Lean Launch Data Engineering Projects with Super Type Power

Data is ubiquitous. Many modern software and data analytics applications rely on robust and quality datasets. Data engineering becomes a common pipeline in systems running in start-up and enterprise businesses. Data engineering projects in the past were perceived as a set of programming scripts which were typically in a “build-then-scrap” cycle. As the data analytics applications became parts of the main trends, such projects require a serious planning and development to minimize the overhead of integration and maintenance due to scaling up. In this article, we discuss how to use type systems and formal methods to reduce these overheads.