> For the complete documentation index, see [llms.txt](https://docs.videc.de/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.videc.de/june5-3.7/en/datenquellenunterstuetzung-und-einbindung/june5-batch-connector/anwendungsfall.md).

# Use Case

To illustrate the operation, the data flow is demonstrated using a company called "The Beer Company" (abbreviated as TBC). The Beer Company produces various types of beer (standard, light, and dark) at multiple locations (Berlin and Paris). TBC has two customers A and B. TBC now grants both customers access to production data via the JUNE5 Batch Connector.

Each production batch is assigned a unique batch ID. The batch ID consists of three parts here.

Part 1 = Location such as Berlin (BER) and Paris (CDG)\
Part 2 = Product identification, e.g., B200, B201...

Part 3 = Alphanumeric random value consisting of three characters: e.g., ABC, DEF, X5H, I9W ...

![](/files/lQkRk5hzl2ZnLSb7qnwI)

The batches are then shipped to the customer by freight after production. Customer (A and B) is now interested in the production data. TBC provides each customer with a VM where the customer gains insight into the production data. TBC must ensure the following:

* Customer A sees only the production data for the batches delivered to Customer A.
* Customer B sees only the production data for the batches delivered to Customer B.
* Customer A must never see Customer B's data.
* Customer B must never see Customer A's data.

![](/files/91SiwqmAtRZwFveMLJes)

### Source Data:

The source data is JUNE5 stations (here BER and CDG). At these stations, TBC can analyze local production with JUNE5.

### Target Data:

The target data is the data of customers A and B. They only see the batches intended for them.


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