Is Data Visualization a Hard Class?

As with any skill, data visualization difficulty level is highly subjective, with some finding it more challenging than others. However, it is generally easier for people with prior data experience and those who choose to learn it in a live class. Additionally, the difficulty of a data visualization class can also depend on what information it covers, whether it sticks to beginner skills only or offers more advanced training. With time and practice, however, learning data visualization is 100% doable for anyone who puts their mind to it. This article will review the most common challenges faced by data learners and offer suggestions on how to simplify the learning process. 

What is Hard about Learning Data Visualization?

Data visualization, while rewarding, can present challenges for beginners.

Understanding Data 

Grasping different data types (numerical, categorical, dates) and how they influence visualization choices can be a hurdle. You might need to brush up on basic data analysis techniques to identify patterns and trends effectively. Before diving into creating visualizations, it's important to address the messy data by dealing with missing values, outliers, and inconsistencies, which can be quite time-consuming and demands attention to detail.

Visual Design 

Data visualization goes beyond just charts and graphs. Applying design principles effectively (color theory, typography, layout) can be challenging, especially if you're new to design concepts. Finding the right balance between aesthetics and clarity can take practice. With numerous chart options available, selecting the most suitable one for your data and message can be tricky. Understanding the strengths and weaknesses of different charts requires practice and experience.

Software Skills 

Popular data visualization tools like Tableau or Power BI have a range of functionalities. Mastering these tools and navigating their interfaces can take time and dedication. Data visualization tools offer a vast range of features. Mastering all functionalities, especially advanced options like scripting or automation, takes time and practice. Learning how to import data from various sources and manipulate it within the software for visualization can also be a challenge.

Other Challenges

Communicating insights effectively through visualizations requires practice. It can be challenging to learn to craft compelling data narratives and tailor visualizations for specific audiences. Not all data has an inherently clear story. You need to be able to analyze the data, identify trends or patterns, and translate them into a compelling narrative. This requires critical thinking and an ability to see the bigger picture. Also, the data visualization field is evolving, and new tools and techniques emerge constantly. Staying updated with the latest trends and best practices requires ongoing learning.

How Can I Make Learning Data Visualization Easier?

There are a variety of resources you can use to make data visualization easier to learn. However, each resource has different advantages, making it important to choose ones that align well with your learning goals. If you only use data lightly, you can get a head start by attending a short class or finding the right free learning tools. If, on the other hand, you plan to use data visualization for your career, you’ll benefit from choosing a certificate program that will pay more attention to instructors and provide more professional resources. 

Free Resources (For Exploring Data Visualization Basics and Answering Questions)

Although the capabilities of free data visualization tools are somewhat restricted, they can offer a helpful starting point for those embarking on data visualization projects. Before starting your classes, familiarizing yourself with data visualization through a brief tutorial can greatly enhance your learning experience with the instructor. Similarly, free data visualization education resources are a good option when you're just looking to learn a few basics to complete a beginner-level project. You can also use free resources to solve niche problems on the fly. When faced with challenges in a data visualization project without immediate instructor support, leveraging free resources can serve as a helpful but somewhat constrained solution.

In order to fully leverage free resources, it is essential to know how to locate them and determine their quality. Rather than clicking on the first YouTube tutorial you see, take a moment to check whether there’s a resource available through a reputable design company like Tableau. You can also use free data visualization sample courses published by tech education platforms such as Noble Desktop. By sticking to more established sources, you’ll dodge the bad design habits of other beginners on the Internet. 

Short Live Classes (For Hobbyists Who Want to Learn Data Visualization)

Even if you're pursuing data visualization as a personal interest, learning from an expert can significantly streamline your journey. Enrolling in a class will spare you the hassle of sifting through numerous free resources to find what you need, which can be quite overwhelming. Instead, you'll receive hands-on guidance with plenty of opportunities to ask questions (no frantic Google search necessary). 

Doable in under a week, these classes slot easily into a busy schedule and are available both online and in person. Many classes take just one day; others allow you to spread your training into several shorter sessions. However, because short courses have a limited time allowance, they tend to focus more on technical skills than soft skills that are just as relevant to data. 

Most live classes deal with beginner topics, making them ideal for hobbyists. However, plenty of short classes treat advanced topics like advanced chart types and techniques. As a result, short classes are a great way to level up or learn niche skills for a specific project. In addition to making it easier to learn new skills, short courses also offer an affordable, low-stress environment where aspiring professionals can take data visualization for a test drive before committing to a more intensive training program. For the same reasons, taking a short introduction course can also help you prepare for success in a certificate course. 

Certificates and Bootcamps (For Comprehensive Career Preparation)

Attending a certificate-granting data visualization course is the ideal way to prepare for a career in data visualization. When aiming to utilize data visualization professionally, acquiring advanced skills beyond personal use is crucial. Additionally, developing proficiency in other data-related abilities is crucial, and obtaining design certificates can facilitate this process efficiently and expediently. The average certificate takes only a few months (part-time) or several weeks (full-time) to complete and offers online and in-person expert-guided instruction. 

Data certificates serve as vocational training programs that offer practical instruction that seamlessly prepares individuals for employment. Furthermore, boot camps prioritize hands-on experience and potentially incorporate internship opportunities. These accelerated training programs can even replace a college degree, allowing you to become a full-fledged data professional without attending college. Moreover, most certificate-granting bootcamps typically cost $2,000 to $4,000, rather than the higher costs often associated with university programs.

On top of making it easier to develop a well-rounded professional skill set, certificate courses make it less challenging to get a job. Most programs include portfolio workshops, industry overviews, and interview training. Many classes also provide one-on-one mentorship or career counseling to help you get your career on the road with as few hiccups as possible. 

Short On-Demand Classes (For Affordable Supplementary Training)

On-demand data visualization training can greatly enhance your skill set when viewed as a complement to other training methods. Available through digital platforms like Coursera, Masterclass, Udemy, and SkillShare, on-demand courses can provide you with self-study materials to explore during your free time. Many on-demand classes are offered as subscription services, with costs varying significantly from class to class. 

In the on-demand packages, you can access pre-recorded video lectures, written tutorials, and practice prompts for studying beginner and niche topics similar to those covered in free resources. However, the main difference between on-demand data visualization classes and free learning materials is that an expert typically curates the materials included in these classes. On-demand study tools can be incredibly valuable when troubleshooting a niche data visualization project outside your regular class time. 

Best Ways to Learn Data Visualization Without Difficulty

Participating in a live class will help you avoid pitfalls common to new data visualization learners. With a live instructor at your side through the many challenges you’ll encounter, you’ll learn more quickly and spend less time accidentally building bad habits. Live classes also provide hands-on practice to help you develop skills as you learn. Feedback and encouragement from your instructor can also make it easier to identify weaknesses and overcome discouragement. 

Another way live classes make learning data visualization less difficult is by offering complimentary resources. If grappling with the financial burden of investing in an educational program feels overwhelming, enrolling in a live class can address both concerns simultaneously. Upon enrollment, many courses provide temporary access to specialized data visualization software, offering a multifaceted solution. If you’re looking for career resources, live bootcamps will give you the biggest bang for your buck, with perks like career counseling, interview training, and study materials for certification exams.

Learn Data Visualization With 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. 

Transform your data analysis process using artificial intelligence (AI). AI for Data Analytics offers an in-depth exploration of AI tools that automate data collection, preprocessing, analysis, and visualization, empowering individuals to derive valuable insights with minimal coding knowledge. By the end of the course, students will have gained proficiency in deploying AI-powered analytics in diverse sectors like finance, marketing, and healthcare, and will have honed their ability to communicate findings effectively through advanced visualizations and reports.

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.