Data visualization:
what you need to know

A beginner’s guide to everything you need to know about
data visualization.

Learn about data visualization

Our world runs on data, now more than ever. The growth of the internet means that 90% of the world's data has been created in the last decade, dwarfing data we had access to previously. But this data just takes up space unless you know how to use it — to glean important insights, create data stories, and use data as evidence to inform your decisions. Since not everyone considers themself a “numbers person,” finding the best way to communicate detailed trends and analyses are key.

No matter what sector you’re in, from marketing and sales to healthcare and technology, data visualization is going to be one of the most important tools in your toolbox. Here’s an overview of what data visualization is, how to use it, and what it can do for you.

What is data visualization?

Data visualization is the process of converting data, like numbers over time or across geographic locations, into an easy-to-understand visual format that highlights insights and makes them easier to understand and communicate. This could be as simple as a chart that shows sales over time, a map that color-codes states by virus case prevalence, or a word cloud that shows which words employees used most often in the latest company survey.

Why is data visualization important?

Data visualization is critical to telling your data’s story. While raw data may contain the information about topics like annual growth rate or customer's average age, it makes it very challenging to see insights that can be lost in a sea of numbers. But when data is in visual form, more insights about trends and patterns become readily apparent. It’s much easier to spot a neglected outlier, an unexpected trend, or an area where something’s amiss. And it’s not just helpful for you, it takes the way you communicate to others to the next level.

Benefits of using data visualizations

Learning visually is in our DNA. Although psychologists and education researchers have debunked the concept of “visual learners,” it’s long established that the human brain is excellent at understanding visual patterns. Some even say it’s what makes our brains so human.

There are many reasons why using data visualizations can benefit you, your teams, your clients, your customers — basically anyone you’re ever discussing data with — such as:

Accessibility of data

Data visualizations make data insights more accessible to a wider audience. Not everyone has the skill or interest required to dig deep into the numbers and pull out relevant trends, but anyone can look at a chart or graph and understand how different elements compare, or contrast, giving them an instant understanding of what the visualization seeks to convey.

Determine what's significant

The more data you have access to, the harder it can be to find the most significant insights. Rigorous statistical analyses can spit out the answers, but that requires knowing exactly what question to ask — and a statistician, data analyst, or data scientist. Data visualizations, on the other hand, can help leaders and nontechnical business people determine what information is significant at a glance, so they can quickly identify areas requiring further evaluation or action.

Create an interactive experience

The earliest data visualizations were, essentially, really cool maps and graphs. Today, modern data visualization tools take these static creations to the next level, allowing users to get an even better understanding of their data. Visualizations might come as an interactive chart that lets you drill down into interesting insights. And with embedded interactive analytics experiences, users can dive into the data and create visualizations on their own right within existing tools or apps — no coding skills required.

Share data and its story with others

Not everyone knows their way around a table of raw data. Luckily, visualizations make it easy to present data insights to any audience. Even when raw data reveals important information like a key performance indicator, visualizing that same information in context tells a broader story that everyone can comprehend.

Understand the big picture

Data visualizations give context to your numbers. They can reveal patterns in complex data that would otherwise be hard to understand, and allow you and your audience a better grasp of the insights and knowledge of the big picture.

Identify emerging trends

Using data visualizations to identify emerging trends might be one of its most classic uses. For instance, when data is plotted over time, it’s simple to see what’s going up and what’s going down, how often numbers are fluctuating, and where the peaks and valleys are. You might get a better sense of growth, identify lulls that need attention, or find spikes in KPIs that deserve a closer look.

Get ahead of blockers and bottlenecks

A blocker is anything that derails or delays your efforts. Data visualizations can help identify blockers, like bottlenecks, before they happen. For instance, you might find that production numbers are high up until a certain point in the process, which helps to identify what the specific bottleneck is in order to correct it.

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Data visualization and big data

The more our datasets grow in size, the more challenging it becomes to understand them. Excel spreadsheets have evolved into data platforms, analysts have become engineers — and data visualization has become absolutely vital for sharing insights across teams, management, customers, and clients. As big data becomes more prevalent for organizations, the need for new tools to wrangle it are more important than ever. Data visualizations for big data requires tools that can handle more complex data, compute all that data, and quickly render visualizations in ways that are different from smaller datasets.

Additionally, as data gets bigger and bigger, there's greater risk of sprawl with traditional data visualization tools. These tools were built for desktop users, meaning people either download sections of data to visualize or summaries of that data. In both cases, the power and value of massive amounts of data is lost. But it’s a necessity to be able to fully visualize big data—the bigger the dataset, in theory, the more there is to learn from it.

Data visualization and AI

Luckily for us, artificial intelligence has given our abilities to create data visualizations a major boost. As data volumes explode, AI helps find insights that we might not have known to look for, while data visualization helps present them in a format that’s digestible for yourself and others. AI can also help determine what type of visualization is useful to convey an insight in the first place, even making suggestions within a visualization for further exploration.

Types of data visualizations

For some data, all you need is a bar chart like the ones you drew by hand in middle school to get the picture. But for other data, there’s so much more to convey that something simple won’t do the trick. Luckily, you won’t need graph paper today to make tons of different types of data visualizations, such as:

Column chart

Stacked column chart

Bar chart

Stacked bar chart

Line chart

Pie chart

Area chart

Stacked area chart

Scatter chart

Bubble chart

Pareto chart

Waterfall chart

Heatmap chart

Line column chart

Line stacked column chart

Funnel chart

Geo area chart

Geo bubble chart

Geo heatmap chart

Pivot chart

Sankey chart

Radar chart

Spiderweb chart

Candle stick chart

Examples of data visualizations in use

Data visualizations help people understand their users, readers, customers, clients, patients, students, and more. It shows how your company’s KPIs are changing over time, and identifies strengths and weaknesses that leadership can use for effective decision making. Here are just a few examples of who might use data visualizations to make their job easier:

Data visualizations for marketing analytics

In the marketing department of retail Company X, Lorraine knows website traffic is highly correlated with sales, so she keeps an eye on website analytics like unique users and total pageviews. After visualizing page views over multiple years, she notices a strange surge each May. Further investigation reveals an unexpected popularity of X’s products as gifts for Mother’s Day, which she shares with her colleagues. The following year, the team ramps up advertising in advance of Mother’s Day, quadrupling sales for that month.

Data visualizations for IT operations

In the IT department of Company Y, Cecilia is fed up with the company servers—they’re not often utilized to their fullest, but when they are, they crash. She digs into the records of server usage across time, and it immediately becomes clear that the problem occurs roughly at the end of every quarter. She next plots server usage against company sales, and learns the spikes in usage correlate with booms in online sales. Digging deeper, she learns the company holds a clearance sale at the end of every quarter. Company Y switches server providers to one that allows month-to-month changes in demand, and the company saves big on server costs.

Data visualizations for sales analytics

In the sales department of healthcare Company Z, Miki hopes to identify groups of people currently under-represented by Z who may be currently dissatisfied with their health insurance coverage. His company has recently teamed up with an agency who conducted a large survey of Americans and provided Z with a boatload of data on people’s experiences with and preferences regarding their health insurance. He’s not sure where to start, and lets the AI interface of his modern analytics cloud recommend trends for him. The AI instantly hones in on newly-retired, younger baby boomers who have recently lost their employer-sponsored healthcare and don’t know where to look next. Miki adjusts his sales tactics to be more personalized to this group, and today they’re a mainstay in the customer base for Company Z.

Tips for utilizing data visualizations

Some uses for data visualizations might seem obvious, but to fully reap the benefits, a little extra effort to learn all the ins and outs can go a long way. Here are some tips for how to use data visualizations to their fullest potential.

Explore types of data visualizations

Considering the sheer number of available data visualizations can seem overwhelming, but it needn't be. With a little experimentation — and the help of AI — you can get the hang of what types of data will benefit from what types of visualizations. Paying attention to the visualizations of others can give you a sense of what’s prevalent in your industry, and tip you off to some of the best — and worst — data visualization practices of your colleagues and peers.

The type of visualization you choose to use can impact how the data is understood, so it’s important to take the choice seriously. But remember: Data visualization can be an art, if you want it to be. Enjoy it!

Determine your audience and intent

The number one rule of successful communication, be it data presented in visual form or something else entirely, is to know your audience. If you’re exploring data for your own benefit, you’re free to stick with whatever works for you. But if you’re sharing insights with someone else, it’s vital to consider what you want them to learn, what their background knowledge and assumptions might be, and what they’re most interested in. This will determine how you present your data.

For example, if you’re presenting a complex, technical subject to an audience full of members of the general public, you’ll likely distill it down into a simple chart. But if you’re presenting that same information to experts on that subject, a greater level of detail may be more appropriate. Of course, sometimes experts appreciate simplicity, too. Use your best judgment.

Create easily shareable data visualizations

Sometimes you’re on your own when it comes to creating and sharing data visualizations. But some new technologies make your visualizations as shareable and discoverable among your colleagues as your last social media post was to your online peers. This type of system maximizes efficiency within organizations, making sure no employee reinvents the wheel when another employee has already found the answer. Sometimes the best way forward isn’t creating your own data visualization, but finding a great one that someone at your company already shared.

Choose the right tools

In the end, the key to effective data visualization is to have the right tools at hand. What’s best will likely be unique to each organization, so be sure to do your research to find the right tool for your and your company’s needs. Luckily, there are great options out there like ThoughtSpot that make data visualization accessible to anyone, not just data scientists and analysts.

Are you ready to do more with your data?

Thoughtspot offers a Live Analytics experience, which means you don’t just stop at a data visualization, you can endlessly explore your data. Drill down, zoom out, separate the wheat from the chaff, and get insights you didn’t know you were looking for. If you don’t feel like digging, robust AI capabilities help you make the most of your data, whether that’s finding the right visualization to start with, or suggesting additional insights to dig into deeper. And once you or your colleagues have made a great data visualization, it’ll be shareable and discoverable by your whole team.

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