Introduction

Hey there! In today’s digital age, we face a challenge: how to make sense of the overwhelming amount of data around us. But fear not! We have a secret weapon called information visualization that can help us navigate through this data maze. In this blog post, we’ll explore the fascinating world of information visualization and how it helps us understand complex data. Ready? Let’s dive in!

Understanding Information Visualization

Visualizing from an Early Age

Did you ever notice how we start visualizing data from a young age? It’s true! From learning our ABCs to recognizing words, our brains are wired to process visual information. Remember playing with globes or treasure maps as a kid? They helped us understand the world and navigate through exciting adventures. Those early experiences laid the foundation for our ability to visualize and make sense of information.

The Role of Schemas

Do you know what Schemas are? If not, it might help to look up. They’re mental frameworks that help us organize and understand information. Well, it turns out that schemas are like visual libraries in our minds. The more concepts we learn, the more visualizations we have to draw upon. It’s like having a rich collection of images and patterns stored in our memory. These visual references enable us to grasp new visualizations and gain deeper insights.

The Power of Information Visualization

Converting Data into Information and Knowledge

Now, let’s talk about the magic that happens when data transforms into something meaningful. Raw data is like scattered puzzle pieces—it doesn’t make sense until we put them together. By organizing data into structured formats, such as tables or charts, we turn it into information. And when we start asking questions and drawing insights from that information, we enter the realm of knowledge. It’s like solving a puzzle and discovering the bigger picture.

Context and Comprehension

Data, consisting of isolated numbers, lacks meaning without context. Consider an example: there are 500 students in an institute. But this is merely a data point. To transform this data into meaningful information, we need structure. For instance, we can create a table with student details like name, age, gender, origin, stream, date of joining, and score. By asking the right questions—how many male and female students are there? Where do they come from? How old are they?—we can extract valuable insights.

Once we structure the data, it becomes information. But we can take it even further to knowledge. Drawing inferences from the data, we can identify patterns and ratios, such as a 2:1 male-to-female ratio or 50% more students in engineering than in design. Visualizations are another way to make data easier to comprehend. By representing the data visually, we can showcase typical age groups or streams of the 500 students. Combining visuals with text enhances data memorability.

Information visualization enables us to derive maximum value from random data points and condense it into actionable insights. However, context remains crucial. Understanding the desired data and the relationships between different data points is essential for effective visualization.

Google Maps has become an indispensable tool for most of us. We rely on maps, especially when navigating unfamiliar places. When we use maps, we often find ourselves asking a series of common questions:

• “Where are we?” We need to know our current location to orient ourselves.
• “Where is the place we are looking for?” We seek the destination’s precise location on the map.
• “How far is it by cab?” We want to estimate the distance and travel time by taxi.
• “Are there any alternate routes?” We explore different paths to reach our destination.
• “What’s the traffic like?” We check for congestion or any potential delays.
• “How far is it by public transport?” We consider public transportation options.
• “What places of interest are along the way?” We look for restaurants, malls, and other attractions.
• Google Maps even provides specific information, such as nearby restaurants and amenities.

With just a simple data visualization, Google Maps helps us in countless ways. It provides the answers to these questions and serves as a reliable companion during our journeys.

Data Comparison and Analysis

One of the superpowers of visualizations is their ability to help us compare and analyze data. By representing information visually, we can easily spot trends, patterns, and outliers. Whether we’re comparing sales figures, evaluating performance, or examining market trends, visualizations empower us to make data-driven decisions. They’re like magnifying glasses that reveal hidden insights and guide us towards the best course of action.

Visualizing the Qualitative

Sometimes, it’s not about the exact numbers—it’s about the impact or significance of data. Visualizations allow us to capture the qualitative aspects of information. For example, a simple gauge indicating a car running out of fuel is enough to prompt us to refuel. It’s not about the precise amount of fuel left; it’s about the effect of that quantity. Visualizations help us focus on the essence of data, making it more actionable and relevant.

Simplifying Complex Processes

We all remember the diagram of evaporation. Looking at the diagram, simplified the understanding of how water changes form and moves through the system. A visual helped in conceptually understanding a process. Similarly there are many other diagrams that help us understand complex processes.

Whether it’s a flowchart, a wireframe, or a diagram, visualizations break down complexity into manageable pieces.

Universal Visual Language

Visualizations speak a universal language that transcends barriers. From airports to road signs, standardized visual symbols help us communicate and navigate our surroundings, regardless of language or culture. They bridge gaps, ensure clarity, and enable efficient communication. Visualizations are like global ambassadors, bringing people together through a shared understanding.

How to Design Effective Information Visualization?

Defining Objectives and Audience

When creating visualizations, it’s important to define our objectives and understand our audience. For e.g. if you are trying to visualize data or information regarding traffic that comes to your site you will have the following questions:

• How many users come to your site everyday?
• What are the sources of the traffic?
• Which regions do they come from?
• Which pages do they see the most?
• How many people bought your product?
• What time of the day do you get the most traffic?
• Are there any users on my site right now and on which page?

We spoke about how just having data does not help. Even with an objective pure data cannot be of any use. It has to be put under some sort of structure to work further on it. For instance in the example of the institute we did not have an objective but without structure we could not even understand data or work further on it. So we decided on a simplistic structure of listing details of each student based on age, gender, stream, their address etc.

Based on an objective we could now look at this data better.

Data presentation is dependent on who your audience is

• Whom are you presenting this data to?
• What do they want from this?
• How much time do they have to look at it?
• Summary level vs details
• Does it answer all their questions?

Google analytics is by far the best tool i have used for website analytics. It does not assume that you are an expert on data management or analysis. Hence it presents information both in tabular and visual format to help you understand the summary level information and also give detailed data. The graphs are easy to understand and chosen based on data set in question. The same is also available on a mobile app where one can quickly look at website data on the go and get a sense of the important events happening on the site. It covers every possible data set that the user may require. They categorise data based on relevance for e.g. Audience, Acquisition, Behavior, Conversion etc.

Selecting the Right Visual Representation

Choosing the right visual representation is like selecting the perfect tool for the job. Bar charts, line graphs, pie charts—each has its strengths and suits different types of data. We want to present our data in the most effective and engaging way possible. It’s like telling a story using the right medium—painting vivid pictures with data.

Viewing data over a period of time gives us a sense of trends. For example, scoring in cricket, we consume data via visualisations of multiple types which helps understand the performance and various trends. Runs, balls, overs, wickets, run rate, personal best scores and a ton more. Some data is point in time while other is a trend. Some visualisations are comparisons while others, analysis.

The Power of Colors

Colors add life and meaning to visualizations. They help us convey emotions, highlight important information, and create visual hierarchies. However, it’s important to choose colors wisely, considering cultural and contextual factors. Colors can be like a universal language, speaking to our senses and evoking specific responses. They’re the brushstrokes that make our visualizations come alive.

For e.g Subway Maps

• They are simplified versions of routes from point A to B.
• They may not represent the actual layout of the city but they simplify that layout.
• They are designed both for locals and tourists and people with reading disabilities as well.
• You can count stations and stops from one point to the other
• You know where to change the trains from.
• You can see the shortest route
• Colors symbolise different lines. This is probably the most important element of the entire visualisation. People just follow the color to find their route.

Intelligent Data Visualization

Imagine having a team of data experts working behind the scenes, uncovering insights and making sense of vast amounts of data. Intelligent data visualization leverages advanced technologies like artificial intelligence to analyze and present data in real-time. It’s like having a personal data assistant, providing valuable insights and helping us make informed decisions. The future of data is here, and it’s smarter than ever.

Google gives us content based on interest. It is analyzing browsing patterns, time spent on content pieces and many more parameters to give you the content that you are most likely to engage with.

This a derivative of data analysis and parameters defined over a period of time by looking at data. Since it is difficult for humans to look at every minute piece of data. Smart and Intelligent data visualisations help in identifying most relevant pieces of information and derive insights from it. This data is also changing in real time based on new preferences getting added to the larger ecosystem. That’s the power of Big Data!

Conclusion

And there you have it—the world of information visualization at your fingertips. We’ve explored how visualizations help us understand complex data, make informed decisions, and unlock insights that would otherwise remain hidden. From simplifying complexity to bridging communication gaps, visualizations are our trusted allies in the data-driven world.

Whether you are looking to cut down costs, explore new opportunities, improve sales etc. practicing data visualization techniques will give you the answers you are looking for.