The new data terms of Data Lake, Data Reservoir, and Data Swamp have left me with more questions than answers. In this presentation, Karen discusses the types of data anomalies that organizations can run into when they use external data, the wrong datasets for the right reasons and the right datasets for the wrong reasons. She uses her own data to show you the impact of bad design decisions, incomplete testing, and other common mistakes.

These errors in design, oversights and old school, traditional practices can impact the success of your projects, even if you don't use any data lakes.

This session isn't really about data lakes, per se. It's about data quality and project processes.