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You’ll agree when we say that poring through numbers is tedious at best and mentally exhausting at worst.
And this is where data visualization comes in.
Charts come in and distill data into meaningful insights. And this saves tons of hours, which you can use to relax or execute other tasks. Besides, when creating data stories, you need charts that communicate insights with clarity. Note: it’s the clarity and simplicity of charts that make data stories compelling and irresistible.
It turns out there’re data visualization tools that produce charts that are simple to read and interpret. Yes, you read that right. These tools create charts that complement data stories seamlessly.
Remember, without visualizing data to extract insights, chances of getting buy-in will go down.
In this blog, we’ve rounded up tips and strategies that underscore the importance of data visualization. More so, you’ll also come across tons of good data visualization examples to simplify data storytelling techniques.
So take time and steal these golden data storytelling tips and strategies.
Let’s explore why it’s difficult to decode meaning from raw numbers before we delve right into the importance of data visualization.
So why is data hard to read?
Visual communication appeals to our brains more than texts and numbers.
Tables and spreadsheets play a crucial role during data collection and macro-view analysis. However, the aforementioned is always a scratch on the surface. If you want in-depth analysis, you’ve got to think beyond tables.
And this is where visualization comes in.
Essentially, data visualization is an advanced way of communicating data to the audience. Using tables and spreadsheets to communicate data stories to audiences, such as investors and stockholders, comes at a very high cost. Wait! That’s not all.
Check out the disadvantages of using tables and spreadsheets to create data narratives for audiences:
Keep reading because the blog is loaded with tons of good data visualization examples.
Data visualization helps you to identify trends and patterns in your business data quickly.
Our brain processes visual information, such as charts, 60,000 times faster than poring over spreadsheets and data reports.
Visualization is a quick and easy way to convey insights to a broader audience. Make data visualization a habit in your organization to enjoy the benefits below:
Visualization tools make it amazingly easy for you to extract answers from your data to create compelling stories for investors.
Imagine using the tables and spreadsheets to explain emerging patterns and other significant insights to your audience. How would they respond? Would you get buy-in after presenting the table to them?
Our brains grasp visual content, such as graphs and maps, 60,000 times faster than table reports, as we said earlier.
And this means a compelling data story loaded with easy to interpret charts can empower quicker decision-making.
Bulky data provides unlimited opportunities for businesses to extract actionable insights. Yes, insights that could spell the difference between you and competition.
Visualizing data helps pinpoint relationships and patterns between metrics. Exploring these patterns enables you to save immense resources, such as time, by focusing only on areas that need urgent action.
Data visualization helps you spot errors in the data easily. Working with error-free data validates the accuracy of the insights extracted.
We hope you see the importance of data visualization.
The reason why we visualize data is to create data stories. Remember, poring over numbers in spreadsheets is monotonous, especially if you’re in front of an audience.
So you need to create a compelling story with insights extracted from the raw data. People love stories. Yes, and this is because they appeal to emotions.
To craft a compelling data story, you need an actual story.
It sounds contradictory. Yes, we know.
To create a narrative, start by asking a question or forming a hypothesis. And then, dig into your data to find answers.
Below are some of the questions you need to ask:
Remember, visualization comes before you create a data story.
We hope you’re noting the importance of data visualization, especially in creating data narratives.
Let’s take a look at good data visualization examples below. Keep reading if you intend to take your data storytelling skills to the next level.
Visualization plays a significant role in helping in communicating insights in the energy sector.
Check out a good data visualization example below:
Imagine you’ve been tasked by the Energy Commission of a hypothetical country to analyze their gigantic data. They want to know various details about domestic energy consumption, namely:
The Energy Commission wants a data story to use for the forthcoming launch of their 10-year Plan. We’ve used this example to spotlight the importance of data visualization.
The table below has the sample data we’ll use for the scenario above.
Note: the table below is pretty long to show you the immense power visualization, especially when handling gigantic data sets.
Apologies in advance if you find the table below weirdly long.
| Energy Type | Main Source | Source type | Energy Source | Usage | End-User | Mega
Watt |
| Agricultural waste | Bio-conversion | Solid | Thermal generation | Losses in process | Lost | 5 |
| Agricultural waste | Bio-conversion | Solid | Thermal generation | Electricity grid | Industry | 7.3 |
| Agricultural waste | Bio-conversion | Solid | Thermal generation | Electricity grid | Heating and cooling – commercial | 5.1 |
| Agricultural waste | Bio-conversion | Solid | Thermal generation | Electricity grid | Heating and cooling – homes | 3.7 |
| Agricultural waste | Bio-conversion | Solid | Thermal generation | Electricity grid | Lighting & appliances – commercial | 4.9 |
| Agricultural waste | Bio-conversion | Solid | Thermal generation | Electricity grid | Lighting & appliances – homes | 2 |
| Other waste | Bio-conversion | Solid | Thermal generation | Losses in process | Lost | 7.2 |
| Other waste | Bio-conversion | Solid | Thermal generation | Electricity grid | Industry | 5.4 |
| Other waste | Bio-conversion | Solid | Thermal generation | Electricity grid | Heating and cooling – commercial | 6.7 |
| Other waste | Bio-conversion | Solid | Thermal generation | Electricity grid | Heating and cooling – homes | 4.8 |
| Other waste | Bio-conversion | Solid | Thermal generation | Electricity grid | Lighting & appliances – commercial | 7.4 |
| Other waste | Bio-conversion | Solid | Thermal generation | Electricity grid | Lighting & appliances – homes | 2.5 |
| Marina algae | Bio-conversion | Solid | Thermal generation | Losses in process | Lost | 0.7 |
| Marina algae | Bio-conversion | Solid | Thermal generation | Electricity grid | Industry | 0.5 |
| Marina algae | Bio-conversion | Solid | Thermal generation | Electricity grid | Heating and cooling – commercial | 0.9 |
| Marina algae | Bio-conversion | Solid | Thermal generation | Electricity grid | Heating and cooling – homes | 0.5 |
| Marina algae | Bio-conversion | Solid | Thermal generation | Electricity grid | Lighting & appliances – commercial | 0.8 |
| Marina algae | Bio-conversion | Solid | Thermal generation | Electricity grid | Lighting & appliances – homes | 0.6 |
| Land-based bioenergy | Bio-conversion | Solid | Thermal generation | Losses in process | Lost | 1.3 |
| Land-based bioenergy | Bio-conversion | Solid | Thermal generation | Electricity grid | Industry | 2.5 |
| Land-based bioenergy | Bio-conversion | Solid | Thermal generation | Electricity grid | Heating and cooling – commercial | 3.2 |
| Land-based bioenergy | Bio-conversion | Solid | Thermal generation | Electricity grid | Heating and cooling – homes | 0.7 |
| Land-based bioenergy | Bio-conversion | Solid | Thermal generation | Electricity grid | Lighting & appliances – commercial | 1.4 |
| Land-based bioenergy | Bio-conversion | Solid | Thermal generation | Electricity grid | Lighting & appliances – homes | 0.9 |
| Biomass import | Bio-conversion | Solid | Thermal generation | Losses in process | Lost | 0.4 |
| Biomass import | Bio-conversion | Solid | Thermal generation | Electricity grid | Industry | 0.7 |
| Biomass import | Bio-conversion | Solid | Thermal generation | Electricity grid | Heating and cooling – commercial | 0.8 |
| Biomass import | Bio-conversion | Solid | Thermal generation | Electricity grid | Heating and cooling – homes | 0.3 |
| Biomass import | Bio-conversion | Solid | Thermal generation | Electricity grid | Lighting & appliances – commercial | 0.6 |
| Biomass import | Bio-conversion | Solid | Thermal generation | Electricity grid | Lighting & appliances – homes | 0.2 |
| Nuclear reserves | Nuclear Plant | Solid | Thermal generation | Losses in process | Lost | 50 |
| Nuclear reserves | Nuclear Plant | Solid | Thermal generation | Electricity grid | Industry | 13 |
| Nuclear reserves | Nuclear Plant | Solid | Thermal generation | Electricity grid | Heating and cooling – commercial | 8 |
| Nuclear reserves | Nuclear Plant | Solid | Thermal generation | Electricity grid | Heating and cooling – homes | 6 |
| Nuclear reserves | Nuclear Plant | Solid | Thermal generation | Electricity grid | Lighting & appliances – commercial | 11 |
| Nuclear reserves | Nuclear Plant | Solid | Thermal generation | Electricity grid | Lighting & appliances – homes | 4 |
| Coal reserves | Coal | Solid | Thermal generation | Losses in process | Lost | 4.7 |
| Coal reserves | Coal | Solid | Thermal generation | Electricity grid | Industry | 3.1 |
| Coal reserves | Coal | Solid | Thermal generation | Electricity grid | Heating and cooling – commercial | 4.2 |
| Coal reserves | Coal | Solid | Thermal generation | Electricity grid | Heating and cooling – homes | 0.7 |
| Coal reserves | Coal | Solid | Thermal generation | Electricity grid | Lighting & appliances – commercial | 4.8 |
| Coal reserves | Coal | Solid | Thermal generation | Electricity grid | Lighting & appliances – homes | 0.5 |
| Gas reserves | Natural Gas | Gas | Thermal generation | Losses in process | Lost | 5.1 |
| Gas reserves | Natural Gas | Gas | Thermal generation | Electricity grid | Industry | 8.4 |
| Gas reserves | Natural Gas | Gas | Thermal generation | Electricity grid | Heating and cooling – commercial | 7.9 |
| Gas reserves | Natural Gas | Gas | Thermal generation | Electricity grid | Heating and cooling – homes | 4.8 |
| Gas reserves | Natural Gas | Gas | Thermal generation | Electricity grid | Lighting & appliances – commercial | 7.3 |
| Gas reserves | Natural Gas | Gas | Thermal generation | Electricity grid | Lighting & appliances – homes | 3.5 |
Note the power of visualization. The super-gigantic table with energy data has been distilled into the insightful chart below.
Visualization Source: ChartExpo
So what are the insights?
A huge chunk of the country’s energy comes from nuclear sources (41%).
You can read more about energy flow visualization with Sankey diagram here.
Like in the energy sector, data visualization plays a critical role in the education sector, especially in communicating actionable insights to key stakeholders.
Take a look at a good data visualization example below:
The example you’ll come across will underscore the importance of visualization in this sector.
Imagine you run a school and you want to compare the performance of three teachers, namely:
Essentially, you want to use their score in various key performance indicators: knowledge, punctuality, helpfulness, effectiveness, and delivery for promotion. We’ve used this example to highlight the importance of data visualization.
Let’s use the tabular data below for the scenario above.
| Teacher | Quality | Score |
| Justin | Knowledge | 2.7 |
| Justin | Punctual | 4.6 |
| Justin | Helpful | 3.7 |
| Justin | Effectiveness | 4.9 |
| Justin | Delivery | 3.9 |
| Tim | Knowledge | 3.7 |
| Tim | Punctual | 3.2 |
| Tim | Helpful | 4.9 |
| Tim | Effectiveness | 4.1 |
| Tim | Delivery | 2.8 |
| Grace | Knowledge | 4.7 |
| Grace | Punctual | 4.5 |
| Grace | Helpful | 3.8 |
| Grace | Effectiveness | 2.5 |
| Grace | Delivery | 3.7 |
Check out the insightful chart below. Note how it’s easy to extract valuable insights.
For instance, none of the teachers have a good score for delivery.
Visualization Source: ChartExpo
Note we’ve used ChartExpo to generate the insightful and easy-to-interpret chart above.
Keep reading because we’ll explain how you can get this tool for free in the later sections.
You can use charts to extract insights from survey data as well. Take a look at the good data visualization example below.
Imagine you’ve just conducted a survey in a university. You want to know how the students perceive the university brand in aspects, such as mode of teaching and courses offered. We’ve used this example to spotlight the importance of data visualization.
Let’s use the table below for our scenario.
| Questions | Rating | Count |
| How do you rate the courses taught in your university? | 1 | 130 |
| How do you rate the courses taught in your university? | 2 | 1123 |
| How do you rate the courses taught in your university? | 3 | 1293 |
| How do you rate the courses taught in your university? | 4 | 1.391 |
| How do you rate the courses taught in your university? | 5 | 1339 |
| How do you rate the teaching staff and their teaching method? | 1 | 140 |
| How do you rate the teaching staff and their teaching method? | 2 | 1168 |
| How do you rate the teaching staff and their teaching method? | 3 | 1242 |
| How do you rate the teaching staff and their teaching method? | 4 | 1286 |
| How do you rate the teaching staff and their teaching method? | 5 | 1302 |
| How do you rate the facilities provided by the university? | 1 | 120 |
| How do you rate the facilities provided by the university? | 2 | 1203 |
| How do you rate the facilities provided by the university? | 3 | 1212 |
| How do you rate the facilities provided by the university? | 4 | 1351 |
| How do you rate the facilities provided by the university? | 5 | 1424 |
| How do you rate the variety of food items available in the cafeteria? | 1 | 110 |
| How do you rate the variety of food items available in the cafeteria? | 2 | 985 |
| How do you rate the variety of food items available in the cafeteria? | 3 | 1403 |
| How do you rate the variety of food items available in the cafeteria? | 4 | 1428 |
| How do you rate the variety of food items available in the cafeteria? | 5 | 1510 |
This chart provides in-depth insights into the massive table you’ve just skipped to reach here. Note how colors have been used strategically to create a clear distinction in variable differences.
Visualization Source: ChartExpo
So what are the insights?
Food items available in the cafeteria have the lowest score (2.4/5). Besides, the overall brand perception of the university has (2.5/5).
Note we’ve used ChartExpo to generate the insightful and easy-to-interpret chart below.
Keep reading because you don’t want to miss more tips that underscore the importance of data visualization, especially in healthcare.
Health practitioners will tell you the importance of data visualization without mincing words.
Data visualization is revolutionizing the sector, especially in the decision-making process. Health facilities are increasingly using data models to plan for resource allocation and mitigate losses.
Take a look at the example below.
Imagine a US Governor has tasked you to provide insights into children’s diseases affecting his state. Essentially, the Governor wants to know the prevalent disease affecting children each month of the year for efficient resource allocation.
The main diseases you’ll focus on are listed below:
Let’s use the table below for our scenario.
This example underscores the importance of data visualization in the healthcare sector.
| Months | Chickenpox | Whooping cough | Measles | Rotavirus | Tetanus | Hepatitis B |
| 1 | 168 | 187 | 159 | 51 | 247 | 229 |
| 2 | 66 | 77 | 136 | 199 | 87 | 159 |
| 3 | 81 | 148 | 69 | 101 | 217 | 125 |
| 4 | 144 | 206 | 163 | 121 | 189 | 67 |
| 5 | 46 | 230 | 231 | 149 | 84 | 228 |
| 6 | 162 | 113 | 20 | 183 | 90 | 147 |
| 7 | 33 | 37 | 234 | 95 | 239 | 243 |
| 8 | 12 | 209 | 217 | 105 | 67 | 128 |
| 9 | 144 | 23 | 84 | 224 | 212 | 114 |
| 10 | 157 | 25 | 189 | 13 | 199 | 252 |
| 11 | 28 | 15 | 34 | 100 | 203 | 171 |
| 12 | 190 | 202 | 247 | 183 | 85 | 105 |
The insightful chart below is a good data visualization example. Note how this chart is easy to read and interpret.
Visualization Source: ChartExpo
So what are the insights?
Measles is the leading outbreak among children in the state in May and December.
Chickenpox remained least in August and November. October is least affected by Rotavirus and October is the Month in which maximum hepatitis cases were reported.
Now that you’ve learned about the importance of data visualization: let’s delve into the best tools to use.
Google Sheets is one of the most used tools for visualizing data. And this is because it’s free and easy to use. However, it lacks charts that can make your data story compelling.
This is where the ChartExpo add-on comes in. Use this tool to supercharge your Google Sheets to create irresistible data stories.
This premium visualization tool comes with a 7-day free trial period. Besides, it’s a drag and drop tool you can use to create a compelling narrative using data reports, maps, dashboards, etc.
ChartExpo empowers you to visualize diverse data types, such as sales and marketing data, annual reports, monthly reports, office productivity data, investor slide decks, etc.
The main benefit of ChartExpo is that it produces charts that are easy to read and interpret.
Besides, you don’t need to be skilled in coding or programming. You just need to scroll your mouse to produce incredibly insightful charts that complement your data story seamlessly.
ChartExpo allows you to save charts in the world’s most recognized formats, namely PNG and JPG. You can easily attach your charts to Google Sheets and Excel.
This easy-to-use and highly affordable tool come with 50-plus charts, including Column, Line, Bar, Donut, Area, Scatter Plots, Sankey, NPS, and Sentiment charts, among others.
Data visualization is useful for data monitoring, exploring data structure, detecting outliers and unusual groups, identifying trends and clusters, spotting patterns, and presenting actionable results. There’re tons of good data visualization examples, such as Bar graphs and Sankey, you can use to create irresistible data stories.
Compelling data visualizations allow both analysts and decision-makers to examine gigantic amounts of data for actionable insights quickly. Remember, data on its own is not adequate for a growing business.
Ignore the importance of data visualization, especially in business, at your own risk.
Like we said earlier, data without a chart is pretty voiceless.
The statement above underscores the importance of data visualization in almost all sectors.
If you want to make your data story persuasive, then explore good data visualization examples we’ve rounded up for you. (Please refer back to the blog).
Data is only valid when it provides actionable insights to fuel growth and revenue in businesses.
This blog has tons of golden tips you can leverage to transform your raw data into actionable answers for the decision-making process. We recommend the ChartExpo add-in for Excel because it comes with a plethora of creative and interactive charts that are easy to read and interpret.
With ChartExpo, you have unlimited access to over 50 creative chart templates to ensure you’ve got everything you need to create that irresistible data story.
Sign up today to create data stories that attract instant buy-in from the audience.
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