Know Your Data

As data analysts, our work begins with understanding the data itself. Where does it come from? What kind of data are we dealing with—structured, unstructured, or something in between? Was it entered manually or generated by machines? These details might seem minor, but they shape how we explore, clean, and interpret the data. Before we get into building charts or start sharing insights, we need that upfront clarity. It’s what helps us avoid wrong assumptions, ask smarter questions, and deliver insights others can act on with confidence.

Know the backstory

Every dataset has a backstory. 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. ...