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You’ll agree when we say parsing through raw data is incredibly time-intensive and mentally exhausting.
More so, if your data is gigantic, it can easily overwhelm you.
This is why you need graphs and charts to distill signals from noise in your data.
Luckily, there’s a ton of freemium data visualization tools, such as Google Sheets and Excel you can leverage to get the most out of your data.
Besides, there’re third-party tools you can use to supercharge your Excel with Add-in and Google Sheets with Add-on. Yes, you read that right.
Why?
These free data visualization tools (Excel and Google Sheets) produce pretty basic charts that need multiple tweaking before becoming final products.
This blog will walk you through the intricacies of creating a compelling data story using graphs and charts. We’ll use different examples of data graphs, such as
1-Pareto
2-Double Bar Charts
3- CSAT Score Survey (NPS Detail) Chart
4-Ordered Square
5-Radar
Keep reading if you intend to take your spreadsheet game to the All-Star level.
Before we delve right into the easy-to-follow examples to get you started with data visualization: let’s explore why charts are significant.
Until recent years, making sense of the raw data in huge databases was too daunting and time-intensive for us.
But, recent developments, such as artificial intelligence (AI), are increasingly helping us crunch gigantic data sets on an unprecedented scale. Remember, when leveraged fully, data helps businesses to personalize marketing communication.
The five examples of data graphs (we’ll mention later) are part of the visualization designs you need to get started with data stories.
As we said, it’s daunting to extract patterns and trends in raw data. You can only alleviate the situation above by leveraging charts and graphs fully to extract high-level insights.
Tables and spreadsheets play a crucial role in 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 examples of data graphs (which we’ll cover in later sections) come in.
Essentially, graphs and charts are an advanced way of communicating data to the audience. Using tables and spreadsheets to communicate data stories to audiences, such as investors and shareholders, can be very costly, primarily if your business’ survival hinges on their buy-in.
So what’s the best tool to use to create graphs and charts that are incredibly easy to read and understand?
The tool we recommend to our readers is ChartExpo. Our recommendation is based on the following factors:
Well, ChartExpo comes jam-packed with features that all tick on our checklist above. Firstly, this data visualization tool comes with an ultra-friendly user interface (UI). Secondly, accessing this tool is FREE for 7-days. More so, it produces charts that are remarkably insightful, easy to read, and stunning.
ChartExpo’s library has over 50-plus charts to ensure your data story is compelling.
Note: ChartExpo is for anyone who needs to create data visualizations for various purposes. For example, you can use this intuitive tool to create charts for blogs, dashboards, reports, presentations, proposals, social media, and more.
Remember, ChartExpo has all the five examples of data graphs (which form the core of this blog).
The screenshot (below) is proof that ChartExpo is more loaded than the next best data visualization tool in the market. Its expansive library is subdivided into 6 major chart categories, namely:
Let’s dive into the heart of the blog: the top 5 examples of data graphs you need to test with your data stories.
Note: we’ll start with 4 examples in Google ads, and finish with the final example in Excel, at the climax. So that you can full idea to use this library in both tools. Keep reading because you don’t want to miss this.
A Pareto Chart provides actionable insights needed for setting priorities.
Besides, it’s a form of a vertical Bar Chart that categorizes variables in your data in order (from the highest to the lowest) relative to a dimension, such as frequency, cost, or time.
This diagram is based on the (80/20) principle, stating that 20% of the causal factors result in 80% of the effect.
Let’s look at an example below to get you started with Pareto Charts in your data stories.
Imagine you own a fashion brand store. Your inventory is stocked with the following products:
This is where a Pareto Chart comes in as one of the examples of data graphs. Let’s use the table below for our scenario.
| Products | Items Returned |
| Polo Shirts | 2 |
| Hoodies | 9 |
| Jackets | 20 |
| Trousers | 18 |
| Shorts | 4 |
| Joggers | 12 |
| Coats | 75 |
| Jeans | 68 |
| Suits | 11 |
| T-Shirts | 6 |
If you use ChartExpo to visualize the data set above, your resulting diagram should look like this (below). In the later sections, you’ll learn how to visualize your data using our hidden gem (ChartExpo).
Visualization Source: ChartExpo
Do you find the chart above easy to read? You can read more about Pareto Chart here.
Putting data side-by-side in a chart is an essential visual cue for our brains to derive comparison insights. And this is the core principle behind the Double Bar Chart.
This diagram comprises Stacked and Adjacent Bars to provide you with a seamless experience in extracting comparison insights across multiple categories.
A Double Bar Diagram is one of the charts you need to identify trends and proportions in your data. Why? Traditional, column-shaped graphs can easily miss such insights.
Let’s take a look at an example (below) to get you started with Double Bar Charts.
Imagine you want to know to assess the performance of TWO key metrics, such as sales value and growth at the same time. Which chart would you go for?
Yes, you guessed right. You need a Double Bar Chart (one of the examples of data graphs) to get started with complex tasks (such as the above).
A Double Bar Visualization is suitable for our scenario because it will show both numerical and percentage values.
Let’s use the table below for our scenario.
| Quartiles | Sales | Growth |
| Q1-19 | 7000 | 4.2 |
| Q2-19 | 7606 | 7.6 |
| Q3-19 | 7895 | 3.8 |
| Q4-19 | 8242 | 4.4 |
| Q1-20 | 8327 | 0.7 |
| Q2-20 | 8768 | 5.3 |
| Q3-20 | 9337 | 6.5 |
| Q4-20 | 9589 | 2.7 |
If you use ChartExpo to visualize the dataset above, your resulting diagram should look like this (below).
Visualization Source: ChartExpo
From the chart above, you can easily match the sales revenue with the corresponding growth. For instance, when you earn $7,606, the company grows by a whopping 7.6%.
The NPS Diagram is one of the graphs and charts used to gauge customer loyalty, satisfaction, and enthusiasm towards a brand.
Its score is calculated by asking customers to rate various key variables that make up a brand.
For instance, on a scale of 0 to 10, how likely are you to recommend this product to a friend or colleague?
The overall NPS Scores can help your brand improve critical areas, such as service, customer support, delivery, which promote loyalty. Using an NPS Score Chart (one of the examples of data graphs), you can quickly develop growth strategies using your existing customer base.
By identifying the customers who love your brand offerings the most, you can quickly turn passive fans (friends and relatives) into active promoters.
An NPS Score Diagram is one of the examples of data graphs that seasoned professionals use to visualize their survey data.
Let’s look at an example (below) to get you started with NPS Score Charts.
Imagine you run a start-up that deals with software as a service (SaaS) products. You want to know the level of loyalty in your existing customer base.
Let’s assume you’ve already gathered your customers’ sentiments and opinions via a feedback collection system. Let’s use the table below for our scenario.
| Question | Rating | Count |
| How likely is it that you would recommend this software to a friend or colleague? | 0 | 215 |
| How likely is it that you would recommend this software to a friend or colleague? | 1 | 129 |
| How likely is it that you would recommend this software to a friend or colleague? | 2 | 43 |
| How likely is it that you would recommend this software to a friend or colleague? | 3 | 86 |
| How likely is it that you would recommend this software to a friend or colleague? | 4 | 172 |
| How likely is it that you would recommend this software to a friend or colleague? | 5 | 258 |
| How likely is it that you would recommend this software to a friend or colleague? | 6 | 430 |
| How likely is it that you would recommend this software to a friend or colleague? | 7 | 302 |
| How likely is it that you would recommend this software to a friend or colleague? | 8 | 860 |
| How likely is it that you would recommend this software to a friend or colleague? | 9 | 745 |
| How likely is it that you would recommend this software to a friend or colleague? | 10 | 966 |
Your resulting diagram should look like this (below), if you use ChartExpo to visualize the data set.
Visualization Source: ChartExpo
The aggregate NPS Score is 9. The number of promoters (customers spreading the brand through word of mouth) is a whopping 41%. And this means the brand’s traction is incredibly remarkable.
So how is NPS Score calculated?
Respondents are grouped as follows:
Subtracting of Detractors from Promoters yields the Net Promoter Score (NPS). And this score ranges from -100 (every customer is a Detractor) to +100 (every customer is a Promoter).
Check out the formula of calculating Net Promoter Score below:
NPS Score = % of Promoters — % of Detractors
An NPS Score Chart is one of the examples of data graphs that are incredibly easy to read and interpret.
So how can you install ChartExpo (in both Excel and Google Sheets) and get started with data storytelling using assorted graphs and charts?
The Ordered Square Diagram is one of the graphs and charts that are amazingly easy to interpret, even for non-technical audiences.
Imagine you’ve been tasked to visualize the US government budget for the 2020 financial year. You want a chart that’s stunning and insightful at the same time.
This is where an Ordered Square Chart comes in.
Let’s use the tabular data below to get started with this chart.
| Departments | Spending |
| Revenue and Customs | 49 |
| Cabinet Office | 13 |
| Justice | 12 |
| Digital, Culture, Media, and Sport | 15 |
| Work and Pensions | 180 |
| Health and Social Care | 163 |
| Defense | 57 |
| Business, Energy and Industrial Strategy | 89 |
| Local Government | 24 |
| Transport | 16 |
| Education | 98 |
You must be thinking how did you we created the previous charts? Steps to follow is almost same for every chart. Let’s see the steps in detail for this chart and then you will find how you can install this add-on in Google Sheets. For now, just assume you have this add-on already installed.
Visualization Source: ChartExpo
Charts are incomplete without titles.
Yes, you read that right.
You need a title to give your graphs and charts solid context. ChartExpo gives you unlimited freedom to add extra details, such as title and legend that help your target audience understand data stories better.
Visualization Source: ChartExpo
There are two methods to installing the ChartExpo add-on for Google Sheets.
The second method: Download ChartExpo directly from the Google Sheets App.
Like we said earlier, the two remaining examples of data graphs will be covered using ChartExpo Excel add-in. Let’s dive in.
To get started with ChartExpo for Excel add-in, follow the simple and easy steps below.
A Radar Chart is one of the examples of data graphs that are incredibly easy to interpret. You can use this chart to create data stories that are compelling to your target audience (or readers).
To get you going with the Radar Chart, we’ll use an easy-to-follow example (below).
Let’s use the tabular data (below) to get you started with this chart.
| Teacher | Quality | Score |
| Justin | Knowledge | 2.7 |
| Justin | Punctual | 4.6 |
| Justin | Helpful | 3.7 |
| Justin | Effectiveness | 4.9 |
| Justin | Delivery | 3.9 |
| Tin | Knowledge | 3.7 |
| Tin | Punctual | 3.2 |
| Tin | Helpful | 4.9 |
| Tin | Effectiveness | 4.1 |
| Tin | Delivery | 2.8 |
| Grace | Knowledge | 4.7 |
| Grace | Punctual | 4.5 |
| Grace | Helpful | 3.8 |
| Grace | Effectiveness | 2.5 |
| Grace | Delivery | 3.7 |
A data chart is a diagram you can use to distill insights from raw data. There are multiple charts and graphs you can use to get the most out of your data.
Data graphs are increasingly penetrating almost all the sectors of the economy, including arts and entertainment.
There are multiple examples of data graphs you can use to visualize your data for insights basic three are used as line, bar and pie graph.
Use Bar Graphs to compare critical metrics in your business data or track performance changes over time.
If your goal is to measure the change over time, Bar Graphs are the go-to diagrams. These charts are among the examples of data graphs that are remarkably easy to interpret.
Like we said earlier, parsing through raw data in spreadsheets and tables is time-intensive and overwhelming in some instances.
It doesn’t have to be like this.
Do you want to get the most out of your data?
Look no further. Explore the top 5 examples of data graphs we’ve rounded up for you. (Please refer back to the blog).
We recommend our readers to use ChartExpo because it comes pre-loaded with over 50 charts and graphs that are easy to read and interpret.
With ChartExpo, you have unlimited access to stunning and insightful chart templates you need to get started with data stories.
Sign up today to get your data stories going with incredibly easy-to-read and interpret charts.
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