Are Data Analytics Bootcamps Worth It?

If you’re interested in learning how to find meaningful insights in vast stores of data, many training options are available. However, you may not be certain whether you should enroll in a bootcamp program or opt for a different educational route. Bootcamps provide hands-on training that can help you not only learn the skills needed to make sense of raw data but to apply this training to real-world problems an organization faces. In this article, prospective data analytics students can learn more about how bootcamps compare to other types of data analytics training to determine whether they’re a good match for you.

What is Data Analytics?

Data plays an integral role in nearly all aspects of the modern digital landscape. Each day, approximately 2.5 quintillion bytes of data are created. Because so much data is being created across industries, humans wouldn’t be able to process even a small portion of this information without the assistance of computers. Until these data are processed, they are of no value to an organization. Those with a background in data analytics draw from their background in computer programming, math, statistics, and data visualization to determine what these numbers mean. Data analytics is a process that involves using different techniques and tools to collect, analyze, and visualize raw data so that trends and insights can be extracted from this information. Organizations can then use the data findings to help them understand how they’re currently operating and make more informed business decisions moving forward. 

What Can You Do With Data Analytics Training?

As more organizations continue to see the value in collecting data, the need for those with data analytics training is expected to continue to rise. Learning data analytics is a versatile, in-demand skill set with applications across industries. The data analytics process is a valuable tool with applications for solving real-world problems organizations face. In healthcare, it’s used to optimize resources, prevent diseases, and improve patient care options. Healthcare analytics can help with tasks like providing high-risk patients with personalized treatment plans, determining the efficacy of drug treatment regimens, and identifying disease outbreaks. Within the finance sector, those with a background in data analysis can put their skills to use in evaluating risk, detecting fraud, and providing more informed investment strategies for clients. When banks and other financial institutions handle vast volumes of raw data, they look for suspicious transactions, determine how credit-worthy individuals seeking loans are, and offer their customers personalized portfolio advice. Data analysis is even used to determine how internet search engines perform so that users see the most relevant search results first.

A background in data analytics isn’t only useful for helping organizations solve data problems. The training you’ll receive when you enroll in a data analytics bootcamp will prepare you to break down complicated information and clearly communicate data insights to audience members in a manner that’s easy to understand, even for those who don’t come from a technical background. Knowing how to clearly communicate complex information is a skill set that is essential to nearly all career paths.

Why Learn Data Analytics in a Bootcamp?

As you explore data analytics training options, you’ll want to consider the unique advantages and drawbacks of bootcamps and compare these to other forms of training. Although bootcamp content varies depending on the course focus and the provider, these live programs provide learners with career-focused training in an engaging, accelerated learning environment. Data analytics bootcamps are more intensive than on-demand coursework and shorter skills classes and typically require several weeks of study to complete. Because most bootcamps are career-focused, students can also take advantage of the career services, which is often included with tuition.

Bootcamps Compared to College

If you’re trying to decide whether a college degree or a bootcamp is a better data analytics training option for you, there are several important considerations. The college atmosphere provides learners with an immersive educational experience that affords them four or more years to focus on their studies. However, aspiring data professionals will also need to complete a range of other coursework alongside training in data analytics, including general education requirements. This means that students’ time and efforts are spent on acquiring a range of skills beyond just those involving data.

Moreover, data analytics is a fairly new degree in some colleges and isn’t available as an undergraduate major in all schools. If it’s not offered as a major, students who opt to learn data analytics in the college or university setting may have to declare a different major in a related field to receive instruction on this topic. In these instances, students may opt for a major in data science, computer science, statistics, or applied mathematics to receive data analytics instruction. Depending on their career aspirations, learners may also select economics, finance, business, psychology, or management information systems. Coursework in majors such as these typically offers aspiring Data Analysts training in core data skills, such as how to work with computer programming languages, apply mathematical concepts, perform statistical analysis, and communicate with databases. 

Data analytics bootcamps, on the other hand, offer a much more condensed, focused approach to data analytics training. Rather than requiring students to spend four years learning data analytics alongside other skills, bootcamp participants can fully immerse in their studies over a relatively short period of time, typically several weeks. These courses provide learners with career-specific instruction in one or more data analytics tools, such as Tableau, Excel, Python, or SQL. Rather than having to wait four years or longer to put this training to use, bootcamp graduates can immediately put their skills to use at their current job or apply them to a different data-related career path. Flexible scheduling options, which include weeknight and weekend part-time training, make bootcamps a viable study option for those interested in balancing full-time work with their studies.

Cost-wise, bootcamp study is a much more affordable learning option than college degrees. Tuition at some universities can cost tens of thousands of dollars a year and leave students with six figures of debt upon graduation. Bootcamps, on the other hand, are a more cost-effective type of training. Skill-specific bootcamps, such as Noble Desktop’s SQL Bootcamp, are available for about $1,000 and can be completed in just a few days. Other more comprehensive programs that focus more broadly on data analytics as a whole are generally more expensive and can cost upwards of $15,000 or more. However, this fee is only a fraction of the cost of one year of college for most learners. 

One of the main drawbacks to bootcamp study when compared to college training is that students tend to receive less hands-on training in the bootcamp setting than they would during college coursework. This is due to the duration of the training; bootcamps offer a much more accelerated training pace, which means that those interested in learning to work with data will have less time to practice the skills they’re acquiring than they would during college study. Students who opt for a bootcamp may need to devote additional time outside of the classroom to practicing the data analytics skills and tools they learn. The bottom line is that bootcamps are often a better (and much more affordable) learning option for those who can’t spend four years learning data analytics and who want to devote their entire effort to learning to analyze data rather than studying this alongside other skills.

Bootcamps Compared to Self-Paced Courses

Self-paced data analytics training is another learning option available to students. Programs like those that are available from Coursera and Udemy contain video content and tutorials and are pre-recorded and placed online for students to complete at their own time and at their own speed. This flexible type of data analytics coursework grants students the power to determine their own study pace and pause or rewind as often as needed to comprehend difficult concepts. Self-paced study is a good option for those who have busy work or personal schedules and need to complete their training as time permits.

Cost is one of the main perks of on-demand data analytics classes. They tend to be a much less expensive study option than bootcamps since they don’t provide live instruction. Some platforms offer courses for under $100, whereas others charge a subscription fee for coursework. Those interested in enrolling in a self-paced class should be self-motivated to complete lessons on their own without the support of a cohort of students or deadlines from the teacher.

Unlike bootcamp instruction, which students know reflects the current best practices in data analytics and the most up-to-date versions of software, on-demand study options have the potential to become dated. This is why it’s recommended that learners research the provider before enrolling in a class. Since no live instructor is present for on-demand courses, students will not receive feedback on their work and will have to find answers to questions on their own. This can make it challenging for some learners to fully master advanced-level data skills, such as creating macros in Excel or designing intricate Tableau dashboards. For this reason, some students begin learning data analytics through on-demand content but transition to more structured, live classes like bootcamps down the line, where they’ll receive personalized feedback and hands-on training. 

Bootcamps Compared to Free Online Training Options

If you’re still deciding whether to enroll in a data analytics bootcamp, you may wonder if this form of study is preferable to free online training material. Because of how many organizations and individuals now collect data, many free online resources are available. Learners can select from YouTube channels that provide short video instruction on specific data skills, such as printing Excel worksheets or querying a database with SQL. These videos only take a few minutes to watch and can help you fill a skill gap for a current project. Additionally, some providers post longer courses that offer more robust data analytics instruction, including an overview of the field as a whole. Since there’s no cost associated with these resources, they provide a low-stakes way for students to learn how to work with data. 

One drawback to free online training material is that learners typically don’t receive hands-on instruction in this format. No instructor is present, which means students must motivate themselves to complete lessons and practice the data skills they’re watching. This can make it especially challenging for those who are new to data analytics to fully grasp more complex concepts or skills. This is why free training material is a good place to look if you need to acquire one specific data skill, like creating a bar chart in Excel. However, if you’re trying to break into the field of data analytics to pursue an entry-level position or to acquire more advanced data training, you’ll likely benefit more from live instruction, such as that which is provided in bootcamps.

Learn Data Analytics with Noble Desktop

Now that you’ve decided to study data analytics, the next step is selecting the best course for you. Noble Desktop offers several training options in data analytics and the skills you’ll need to succeed in this field.

If you’re looking to work with Python, Noble’s Python for Data Science Bootcamp is an excellent choice. This rigorous class teaches students to apply their Python training to real-world datasets. You will learn how to use Python to perform statistical analysis and visualize data. Coursework covers topics like writing statements and expressions, working with lists, and creating variables. During this bootcamp, you’ll also tackle more complex Python skills, including how to work with loops, conditional statements, control flow tools, and dictionaries. By course completion, you’ll be able to use NumPy and Pandas to clean data and create advanced data visualization. A supplementary 1-on-1 private training session is included.

Noble Desktop’s Data Analytics Certificate is another excellent training option for aspiring data professionals. In this class, you’ll have the opportunity to work with a range of essential data analytics tools and software. Over the course of this program, you will complete eight shorter classes: Data Analytics Foundations, Excel for Data Analytics, Python for Data Science Bootcamp, Python for Automation, SQL Bootcamp, Python Data Visualization & Interactive Dashboards, Python Machine Learning Bootcamp, and Tableau Bootcamp. Certificate study includes instruction on how to use SQL to communicate with relational databases, visualize data in Tableau, use Python’s scientific libraries, and manipulate data in Excel. Eight 1-on-1 mentoring sessions are included with tuition.

If you’d like to focus your study efforts on learning to work with SQL, Noble’s SQL Bootcamp is for you. This hands-on bootcamp will prepare you to perform many relevant and useful SQL tasks, such as writing queries to extract information from relational databases, aggregating data, joining tables, and filtering results. During this live class, you will become familiar with how to work with subqueries, use functions with parameters, and code queries that can extract the exact information you’re seeking. Although this program focuses on PostgreSQL, the content covered can be applied to other databases, including MySQL or SQL Server. 

All Noble classes are taught in person in New York City and are also offered live online. Each course also provides learners with the option of a free retake for a full year.