In modern fast-moving world, data is being produced at a scale not imaginable just couple of years ago. Therefore, traditional data warehousing techniques are often not applicable to real-world Big Data scenarios. In this session, I will first describe Lambda architecture, aimed to facilitate both batch- and stream-based data processing. Then, I will discuss some complexities and drawbacks of Lambda – and how those can be overcome by utilizing Kappa architecture. Both approaches will be demonstrated using Azure native services and Databricks.