How do Beginners Learn Data Visualization?

Any aspiring data visualization professional will start at the very beginning. Novice students can find thousands of training options that vary in delivery method, length, level of advancement, price, and specific subject matter. Most opt for live online courses, which are the most effective and offer additional benefits. You'll learn about different data types (categorical, numerical, etc.) and basic data analysis techniques to prepare your data for visualization. Additionally, many beginner classes will introduce you to principles of visual perception and how to use visuals effectively to communicate data insights to an audience. Once beginners feel comfortable applying these skills, they will have built a foundation of skills to be built upon in the following higher-level classes.

Getting Started with Data Visualization

Before you begin a data visualization class, ensure you have a few materials and mindsets on hand. Having free tools like code editors before getting started with data visualization is a great advantage. Code editors allow you to experiment with code used in data visualization, even if you're not initially writing complex programs. You can explore syntax, practice basic coding concepts, and get comfortable with the editing environment. Some data visualization projects might involve cleaning or transforming data before visualization. Code editors can help manipulate text files containing data, especially for basic tasks. While many data visualization tools offer user-friendly interfaces, some functionality might be extended through scripting languages like Python or R. A basic understanding of code editing can be beneficial for interacting with these languages in data visualization. 

Before diving into data visualization, it would be helpful to understand data analysis concepts like calculating central tendency and dispersion measures. This helps you identify patterns and trends in your data. Knowing the basic principles of how humans perceive visual information is also beneficial. This includes understanding how color, size, and position influence our interpretation of data visualizations. Also, basic knowledge of color theory helps you choose visually appealing color palettes that are accessible (considering color blindness) and effectively represent your data.

The First Steps When Learning Data Visualization

Embarking on a data visualization career often begins with a foundational course, serving as a springboard to acquire essential skills and knowledge. These initial steps lay the groundwork for developing a robust toolkit and expertise over time. Regarding data preparation and cleaning, you'll develop the ability to recognize different data types within a dataset. This is crucial for choosing the most appropriate visualization methods. The course also introduces you to techniques for handling missing values, outliers, and inconsistencies in your data. Clean data ensures accurate and reliable visualizations. In some cases, you might learn how to transform data to prepare it for specific visualizations.

Choosing the right chart type is a fundamental skill you'll most definitely learn in a beginner data visualization course. A beginner course will introduce you to various chart types. You'll learn the strengths and weaknesses of each type, including what kind of data they represent best and how well they convey specific information. You'll develop the ability to identify the data type within your dataset and choose the chart type that best suits that data structure. Instructors will likely guide you through how to consider your visualization goals (comparison, trends, distribution) and select the chart type that effectively communicates those goals using your data.

You can also expect to learn about visualization design principles in a beginner data visualization course. In fact, these principles are a fundamental aspect of creating clear, informative, and impactful data visualizations. Data visualizations are meant to communicate information effectively. Design principles help ensure your visualizations are easy to understand and don't overwhelm viewers with unnecessary visual clutter. Basic principles of color theory are often covered in a beginner course. You'll learn how to choose color palettes that are visually appealing, accessible (considering color blindness), and effectively represent your data. For example, using contrasting colors for different data points can improve readability. Courses might also introduce you to basic typography principles like choosing appropriate fonts and font sizes to ensure your visualizations are clear and readable. Different fonts can convey different tones and emotions, impacting the overall message.

Free Data Visualization Tools for Beginners

To learn data visualization, you should explore a few free learning tools and resources before diving into a course. Luckily, you can find many with the push of a button. Hundreds of video collections, social media platforms, blogs, and chatrooms discuss data visualization concepts or provide relevant information. For instance, Noble Desktop’s Free Seminar page has a plethora of useful, pre-recorded video lectures in varying fields, subjects, and technologies. You could watch a data visualization lecture or focus on a specific tool, such as Tableau. The options on the internet are vast, so there is a resource out there for everyone, regardless of skill level or reason for learning.

Several free data visualization tools can help you create informative and visually appealing charts and graphs. Google Data Studio, Microsoft Power BI Desktop, and RawGraphs are all highly popular online data visualization tools that anyone can access, whether they are beginners or experts. Many data visualization classes, both beginner and advanced, will teach students how to use free software, so it is worthwhile to have an account set up. While there is a time and a place to rely on free resources, these are all a few of the most common free tools for beginners to have on hand or that they will learn in a beginner course.

Live Data Visualization Training for Beginners

Each course varies in numerous aspects, including their delivery modalities, with some being available on-demand and others being conducted live, in-person, or online. On-demand classes are asynchronous, meaning the student does not attend a lecture or interact with an instructor and peers. Asynchronous classes are becoming increasingly popular but are not the best option for everyone. This delivery method may work for some, but most agree that a live setting provides the most benefits. There are distinct differences between the two that are worth considering before enrolling in a course.

Live training is widely considered one of the best ways to learn a new skill, and for good reason. Overall, a live training course provides ample benefits and advantages that help facilitate learning. The main advantage of a live course is that it frequently promotes interactivity between the student and the material. Most live online classes offer students plenty of hands-on practice, allowing for a more personalized experience. Additionally, the instructor can provide direct feedback in a live course, which is not offered in an on-demand course. This feedback, interaction, and realistic practice with the data visualization material make the learning process much less daunting.

This is particularly applicable to novice learners. As previously indicated, on-demand courses are primarily suitable for a specific group – specifically, beginners. Live classes are the most effective learning method for beginners because they provide an immersive experience. By prolonged use of the technologies and tools used in data visualization, students leave feeling more adept at using their skills in the real world. In addition, many live training options help students with portfolio development, which can make all the difference once entering the workforce. If you’re a total beginner and aspire to become a data visualization professional, a live training course is one of the best ways to start your journey.

The Next Step 

Once you obtain foundational data visualization skills and knowledge, you’ll likely want to diversify your abilities and learn more complex concepts and tools. After completing a beginner course, you can enroll in intermediate and advanced-level courses that bring you one step closer to your goals. An intermediate course will help you surpass your beginner knowledge and allow you to complete more challenging and industry-specific projects. At this level, you’ll likely begin applying theory to the practice at a greater level and gain a better understanding of data principles.

Advanced-level courses pave the road to mastery, which is the goal if you want to become a professional data visualization professional. Advanced courses go beyond basic theory and application and focus heavily on complex topics and concepts. For example, you'll learn how to create interactive data visualizations, allowing users to dynamically explore data through filtering, zooming, and other interactive elements. Libraries like D3.js or tools like Tableau can be used for this purpose. Some advanced courses might even cater to specific industries, such as marketing, finance, or healthcare, teaching you how to tailor data visualizations for those audiences and decision-making needs.

Once you have completed advanced training, a world of possibilities will open before you. There are options to complete certificate courses, which can, in turn, help you prepare for certification exams. While there are distinct differences between certificates and certifications, it is useful to obtain either one (and in some cases, it will be necessary to earn a certification). Advanced training also values career development and portfolio building, so many students take advantage of the class time dedicated to perfecting their resumes, portfolio projects, and interview techniques. To become a data visualization professional, you must undergo advanced training and have sufficient work to show for it. This is often made possible through completing various classes, a bootcamp, or a certificate course.

Live Training Options 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. Noble’s Tableau for Data Visualization Bootcamp is an excellent option for those who wish to work with Tableau to visualize data. 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 PostgreSQL.