A 3-day bug hunt on a 3-person team costs up to €7,200 in lost engineering time. This workshop teaches you to prevent that — unit tests, data tests, and integration tests for PySpark and Databricks Lakeflow, including Spark Declarative Pipelines.
You know me already, I'm a big fan of Apache Spark but also of all kinds of patterns. And one of the patterns that nowadays gains in popularity is lakehouse. Most of the time (always?), this pattern is implemented on top of an ACID-compatible file system like Apache Hudi, Apache Iceberg or Delta Lake. But can we do it differently and use another storage, like BigQuery?
