Making Sense of Data: What Every Beginner Should Know

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Making Sense of Data: What Every Beginner Should Know

We live in a world full of data. From the messages we send to the videos we watch, we’re creating data all the time. But just having data isn’t enough—we need to know how to use it. That’s where data analysts come in.

This blog breaks down some of the basic ideas about data, how it’s organized, and why it matters—especially if you’re starting out in data analytics.

🧱 What Is Structured vs Unstructured Data?

Imagine a neat, well-organized spreadsheet. That’s structured data—things like sales numbers, customer lists, or dates, stored in rows and columns.

Now think of a voice recording, a photo, or a social media post. That’s unstructured data—it's messy and doesn't fit into a nice table. While harder to analyze, it often holds valuable information.

Most of the data in the world today is unstructured, but you’ll usually work with structured data as an analyst.

📊 Types of Data You’ll Work With

There are two big categories:

  • Quantitative data – Numbers and measurements (like age, height, or income).

  • Qualitative data – Descriptions and categories (like someone’s favorite color or type of music).

Some data is countable (discrete), like how many people attended a concert. Some is measurable (continuous), like how long the concert lasted.

🔎 Where Does Data Come From?

Data can be:

  • Primary – You collect it yourself (e.g., through a survey).

  • Secondary – Collected by someone else (like government stats).

  • Internal – Comes from your own company (e.g., sales reports).

  • External – Comes from outside (e.g., market research you bought).

Knowing where your data comes from helps you understand how reliable and useful it is.

🧭 What’s a Data Model?

Making Sense of Data: What Every Beginner Should Know


Think of a data model as a map that shows how data is connected. It helps people understand where to find information and how it fits together.

There are three levels:

  1. Conceptual – A big-picture view.

  2. Logical – How different pieces of data relate.

  3. Physical – The actual details like table names and column types.

You probably won’t create data models as a beginner, but it’s good to know how they help keep everything organized.

🔐 Why Ethics and Privacy Matter

Just because we can collect data doesn’t mean we always should. It’s important to respect people’s privacy and use data fairly. Unfair or biased data can lead to wrong results and poor decisions.

🧠 Bringing It All Together

Working with data isn’t just about numbers—it’s about asking good questions, finding the right data, organizing it properly, and using it to tell a story. Whether you're tracking traffic or helping hospitals understand patient feedback, the goal is the same: use data to make better decisions.

If you're starting your journey in data analytics, take it step by step. Learn the basics, practice often, and remember—every great analysis starts with understanding the data you're working with.

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