We are exploring answers for questions such as: How do you know that the data you are looking at is the data you think you are looking at? How fast can a domain expert, but very likely a technical layperson, get understandable answers to his/her questions if there are so many ways and places where your data is stored? How you make sure that your reports will not be disrupted when you change any of the internal systems to a different kind?
Data Brewery is a knowledge sharing and sometimes lightly hacking community around data warehousing and its application. Anyone is welcome, whether you have small data or big data, whether your data is open or not, whether you are non-profit organisation or a corporation.
The topics are mostly about master data management, data quality, conceptual data modelling, metadata and ETL. We bring together data users (not necessarily with technical background) and data engineers to share their stories, ask questions and come up with solutions.
From time-to-time we will also be talking about or lightly hacking on data warehousing libraries and applications. We are putting together a collection of open-source tools that anyone would be able to use to help them with their data problems. Language of our choice is Python.