Where do we begin with data?
As you progress through this book, you will learn how to use these technologies together to clean and prepare your data for performant data visualization. However, before diving into some examples and learning how to actually carry out these transformations, it’s important you pick up a few best practices on what you should consider before getting started.
Key elements to consider here are what is meant when we say data quality, why it is important (outside of the obvious reasons), who’s responsible for it, and how to plan for this data preparation.
