BI Industrialisation
when I'm asked what is the most undervalued feature of the library, then my answer is clear. The REST API and mstrio-py. Here you can read why
​Strateg(P)ython
​(Micro)Strategy devOps processes are still very manual and mouse driven. The existing automatisation tools are well accepted in the developer community, but proprietary, limited from feature and will be depreicated sooner or later. Python & the REST API is much more powerfull, but there is a learning curve to use and run Python applications. However, running Python on top of MSTR, we should re-think our best pratices​​​​​​​​
Schema Monitor​​
Logical tables and their mappings are the interface to the backend. Using Python we can read out the mappings to attributes & facts. We can enrich this with PA data and than we know, which columns are mapped, which are used and this for dev, test and production. Futher we can do dependencie searches...​​​​
Power BI on Top of MSTR​​​
The question, if MSTR and Power BI are comopetitors is on going. They are competitors, if you see then as visualization tools. Personally I like them to work in coexistance. MSTR is the access layer to complex modelt data. It ensures a unfied business logic aand security. PBI is perfect to add / combine multiple data source or conect to data models up to medium level of complexity​​
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​​​​AI for devOps
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AI can be a great help for devlopers, but we need to think about how we integrate this into our processes. I like the idea to use AI for spelling checks or ensure that nobody is using pie charts