Data is a language

A language is a structured system of communication used by humans to convey thoughts, ideas, and emotions. It allows us to express complex concepts, share information, and understand one another. Language involves symbols, grammar, and rules that help us form and interpret meaning. It is a tool for connecting people and articulating the world around us.

Data can be thought of as a language because it serves a similar purpose—it conveys meaning and information about events, activities, and statuses. Like a spoken or written language, data consists of symbols (numbers, text, categories) that, when organized in meaningful ways, provide insights and tell stories. For instance, data allows us to describe financial transactions, employee activities, supply chain processes, or school metrics. By connecting different data points, we create a narrative that helps us understand and make decisions about the world. Data, much like language, helps translate the complexity of reality into understandable terms, making it a powerful tool for communication and analysis.

Data captures events, activities, and status. In finance, it captures the activities of earning and spending. In HR, it captures details of recruitment, promotions, manpower costs, and staff age. In supply chain management, data captures activities such as orders and sales of goods. In schools, it captures the popularity of subjects and attendance. In kindergartens, it captures the attendance of children and their arrival times. By connecting two or more columns of data, you can describe activities and events that are happening, revealing valuable insights.

Imagine being able to communicate without words but through numbers, patterns, and visual insights. Data is very much like a language—a powerful means to convey messages, describe situations, and even predict outcomes. Just as we use words to create stories, we use data to tell the story behind numbers, trends, and relationships. Learning to understand data means learning to speak this language fluently, especially in today’s world where data-driven decisions are at the core of everything from business operations to personal finance.

At its core, data is a collection of symbols, values, or measurements that might seem meaningless on their own. But when we start to combine them, their real power unfolds. For example, a simple invoice number doesn’t tell us much by itself. However, when paired with an amount, it tells us the value of the transaction. Add in a list of items, and we begin to understand what’s inside that transaction—a story starts to form. The magic of data is in these relationships, much like how words, when structured together, convey deeper meaning.

If you’re new to this language, mastering it might feel daunting—similar to learning a new spoken language. But like any language, you start with the basics and slowly build up your fluency. For data, the basics involve understanding different types of data (like numerical, categorical, or text), learning how to organize and visualize information, and finally, interpreting what that information tells you. When you start to combine these skills, you’re effectively learning to “read” data.

Step One: Learn to Listen

Just as the first step to mastering a spoken language is listening, the first step to mastering data is understanding how to observe it. Begin by getting comfortable with looking at data in different forms—tables, spreadsheets, charts. Get curious. Ask questions like, “What story is this data trying to tell me?” or “What does this trend mean?” This initial curiosity will help you get comfortable with data and make sense of its patterns.

Step Two: Learn the Grammar—Basic Tools and Techniques

Once you’ve familiarized yourself with observing data, it’s time to learn the grammar of the language. This involves basic data tools and techniques. Learning tools like Excel, Google Sheets, or data visualization platforms like Power BI or Tableau is akin to learning verbs and sentence structure. You need these tools to organize, manipulate, and visualize data so that its meaning becomes clear. Think of charts and graphs as the visual equivalent of expressions and gestures—they make the meaning of data more relatable and easy to understand.

Step Three: Start Speaking—Telling Stories with Data

Once you’ve gathered your data and learned the tools to interpret it, it’s time to start creating your own messages. This is where storytelling comes into play. The ability to communicate insights from data is what turns numbers into knowledge and understanding. Ask yourself: What do I want to communicate? What does this data reveal? When you can answer these questions clearly and share them with others, you’re effectively speaking the language of data.

Mastering data takes practice, much like learning any other language. The more you work with data—organizing it, analyzing it, and visualizing it—the more fluent you will become. And like any language, data fluency can open doors: allowing you to make informed decisions, understand complex situations, and communicate effectively with others.

Ready to Begin Your Journey?

Start by diving into a small dataset that interests you—maybe your own monthly expenses, or a favorite hobby’s statistics. Practice observing, organizing, and visualizing that data, and see the story unfold. Every journey starts with small steps, and soon you’ll be fluent in the language of data—a skill that will empower you to understand the world in a deeper way.