Know Your Data

As we embark on our journey as data analysts, our work truly begins with understanding the data itself. Where does it come from? What kind of data are we dealing with? Is it structured, unstructured, or something in between? Was it entered manually or generated by machines? These details might seem minor, but they profoundly shape how we explore, clean, and interpret the data.

Know the backstory

Every dataset has a backstory around how it was collected. It might be clean and well-organized, or it might be imperfect and inconsistent. Maybe it was collected through a web form, a sensor, or a survey. Each of these origins shapes what the data can tell us, and what it can’t.

Consider planning a trip. You wouldn’t just jump in the car and start driving without knowing where you’re headed. In the same way, we need to understand the landscape of our data before we can navigate it with confidence.

Now, let’s examine the types of data we might work with. Each one has its own structure, and recognizing these differences helps us choose the right tools and approaches.

Data types

Not all data looks the same. Some datasets are highly organized and easy to explore. Others are more complex, less structured, and require a bit more work to make sense of. Knowing how to recognize different types of data is a foundational skill; it informs how we clean, analyze, and draw meaningful insights from it. ...