Objective
When manually sharing data between SAP Fieldglass and other ERP systems, you’ll use what’s called an integration "Connector"— essentially, a file which is used to format and process data between the systems. The connector file contains data that aligns with the Access, Master, and/or Transactional data that resides in a client’s instance of SAP Fieldglass.
Play the video to learn how data connector files are used to share data between SAP Fieldglass and other ERP systems.
The CSV file illustrated here represents a completed user upload connector.
| Rows 1-7 | The File Header provides instructions on how Fieldglass should handle the data. These seven rows represent typical file header information. Individual connector files may have additional rows to indicate specific requirements for that connector. |
| Row 1 | Type indicates the type of integration connector; in this case, a User Upload. The names of the SAP Fieldglass default connectors would be reflected here. If a custom connector is used, that connector must appear here as named in the application. |
| Row 2 | Transaction defines how the data will be handled by SAP Fieldglass.
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| Row 3 | Send Notification? determines whether notification of this upload should be sent to other users.
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| Row 4 | Language indicates the language to be used in the file. This should reflect what is appropriate for the company. For example, if the company is based in the U.S., the language should reflect English (United States). If the company is based in Germany, the language should be German (Germany). |
| Row 5 | Number Format determines the number format to be used in the file. The valid number format values are = "#,##9.99 (Example = 1,234,567.99)" "#.##9,99 (Example = 1.234.567,99)" "#'##9.99 (Example = 1'234'567.99)" "# ##9,99 (Example = 1 234 567,99)" |
| Row 6 | Date Format determines the date format to be used in the file. This should reflect what is appropriate for the company. For example, if the company is based in the U.S., the date format should reflect month/day/year. Conversely, in the company is based in Germany, the date should reflect Day/Month/Year. Valid formats are = MM/DD/YYYY DD/MM/YYYY YYYY-MM-DD |
| Row 7 | Comments is an optional field where you can add notes about the upload file. |
| Row 10 | The Header Row identifies the type of information that is contained in the respective columns. The system that the data is being uploaded into then reads and processes the information in the data rows accordingly. |
| Row 11 and down | Data Rows, which are basically every populated row below the header row, contain the actual data that is being uploaded. This is the information that is processed according to the type of data identified in the header row. |
There is a little more to integrations than just downloading and uploading connector files. There are, in fact, different methods of transferring data to and from SAP Fieldglass depending on what activity is taking place.
Two commons methods available for transferring data are Batch and Single Transaction.
A Batch integration allows multiple transactions or records to be moved at a time, at specified intervals.
For example, if Mavis and other hiring managers at WorkingNet complete twenty-five invoices in a given day, the data associated with all twenty-five invoices might be downloaded from SAP Fieldglass and uploaded into WorkingNet’s accounts payable system at the end of each work day.
And there are actually two ways that data can be Batch loaded into or out of SAP Fieldglass: through what’s called a Delta batch or a Full batch.
With a Delta batch, only new data is transferred.
The CSV file that is downloaded from SAP Fieldglass will contain records of items that are new or have changed since the last time the data was downloaded.
So for Nelson, the CSV contains the data of the six new temporary employees that were procured since the last time data was uploaded into WorkingNet’s human resource system.
On the other hand, the data can also be transferred as a Full batch.
This means that SAP Fieldglass would download data for all of WorkingNet’s temporary workers, regardless of when they were added to SAP Fieldglass.
WorkingNet’s HR Information System, then, is responsible for parsing out all of the data that is new since the last upload.
One thing to consider about Batch processing is that the processing behaviors are different for uploads and downloads.
A Delta batch download is considered dependent.
That is, SAP Fieldglass compares the download against the previous download to determine what’s changed.
Thus, the download is dependent upon the last download for a comparison basis.
A Full batch download, on the other hand, is independent.
Since SAP Fieldglass downloads all records, it doesn’t process any changes.
The client system—like Patricia’s ID system—compares and processes the data.
Conversely, with uploads, the opposite is true. The Delta batch upload is independent, and SAP Fieldglass assumes that the data from the client system is all new and processes it accordingly.
A Full batch upload is dependent, so SAP Fieldglass compares the file against the previous upload to determine what has changed.
A Single Transaction integration is triggered by an event or action and transfers the data immediately from SAP Fieldglass to the other system.
It’s a "just-in-time" integration and it still uses a Connector file to move the information, but the download is triggered by a particular action and contains only the information for that change.
So if Mavis approves a time sheet submitted by Joe resulting in a new invoice, the information contained in that invoice can be downloaded from SAP Fieldglass as soon as Mavis approves the time sheet (with auto-invoice enabled), which can then be uploaded into WorkingNet’s AP system.
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