got an XML format. And then I've got this additional s four migration workbench example. We can run-in the foreground or the background. If we are moving, large volumes of data out into CSV files, we can split the work over several background jobs, and they can even be across different servers as well. So I'm going to kick this off now. And it's starting to select the data based on our data model. And it will then extract it into CSV files that are grouped by the table. So all of the object keys will appear in the Mara table, for example. And then in the other tables, some may have entries, some may not. We can see there our run has finished. It took seventeen seconds to extract the data. And I'm going to go grab the file so we can have a look at this. So I'm going to extract that zip file from our run six seven two four. And here we can see all of the tables based on the materials that I selected. So if I, make this a little bit bigger you can see Marcy, Mara, and so on for those two forty two materials. If I go into one of these as an example, we can see in there all of the fields laid out as CSV with quotes around to deal with special characters, and we can then adjust as required and copy and paste this into the S/4 template. We can change the orders. We can exclude fields, anything we need to do to match the format within the template. And if we go back into the extractor, you can see we've got lots of coverage across the different areas of SAP. They're in materials management, sales and distribution, both master data and transactional data. So a really good way to get the data from legacy systems into the format needed for S/4HANA.