Straten Consulting’s Hyper Data Suite (HDS) enables its users to create interfaces to extract and load data into SAP ERP without programming.
Most SAP customers are continuously looking for new solutions that give them an edge over competitors. While this quest might never end, Straten Consulting’s Hyper Data Extractor (HDE) will make data provisioning a fast and effortless process. Finally, SAP customers can truly free their data and the need to create new and costly interfaces has come to an end.
HDE provides a streamlined, informative interface to simplify data extracts from SAP in ways never seen before. The interface fully guides the user through the process of defining, selecting and creating data for a data extract. In addition, it also includes advanced features to schedule data extracts as desired. It’s data output options are equally powerful and allow the creation of text, Excel and XML files.
On a high level, HDE splits the creation of a data extract into three different processes:
The dataset definition process requires the user to provide a transaction code, report, function module or table to automatically identify all related tables. In a next step, the user can select all desired tables and fields as shown in the following screenshot. Advanced users also have an option to add any missing tables. Once the selection process is completed, the program automatically builds relationships between all selected tables. If a table cannot be linked, the user has an option to link it manually with guidance from the application. In a final step, the user can replace standard field labels with custom field labels.
Throughout the entire process, HDE is pursuing a high standard for its user interface by assisting the user with visual progress indicators, easy to use select options and an impressive real-time data preview.
It should be noted that datasets defined during the data definition process can be shared with other users.
Once the data definition process is completed, the user needs to go through the scheduling process. The scheduling process can be simple (one-time extract) or more complex (scheduled extract). For both scenarios, the user can assign static or dynamic (e.g. date fields) values to user defined selection fields for data selection.
Since the scheduling process stores the data extract in the database, the extract process can create output files for the same extract in various formats (Excel, Text and XML) to various destinations (application server, local desktop and RFC destination). Furthermore, the extract process allows the user to customize the extract content (column headers, key field alignment and others).
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