Dane Są Wszędzie

Dane Są Wszędzie is a measured Polish podcast about the practical life of data. Its center is Business Intelligence and Data Engineering, but the show keeps returning to a broader question: how does data become useful, readable, trusted, and worth building around? Some episodes are solo technical explainers. Others are long, careful conversations with guests. The rhythm stays similar in both formats: define the terms, place the tool inside a workflow, then test the idea against realistic business or organizational use. Power BI appears often, especially around semantic models, Tabular Editor, Power Query, C# automation, measures, Time Intelligence, and the kinds of repetitive development work that invite mistakes. Architecture episodes move from classic relational warehouses into Data Lake and Lakehouse thinking, with raw, silver, and gold layers explained through the problem of preparing data for BI consumption. The show also likes concrete domains. A conversation about Atlas ETF turns external data into questions about vendors, licensing, file delivery, technical constraints, and keeping a data product financially workable. A baseball analytics episode begins by orienting Polish listeners in the sport itself, then follows the data through cameras, biomechanical data, computer vision vendors, JSON, BigQuery, and team analysis workflows. The educational-business episode with Kajo Rudziński looks at what happens when a technical person moves toward teaching, management, and helping analysts grow. The #BI_NGO conversation with Ela Wajdzik gives the show a social-data angle, where visualizations can support organizations while volunteers develop their own skills. Even the challenge episodes stay implementation-minded, using seasonal narrative only as a wrapper for SQL and Power BI tasks inspired by business cases. The tone is calm and generous. It does not flatten technical work into slogans. It gives listeners room to understand why a design choice matters, where a tool helps, and where real data projects become messy.