Design a survey about actual data transmission

[RaphaelKomander]

A seamless data transmission works if the actual to be exchanged data of business transactions can be transmitted between different Connectors. Those affected data fields only represent a subset of the underlying proprietary data models. Passing towards an approach where these data will become a result of an investigation, serves the base for challenging the standard model (configuration).

According to Andreas @ag737 (IESE Fraunhofer), it is better to remodel aggregates than the underlying data models. In consideration of the framework evolution process, the underlying models have to stay backward compatible. Therefrom the need for a sustainable preselection of data fields arises for the first release.

Investigate actual data of frequent business transactions

• Narrow the apps that can make use of the domain models
  • Start with that 10 SaaS Solutions already analyzed
• Ask experienced ISVs that integrate these apps - often OnPremise provider
  • Realized business app integrations
  • Data that are actually transmitted
• Ask SMEs about actual data of frequent business transactions
  • Business apps in use
  • Given roles of user permissions

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• Excel KW6 (asap) - based on 10 SaaS Analysis

Survey structure (dynamic)

- Example of data quality - precision
- Business transactions* with data exchange of Addresses & Products (items)
- Prioritization*: mandatory / nice to have / not needed
- Data fields (update frequency, data privacy, mandatory field) > Grouping

[RaphaelKomander]

This survey design is intended to collect information about actual data transmissions. The Interviewee extends the form by typing in new data points. He will be asked to group them per domain.

This is a result of collaboration with Fraunhofer - @ag737 Andreas.

[RaphaelKomander]

In addition to sending us a corresponding list of data sets, interviewees can submit their data points via this Google form

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How can we resolve this?

• Set the context language to English
• Send a collected data point after another - script