Author here. Just a small explanation: target audience are mostly those who would like to add OLAP to their apps with simple multi-dimensional reporting needs (see trivial hello-world example [1]). This release brings new star/snowflake aggregation browser which can be (roughly) considered to your analytical data as ORM framework is to your transactional data - some magic happens between your code and the database that makes your life easier.

Visualisation is not yet included and will be added in modular form of "presenters" [2]. If anyone with web/JS skills would like to help, he is welcome, as my skills in this area is little bit weak. There is unmaintained and unfinished prototype of JavaScript front-end as well [3]. Flask based example of simple dimension browsing is included in the source [4].

If you need any help with model creation, you encounter any issues, have a suggestion let me know.

[1] https://github.com/Stiivi/cubes/blob/master/examples/hello_w...

[2] https://github.com/Stiivi/cubes/issues/53

[3] https://github.com/stiivi/cubes.js

[4] https://github.com/Stiivi/cubes/tree/master/examples/sandbox...

Interesting idea. Ofcourse, OLAP isn't just about the underlying cubes and dimensions, in the end it's about how the information is being presented to the user. There's a reason why Microsoft is so good at data warehousing, because their product is one of the best, and also extremely feature-rich from the "front end" to the back end.

I haven't encountered a lot of BI nerds who are Pythonistas, but this is a great contribution nonetheless.

The more open source tools we can get that can begin displacing products like Cognos and BO, the better.

Is this going to integrate with the broader python ecosystem? I'm specifically wondering about packages like pyTables, pandas and larry.