How about working with poorly designed schemas? I work with SQL-Server as well, dealing with legacy data designed around imperative t-sql programming. Our 'BI-Solution', SSRS, crawls on pretty simple queries, where 'hacks' need to be done, joining on same table, all kinds of dirty tricks...
I don't know... I honestly feel like 'BI-Solutions' are a poor-persons Python if you are doing anything more than simple dashboards. Something that can be done in 2 lines of code in a Notebook requires endless fiddling in an IDE, to produce something not easily reproducible.
Aside, I've no experience with Tableau or Power-BI, just know that Crystal Reports and SSRS which are pretty painful.
it's hard dealing with legacy stuff. One alternative I can propose - pitch your management and go get yourself a separate and latest SQL instance just for analytics.
Easiest solution you can do is to install SQL Server Developer version which is free.
cherry pick what your need and ETL your data out of legacy systems into your warehouse and run something like tableau/looker/powerbi on top and you will be amazed how effective you can be
Agreed, but again, I ETL my data into a warehouse, as a developer (not a BI person), I'm reaching for spark, flink, or whatever to roll my analytics, and python/flask/d3 for building web dashboards.
Then, once you have 'insight' into your Data, you can easily 'do' something with it without the limitations of a tiered product.
I don't know... I honestly feel like 'BI-Solutions' are a poor-persons Python if you are doing anything more than simple dashboards. Something that can be done in 2 lines of code in a Notebook requires endless fiddling in an IDE, to produce something not easily reproducible.
Aside, I've no experience with Tableau or Power-BI, just know that Crystal Reports and SSRS which are pretty painful.