Data is everywhere and more and more businesses are realizing the benefit of harnessing them to develop critical insights and stay competitive. With companies investing in data science teams and roles, there is already a good understanding of why data literacy is important but visual literacy is a term that might be less well-known.

So what exactly is visual literacy and how does it impact data analysis and visualization? It can seem like they’re one in the same but there are important distinctions that can help us better understand the ecosystem of data analysis and visualization.

What Do We Mean by Visual Literacy?

The term “visual literacy” refers to a set of abilities to find, interpret, evaluate, use, and create images and visual media. It’s a concept with application traditionally in art and design, but it is much broader. Visual literacy is concerned with language, conversation, and interaction, and in the context of data, it is concerned with how visual mechanisms work with data. For example, how a user understands and interprets a chart that shows sales performance over the last six months is related to visual literacy. How that chart is presented for ease of understanding and memorability is the role visual literacy plays in the effectiveness of any data visualization.

How Does Visual Literacy Affect Data Viz and Storytelling?

The omnipresence of data has changed the way people work and is often recognized as critical to future generations’ democracy, but there is a crucial distinction to make when it comes to visual literacy and understanding how data visualization works. If you think of data as a piece of music, strong data literacy requires the ability to read notes to understand the whole piece. It has to do with understanding when to utilize a mean versus a median or determining when to trust a study’s results and when to disbelieve small-sample size research.

On the other hand, visual literacy is the music. It is demonstrated by a tune that repeats or develops into a chorus. When adding data notes into a song, consider your audience’s visual literacy to create meaningful narratives. And meaningful narratives are the building blocks of a data story.

Show the Data or Tell a Story?

The ways in which we connect and visualize data to convey information is an essential task for any data visualization professional and can result in some difficult choices: do we want simplicity or complexity? Do we want to craft a narrative? Or is it worth it to display raw data and allow consumers to explore on their own? Do you go for simplicity or complexity? Do you show the data or tell a story? Do you display raw data or take the user on a journey?

Ultimately, significant data visualizations must be both accurate and appealing and strike a balance between being informative and being aesthetically appealing. Visual literacy can help us strike that perfect balance of helpful and easy to view.

Data Literacy Vs. Visual Literacy

In today’s world, many of us suffer from information and insight fatigue, and are inundated by things like dashboards cluttered with red and green indicators of excellent and negative performance.That’s where data literacy comes into play; it’s the ability to interpret and understand data itself. Good data literacy allows you to select the right chart for your data and typically places an importance on clarity above aesthetic; rather than radials, it chooses bars.

Visual literacy is concerned with the presentation of data as information. It requires attention to detail but is also concerned with whether or not your audience cares about the data you’re showing them. Simultaneously, visual literacy is concerned with how the work is remembered, the story it tells, and whether or not it’s meaningful, instructive, and significant.

A few other questions that might come up when thinking about visual literacy in data visualization, include:

• Is this chart visually interesting enough?

• Will people want to interact with it and explore further?

• Is it memorable?

• Is it beautiful?

• Is the meaning clear? If not, is more information intuitive enough to find?

Conclusion

For the art and science of data analytics and visualization to progress, we must transcend data literacy. Data literacy is an essential start, but users don’t want to look at just bar graphs and pie charts. We must pay attention to color theory, forms, the reading habits of internet consumers, and the rising sense of data fatigue among end-users, just to name a few factors. Visual literacy must be learned, practiced, and perfected to ensure that data visualization remains relevant and useful for everyone.

Interested in learning how data storytelling could help your business? Reach out to Gemini today! We believe that data is a powerful storyteller and with our expertise, you can improve your business’ capability to build and comprehend even the most complex data associations, connections, and relationships.

Big data is used in just about every industry today, as it can help inform the decisions that companies and organizations make. Now, one of the best examples of how this can be used comes in the form of data storytelling. 

We understand if it’s your first time encountering this term. To help shed some light on this subject, we thought it would be beneficial to have a brief discussion on data storytelling and what it can do for you. If this is something that you’re interested in, read on as we breakdown how effective data storytelling can help your business:

What is Data Storytelling?

Data storytelling is a methodology for communicating information to make it easy for a specific audience to understand. This all goes back to how big data can’t really be understood by people who aren’t in the know when it comes to data science. So, how does this work?

Data storytelling relies on a compelling narrative to make data and figures significantly more accessible. It essentially hinges on three key fields of expertise working in harmony, as it takes a combination of data science, storytelling, and visualization to make big data more understandable.

To help you get a clearer picture, here’s a short summary of the role that these three fields play in data storytelling:

• Data Science: The data is the content in data storytelling. It serves as the backbone of the narrative that you’re trying to convey.

• Visualization: Even with a great narrative, your audience won’t be able to comprehend complex data. This is why good visuals are needed to better understand the data that’s being presented. Through the use of charts and graphs, abstract data becomes easier for the audience to digest.

• Storytelling: You’ll need to be able to explain the data in terms that are palatable for your target audience. This part may be the most important of all, as data won’t mean anything if you can’t get your audience to buy into it.

How Can Data Storytelling Positively Impact Your Business?

Because of data storytelling’s ability to make abstract concepts more understandable, it opens up many different possibilities for your business. One of the major ways that it can help your business comes in the form of securing funding.

No matter the industry that you are in, you will need funds and investors to turn your vision into a reality. And while you can try to sell your ideas to the investors, they’ll want tangible proof that their investments will pay off. This is where data storytelling comes in.

By presenting data in an understandable way, you put your investors at ease as they’ll know what they can expect after investing in your company. This also helps set the appropriate expectations, which means that they won’t be spooked easily if your company takes a little longer to flourish.

Conclusion

We hope this information proves to be useful when it comes to helping you understand the importance of data. Because the world is becoming more and more reliant on information, data storytelling will surely cement its place as one of the most important aspects of big data services.

If you want to see how Gemini Data can help you tell stories with your data, contact us to set up a discussion with our data professionals in California to learn more about how big data services can help you. Visit our website or send us an email at contact@geminidata.com to schedule a consultation!

Although intuition can be helpful, relying solely on it may lead to ill-informed choices that negatively impact a business. However, using data to influence decision making allows for smarter and evidence-based outcomes that can take your business to the next level.

Looking ahead to the future, data-driven decision making will be more important than ever as we’re flooded with more information and digital technologies evolve daily.

What Is Data-Driven Decision-Making?

Data-driven decision-making is the process of using actual data to make organizational decisions, validate a course of action, and work toward goals rather than relying on observation or guesswork. It prevents poor decision-making due to biases or false assumptions that can often cloud judgment.

This process involves using key performance indicators and measurable goals to make business decisions. The insights from these facts and patterns are analyzed to develop strategies and activities that are most beneficial for the organization. Additionally, data-driven decision-making allows us to conduct real-time analysis to make quicker decisions and pivot on a dime.

Real-World Examples of Data-Driven Decision-Making

Before the digital revolution, collecting and analyzing data insights was tedious and time-consuming, which often led to delays. Now, business intelligence software is available that makes decision-making faster and more convenient. Even users who do not have deep technical knowledge and expertise can use a program to extract insights from accurate, relevant, and valuable data quickly and effortlessly.

Data-driven decision-making can come in many forms. For example, your company can conduct surveys to know the products and services your target audience is interested in or launch a new product in a test market to get a glimpse of how it might perform. Here are some real-world examples of businesses using data to their advantage when making high-impact business decisions:

• Future store locations at Starbucks

  During the 2008 economic recession, hundreds of Starbucks branches were closed as the company – like many others – reacted to a multitude of financial troubles. As they recalibrated their approach, former CEO Howard Schultz promised that the company would identify future store locations with a more analytical approach. Starbucks had been known for its aggressive growth, but that strategy may not have been rooted in actual data. At present, the corporation works with a location analytics company to determine ideal store locations and see the likelihood of success for these areas using demographics and traffic patterns.

• Leadership development at Google

  Google prioritizes people analytics, which is an approach that aims to inform people of the organization’s practices, processes, and programs. Due to this, they launched Project Oxygen, a well-known people analytics initiative used to identify common behaviors of high-performing managers. It also developed training programs to improve employee’s core competencies. It collected data from more than 10,000 performance reviews and compared it with employee retention rates.

Why Is Data-Driven Decision-Making Important For My Business?

No matter the industry, your business has to be data-driven. Failing to do so and basing decisions on pure intuition can lead to challenges down the road. Through big data analytics, you have a higher chance of success and preparing your business for future growth by predicting future trends more accurately, optimizing operational efforts, and producing insights that can be acted upon in the best interests of your company. In other words, using data in decision-making will keep you heading in the right direction.

What’s Next?

As digital technologies evolve seemingly every day, data-driven decisions will also keep changing. Serverless and no-ops cloud deployments will help businesses automate many processes, allowing owners to focus on running their business and making smarter decisions. As businesses require more real-time decision-making (as we’ve seen throughout the COVID-19 pandemic), streaming data will be critical to making real-time business decisions. With the continued ease of access to machine learning, data analysts will be able to quickly and cheaply roll out technology-driven initiatives that previously would have been costly and time-consuming. Additionally, as data-driven technology becomes more mainstream, lowering barriers to access and pricing, more businesses will be able to analyze and react in real-time.

Conclusion

Making business decisions should be taken seriously since it can mean the difference between failing to reach your business goals and making a mark in the industry. By incorporating data analytics into your business strategies, your business can continue to grow and thrive.

Transform the way you make business decisions with data analytics solutions. At Gemini, we’re redefining data analytics so you can go from data to insights to decisions faster. Contact us to learn more about how we can help your business.