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.
You will learn:
- About the types of data quality errors that happen in real life
- How to mitigate these errors in SQL Server and other data technologies
- See real-life examples of the speaker's data quality experiences