What is the overall flow of the process for integrating a data source into IAM, with its decision points?
Check whether existing IAM data covers the request; if not, decide between a quantitative and a qualitative extension. The quantitative path goes straight to agreement and connection; the qualitative path first checks scope, data model, data-protection basis and whether a source exists.
* The full decision flow: two exits at the top, a short standardised quantitative path, a longer qualitative path. *
Read it as a series of questions:
- Can the request be covered by data the IAM already holds? If yes, there is nothing to integrate: the application is simply connected through the separate application connection process (Applikations-Anschluss-Prozess) and this process ends.
- If not, what kind of extension is it?
- Quantitative (same kind of data, new source): find the person responsible for the data source, conclude a data delivery agreement, set up the technical connection. Done. This path is meant to be a standardised routine with templates and automation.
- Qualitative (a new kind of data): continue with step 3.
- Is extending the IAM scope worthwhile? If no, the need is solved outside IAM. If yes, extend the business data model.
- Is there a data-protection basis for processing it? If missing, create one, then continue.
- Does a data source for it exist? If not, build a new data source.
- Either way, the path ends like the quantitative one: find the person responsible, conclude the data delivery agreement, set up the technical connection.
The design idea: the cheap, frequent case (another source of the same data) is short and routine, while the rare, expensive case (new kinds of data in the central identity store) passes through every gate where it can be stopped.
Go deeper:
Identity and access management (Wikipedia) — the wider discipline, including provisioning and de-provisioning of accounts across applications.- Master data management (Wikipedia) — the general discipline of keeping one consistent version of shared business data across many systems.