Data Visualization Prerequisites

Data visualization is a powerful tool for graphically representing data that’s accessible to general audience members. Visualizing data can take many forms, such as maps, charts, and graphs. You might worry that data visualization will be too hard to learn. This guide will help you understand the best methods for learning data visualization and what you should study first to make the learning process easier. This way, you’ll be successful however you choose to apply your new skills. 

What is Data Visualization?

Data visualization uses graphics like plots, charts, or animations to represent data findings. These visual depictions communicate complicated data relationships in an accessible and engaging format and have a range of applications for sharing data-driven insights with an organization’s internal and external stakeholders. Because an estimated 65% of the population comprises visual learners, data visualization provides a way to quickly and effectively convey data findings. Even though data visualization takes many forms, it shares the common goal of communicating otherwise complex data insights in a memorable and understandable way, even for those who don’t come from a technical background.

Each day, 2.5 quintillion bytes of data are being created, which continues to grow exponentially. This increase in the amount of data has created a corresponding need for visualization practices to share the insights these numbers contain. Data visualization has a variety of uses across industries and professions. It has applications for describing trends or patterns hidden in data and communicating organizational structures or hierarchies. The data visualization process is typically broken into four purposes: to generate ideas, to illustrate concepts, to provide avenues into visual discovery, and to convey data in the form of visualizations.

Read more about what data visualization is and why you should learn it.

What Can You Do with Data Visualization?

Those with the skills to create engaging and effective data visualizations have the power to communicate detailed data insights and findings to audience members from all backgrounds. Data visualizations provide a concise and interactive way to depict data trends. Visualizations incorporate color and contrast to present information like sales patterns so that audience members can quickly observe information that may be difficult to see from a graph or spreadsheet. In addition, another benefit of working with data visualizations is that they can provide perspective on the data by placing it in the context of a larger story, which can help audience members understand the information as it relates to an organization’s overall goals or bottom line. Context plays an integral role in helping audiences understand the entirety of the data being depicted, which would be difficult to convey by listing numbers in a table.

Data visualization also provides a better understanding of a business’s operations. Running a business requires staying on top of many moving parts, and data visualizations provide a tool that can depict multifaceted operations and how different business activities connect. Moreover, analyzing and visualizing data provides insights into important business metrics that can lead to smoother daily operations and more successful project execution. For organizations that sell products or services to customers, data visualizations offer crucial insights into customers’ preferences, demographics, and shopping patterns. They provide a way for organizations to use customer-focused data to explore brand perception, customer sentiments, and even what customers post about the product or service on social media outlets. Businesses can then use these insights to tailor marketing strategies and brand outreach.

In addition to providing customer insights and depicting important trends in the data, visualizations also tell a story. Information is presented in an easy-to-understand format, and the audience is taken on a journey that leads to an inevitable, data-driven conclusion. Just like a written story, a visual story has a strong beginning, a basic plot, and an ending that looks into the future, providing recommendations for how to move forward. Instead of requiring tens of thousands of words to tell this story, data visualizations can do so with a series of well-placed infographics, carefully worded labels, and brief descriptions of the content, all of which tell the story of data in the larger context of an organization’s needs and goals. 

Is Data Visualization Easy to Learn?

Because the field of data visualization requires a set of related skills, breaking down its difficulty is a matter of looking at each skill separately. Like any skill, the speed at which you learn to visualize data will depend on various factors, such as your prior experience handling data, your background in creating visualizations, and your ability to tell stories.

Most people who work with data visualization also have experience with data analytics. Often, this involves working with programs such as Microsoft Excel, the industry-standard spreadsheet application, for organizing and analyzing numerical findings. Generally speaking, most individuals find Excel a relatively easy program to learn and allow approximately 18-20 hours to become familiar with this application.

Another popular program used by those who visualize data is Tableau. Tableau is a widely used tool for business analytics, data analytics, and data visualization tasks. This software helps users create customized visualizations that convey significant data findings clearly and engagingly. Most Tableau users consider this tool relatively easy to use since it provides an intuitive drag-and-drop interface. However, if you’re new to business intelligence, it can take two to six months to be comfortable working with more advanced visualization features. 

In addition, your familiarity with programming languages such as Python is another contributing factor to how difficult it will be to learn data visualization. Python is one of the most-used programming languages for data analytics and visualization tasks. It provides users with free libraries for visualizing data, like Plotly, Matplotlib, Seaborn, and ggplot. While learning Python basics may take just a few weeks, it can take several months to become proficient with its visualization libraries.

Rather than trying to master data analytics on your own, a great place to learn how to work with data analytics and visual storytelling is to enroll in Noble Desktop’s in-person or live online Data Analytics Certificate. This comprehensive program covers core data analytics and visualization skills, such as working with Excel, SQL, Python, and Tableau. 

What to Know Before Learning Data Visualization

If you’re interested in learning data visualization, there are a few skills you may consider acquiring before you do so, which can expedite the learning process. The following are a few of the most commonly used skills that most individuals who work with data visualization have before they begin to visualize data findings:

Data Analytics

Data analytics is the science of analyzing vast datasets to extract meaningful information. It involves discovering, interpreting, and communicating any significant pattern that emerges in data. Data analytics is used to help organizations make more informed business decisions based on data. Those who work in this field rely on various tools, such as Microsoft Excel and programming languages like SQL, Python, or R, to help with analytics tasks. Noble Desktop’s in-person and live online Data Analytics Certificate provides participants hands-on training using Excel, SQL, Python, and Tableau to pursue a career in business analytics or data analytics. 

Design

Because data visualization involves conveying complex data findings in an easy-to-understand, engaging visualization, those who understand basic design principles may find visualizing data easier than those without formal design training. Design involves envisioning and planning to create a system, object, building, or vehicle that can provide a solution for users. Some of the most basic design principles are balance, contrast, proportion, pattern, unity, white space, variety, and repetition. These principles can be used in concert or individually to create an object or system that’s both functional and visually appealing to users. These design concepts all have applications for those who create data visualizations. A successful visualization must often incorporate several design elements, such as effectively using white space, contrasting dark and light colors, and emphasizing essential data findings or patterns.

Storytelling

When most people think of storytelling, they tend to think of the written word. However, storytelling is a much broader category that can involve using words, actions, or images to engage the audience’s attention and spur their imagination. Visual storytelling involves many elements of written stories, such as an engaging introduction, a compelling storyline, and a conclusion that may look “toward” the future in some way. Just like novels, visual stories in data visualizations are accessible and memorable and likely will leave an impression.

Learn Data Visualization with Hands-on Training at Noble Desktop

If you’re interested in studying data visualization, Noble Desktop offers several in-person and live online courses that provide hands-on training. For those who wish to work with Tableau for visualizing data, Noble’s Tableau for Data Visualization Bootcamp is an excellent option. Participants receive an overview of the field of data visualization and learn about Tableau Public’s visualization tools. By course completion, students will have a solid understanding of identifying which datasets to connect to and how to analyze, filter, and organize data to make customized, publishable visualizations. This course also offers the option of a free retake for those interested in revisiting Tableau concepts. 

Noble’s in-person or live online Data Analytics Certificate is another good learning option for those seeking a more intensive study option. This rigorous program provides expert instruction on various data analytics concepts and prepares learners to become Business Analysts or Data Analysts. By course completion, all participants will be familiar with core business intelligence, statistical analysis, data analysis, and data visualization concepts. This is a project-based course in which students will complete various real-world projects using prescriptive and predictive analytics. All students receive one-on-one mentoring as part of tuition.

In addition, other in-person and live online data visualization courses are also available from Noble Desktop. Those who wish to learn the tools to become Data Scientists may consider enrolling in Noble’s Data Science Certificate, which covers machine learning, automation, SQL, and Python. A Python for Data Science Bootcamp covers fundamental and complex Python programming concepts, such as creating programs and using statistics to make machine learning models. 

The Excel Bootcamp is also available, which teaches core spreadsheet functions like working with macros, formulas, and PivotTables. Finally, those interested in working with SQL to extract information from databases can enroll in Noble’s SQL Bootcamp. This course prepares learners to write queries, aggregate data, and filter results using Postgre SQL.

Key Insights

• Data visualization involves using graphical representations like charts or maps to tell a larger story about data findings so that audience members can easily access the insights.
• Because it is a broad field, learning data visualization involves many related skills, such as studying Excel, Tableau, and programming languages like Python.
• Some common skills individuals may choose to learn before embarking on data visualization study are data analytics, design, and storytelling. 
• Enrolling in one of Noble Desktop’s in-person or live online data visualization classes is a great way to learn more about data visualization.