The Benefits of Data Visualization For Data Analysis

Basty’s Notebook

Hi, everyone! My name is Basty, and I’m a data scientist and educator from Metro Manila. If there’s something I value so much, that is education. Education has allowed me to not only dive into the amazing world of code and data, but also to encourage and inspire others to do the same. Read more about me here.

Outside of work and school, I love playing video games like Valorant and League of Legends. I also love listening to Broadway musicals (HAMILTON, DEH, TICK TICK BOOM ALL THE WAY!). Lastly, I LOVE watching Friends, New Girl, HIMYM, and The Big Bang Theory.

Now, let’s take a look at my notebook!

April 2023 Notebook entry

Whenever we are trying to tell a story or watch a movie, we always strive for something that captures the audience’s attention. Not only that, but we also want to have a connection on a more personal level to make it meaningful to us and to everyone else. In today’s data-driven world, being able to effectively communicate information and stories through visuals is more important than ever. With data visualization, we enable viewers to quickly understand what we are trying to communicate. So in this blog post, we’ll explore the importance of data visualization—and as a bonus, we’ll talk about data storytelling too. Let’s get started! 

First, what is Data Visualization anyway?

Let’s first start by defining what data visualization is. Data visualization is the art and science of presenting data in a visual format, such as charts, graphs, and maps, to help people understand and make sense of complex information. The main goal of data visualization is to communicate information clearly and effectively so that patterns, trends, and insights can be easily identified even by non-technical people. 

Data visualization has a long history, dating back to ancient times when maps and charts were used to navigate and record information. In the modern era, data visualization has become increasingly important with the explosion of data in fields like science, business, and technology. Today, data visualization is used in a wide range of fields—from journalism to scientific research, and from business intelligence to public policy. With the rise of big data and the increasing availability of tools and technologies for data analysis, data visualization has become an essential tool for making sense of complex data and communicating insights to others.

Here’s an analogy, think of a scenario where you try to explain a story to a friend, but they can’t quite get what you’re talking about. So then you try to create an imaginary visual in the air with your finger to better explain what you’re talking about. In the end, the story was the data, and the imaginary drawing was the visualization. 

The Benefits of Data Visualization

There are many benefits to using data visualization to communicate information. I’d say the most obvious benefit is that it allows people to quickly and easily understand complex information, when done correctly. Instead of having to sit through pages of numbers and tables, data visualization presents information in a way that is immediately understandable.

In addition to making information easier to understand, data visualization can also help to uncover insights and patterns that might not be that obvious just by looking at raw data. By visualizing data, it is often possible to identify trends and relationships that are often unnoticed.

Another benefit of data visualization, and perhaps a bit technical, is that it can help to identify outliers and anomalies in data. By visualizing data in a graph or chart, it is often easy to spot data points that are outside the norm. This method of spotting outliers can be particularly useful for detecting fraud, errors, or other issues in data.

Different Types of Graphs and When to Use Them

So we’ve talked about the what and why, now let’s talk about the how and when. There are many different types of graphs and visualizations, and choosing the right one depends on the type of data you have and the insights you want to communicate. Here are some of the most common types of graphs that you can use regardless of the tool and when to use them:

Bar charts - Bar charts are used to compare values across categories. They are particularly useful for showing changes over time or comparing data across different groups. For example, you want to see if Category A performed better than Categories B, C, and D.

Line charts - Line charts are used to show trends over time. They are particularly useful for visualizing changes in data over time. For example, you want to see the increase in inflation overtime.

Scatter plots - Scatter plots are used to show the relationship between two variables. They are particularly useful for identifying correlations and trends in data. For example, you want to see if there is a positive relationship between hours of sleep and math test scores.

Heat maps - Heat maps are used to show the density of data in a particular area. They are particularly useful for visualizing data that is related to geography or population. For example, you want to determine which location had the most covid cases.

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Tips for Effective Data Visualization

Even though I gave a list of graphs, it doesn’t mean you can just go and use them. There are some tips that you should take into mind when deciding on how to present your data. Now while data visualization can be a powerful tool for communicating complex information, it’s also important to use it effectively. Here are some tips for creating effective data visualizations:

1. Choose the right type of visualization for your data - Different types of data require different types of visualizations. Make sure to choose a visualization that is appropriate for your data.
2. Keep it simple - Avoid cluttering your visualization with unnecessary elements. Keep it simple and focused on the key insights you want to communicate.
3. Use color wisely - Color can be a powerful tool for drawing attention to key points in your visualization. However, be careful not to use too many colors, as this can be distracting. For example, red can mean negative and green is positive.
4. Provide context - Make sure to provide context for your visualization, so that viewers can understand the meaning and significance of the data. Without context, we’re often left with our own biases.

The Power of a Story

There’s a lot more to data visualization than just creating graphs. The deciding factor on whether a graph is effective or not, comes down to the way it is being communicated, which is what we call data storytelling. It’s the process of creating a narrative around data and using it to communicate insights and tell a story. It involves using data visualization to create a compelling and engaging story that helps to communicate complex information to different stakeholders.

Storytelling is an effective way to engage audiences not just in films, but also to support data-driven decision-making, and communicate insights in a way that is easy to understand. By using data visualization to create a narrative, we can create a more engaging and memorable experience that connects with our audience on an emotional level. 

We first started by defining data visualization as something a bit technical in nature with its benefits and different types of graphs. However, the most important lesson that I wish to impart to you is that you view this art as a means of communication. A means to communicate a narrative by telling a story that is driven by data insights. By using different types of visualizations, we can create a narrative that takes the viewer on a journey of discovery—revealing insights and patterns in the data. 

Never stop learning!