Approximately 328.77 million terabytes of data are created daily. While companies collect tons of data and don't know what to do next, others are trying to turn the data into insights, make important decisions and grow their business quickly.
More and more data pours into your business every second and from many sources. However, reading and trying to understand data is super boring and inefficient. If data is not figured out in the right way, you might make the wrong decisions, then hurt your business. That's why you should put the data to its effective use and unveil its power to your business’s growth!
A great story, in general, is a narrative that captivates and interests its audience. In addition, it has a great influence on their feelings and thoughts. When talking about storytelling with data visualization, it helps effectively communicate insights, patterns, or trends found in data. Moreover, it combines the power of storytelling with the analysis of data to deliver a compelling message or help make data-driven decisions.
If you are not an expert or skillful data analyst, it's kind of intimidating to implement storytelling with data. Don't worry! This blog post will explore some of the tips for using data visualization in storytelling. We also round up examples and data visualization tools that improve your data communication. Let’s dive into it!
Storytelling with data visualization is a narrative using data to effectively communicate insights, patterns, or trends to audiences. Above all, it involves presenting data in a compelling and meaningful way, using storytelling techniques to engage, educate, and persuade the audiences.
Some might think that presenting beautiful charts and presentations will help quickly attract audiences. However, it's not just that!
The purpose of data visualization storytelling is to present raw data or statistics and focuses on crafting a cohesive and persuasive narrative that resonates with the audience. There are three key aspects of data visualization storytelling:
When using data to convey a story, it is important to choose the relevant data that supports the narrative. To produce actionable insights, the data must be accurate, reliable, and properly analyzed. To find patterns or trends, one might use statistical analysis, data mining, or other analytical techniques.
In data visualization storytelling, visualizations serve as the main medium of communication. They translate raw data into interpretable and visually appealing representations, which makes it easier for the audience to comprehend the information. Data Visualizations feature charts, graphs, maps, diagrams, or any other type of visual representation that best fits the data and the narrative.
Storytelling with data visualization follows a narrative structure, typically consisting of a beginning, middle, and end. It starts by outlining the situation, issue, or query being addressed. The data analysis is followed by the presentation of insights and a buildup to a conclusion or key takeaway.
Let's think about a very simple scenario:
Your stakeholders need to make quick and efficient decisions without having to absorb a lot of data. Therefore, using data to tell a story is helpful. They don't need to schedule meetings, gather them, and explain to them what's in it. Instead, send them visuals and elaborate on what you intend to convey.
Several statistics and studies show how our human brain processes information.
The ability of the human brain to process visual information is very strong. By displaying data in a visual format, visualizations take advantage of this innate ability to help people easily recognize and understand patterns, trends, and correlations within the data. Visuals effectively communicate information by utilizing features like colors, shapes, and spatial positioning. This reduces cognitive load and facilitates understanding.
Moreover, visuals have the power to evoke emotions and build a connection with the data. By presenting data in a visually compelling and relatable way, individuals can develop an emotional engagement with the information. In addition, emotionally impactful visuals can make an impression that lasts, increasing the chance that the information will be remembered over time.
Getting rid of clutter in data visualization storytelling is crucial for effective communication. Some data analysts tend to pack too much data into a chart or a single dashboard. They might think that this brings informative insights to the audience. However, it is a side-effect practice. They are co-incidentally distorting the insights they want to convey.
Cluttered visuals can distract the audience and prevent them from getting the main message or insights. By simplifying the design, removing unnecessary elements, and organizing the information effectively, the audience's focus can be focused on the key points of the data. As a result, this improves comprehension while also reducing visual noise, which makes it easier for the audience to recognize patterns and connections within the material.
Furthermore, eliminating clutter improves aesthetics, readability, and storytelling flow. By presenting a clean and focused visualization, the narrative can develop naturally and make sure the audience remains engaged and captivated. It also helps deliver accurate data representation, reducing prejudice and misunderstandings.
Using effective visuals should be suitable for the data and the context because different types of charts excel at representing specific types of data. By selecting the most suitable chart, you can effectively communicate the information to your audience. A well-chosen chart ensures that the data is presented clearly and understandably, making it easier for the audience to grasp the intended message or insights.
For example, when showing trends over time, line chart is ideal for showing the progression of a variable or multiple variables over time. It enables the audience to observe trends, patterns, and changes in data values. If you want to compare categories, you can use bar chart, column chart, or stacked bar. When displaying correlation, scatter charts are perfect for visualizing the relationship between two continuous variables. You can use a bubble chart, it is like a scatter plot, but with an additional dimension represented by the size of the bubbles. It allows for the comparison of three variables, with the x and y axes representing the correlated variables and the size of the bubbles indicating a third variable.
A well-chosen chart ensures that the data can be presented efficiently and concisely. It not only helps convey the necessary information simply and straightforwardly but also makes the storytelling process more efficient and accessible. Dataflake data visualization tool is a great choice for you to limitlessly deliver storytelling with data with so many highly customizable styling options.
Imagine that you make a good preparation and get ready to tell your story through data to your stakeholders. After that, people aren’t paying attention to your presentation because they don't know where they need to focus. At that time, you are demotivated, right? That's why you need to refocus their attention on the stand-outs, using some technique of colors, shape edges or images, etc.
Your eyes are going to be pulled to whatever stands out the most. When the first time you look at a chart or a dashboard, the elements that stand out the most will be noticed first. Let's take a simple example below to see how it works:
In the cluster of numbers below, how many 3s are there?
We guess that it takes you more than seconds to find the number “3”
Now, with this image, how many 3s are there?
You will right away answer “six”
Thanks to strategically highlighting the results you want to deliver, your audiences can quickly spot the answers. Moreover, making use of the title should be relevant to the most striking stuff on the chart so that your audiences promptly grasp the insights.
When delivering storytelling with data visualization, understanding your audience is very important. No matter how perfect your story is, follow the guide or tips mentioned above, but, you tell the wrong target audiences, you waste your time and efforts.
Research carefully the target audiences that you want to tell a story to, their goals, technical skills, or even their interest. For instance, in terms of technical levels, some people can instantly adapt to the information, but others might take some time to understand the stories. Therefore, for non-technical people, you should choose charts that are simple and easy-to-understand.
Another important area of data visualization storytelling is the message you want to communicate. When understanding the questions that you want to answer through data, choose data that supports it. From that, you can demonstrate how the data relates to the audience's interests, challenges, or decision-making processes. This relevance makes the data story more meaningful and actionable for the audience.
Choosing the right data visualization tool is essential for effective storytelling with data visualization. It not only empowers you to create captivating and impactful data stories but also effectively communicates insights, engages the audience, and leaves a lasting impression.
Based on your business’s needs, you can opt for a suitable data visualization tool. You don't just need a tool that offers features and capabilities that enable you to create compelling visualizations tailored to your data story. You need much more on how you can boost collaboration and automation that save you tons of time and cost. Ahhh, yes, a tool that fits your budget
Now, you are in the right place. Dataflake is a good tool that fits your needs.
Dataflake is a highly customizable data visualization and embedded analytics tool that allows you limitlessly tell your data stories and quickly embed dashboards in any application or website.
Hold on! That’s not all.
Apart from enabling you to deliver data storytelling with Dataflake, you can experience upcoming features that boost collaboration, communication, and automation with your team; for more effective results, check it out:
Manage queries on a single page: Track the status of your queries by editing them, talking to your peers, and adding reviews. Additionally, easily view all query modifications in just a single page
Data Anomaly Monitoring: Choose your metrics and have them tracked automatically. Getting notifications via various channels when your chosen metrics exceed any set data thresholds
Data Quality Monitoring: Keep an eye on your data at all times to prevent errors and downtime. Keep track of the volume and freshness of the data and notify users of any issues with data quality.
Data Incident Management: observability of your data and provide you thorough information about reported incidents, including their status, timeline, and severity, automatically.
In the end, storytelling with data visualization is about making complex information accessible, relatable, and impactful. It enables us to unveil compelling narratives hidden within the numbers, influencing decisions and driving positive change. By harnessing the power of data visualization and storytelling techniques, we can unleash the full potential of data and turn it into an engaging story that connects with our audience.
