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Your Guide to a Data-Driven Career

We provide reliable information and expert recommendations for educational and career pathways in data science, data analytics, and business analytics.

Whatever your background, we can match you with educational opportunities that can slingshot you into a new data job, whether you’re just breaking in or looking to level up.

data analytics market size chart

90 zettabytes (or 90 trillion gigabytes) of data were produced in 2019 and 2020, almost 12,000 gigabytes per person. A staggering number, to be sure, and one with a huge impact for businesses small and large. By 2030, Precedence Research estimates the data analytics market, currently worth around $54 billion, will grow to nearly $350 billion — larger than the size of the GDP of Vietnam.

statista number of graduates

The Increasing Demand for Data Professionals

Data-driven decision making and the job markets that feed it have never been more important for industries like finance, healthcare, ecommerce, and manufacturing. Data analysts are providing crucial insights for businesses about what happened in the past, why it happened, what might happen in the future, and what businesses should do about it. Data scientists are harnessing the power of artificial intelligence and machine learning to devise, develop, and deploy new tools and techniques for extracting insights from the big data sets produced by almost every instance of human activity. Business analysts are combining a business mindset with analytics skills to weigh in on bigger-picture business decisions such as cutting costs, increasing revenue, entering a new market, or initiating mergers and acquisitions.

In addition to these more general roles, we are witnessing the rise of specialized data professionals like business intelligence analysts, market research analysts, healthcare data analysts, and financial analysts who are combining industry expertise with data literacy to drive their areas forward.

Business intelligence analysts instead focus more squarely on developing intelligence tools such as reports and dashboards. Market research analysts leverage data analytics to better understand the consumers and competitors in a certain business space. Healthcare data analysts instead use data literacy to improve health outcomes. Finally, financial analysts analyze data to inform investment strategies, among other things.

New Educational Opportunities

The rising influence and ensuing demand for professionals skilled in data management, statistical analysis, machine learning, and data visualization has fueled an expansion in educational opportunities for those looking to get involved. From traditional bachelor’s and master’s programs to new certificate programs, short courses, and bootcamps, there have never been more options for someone looking to get data-savvy, regardless of their background.

This is particularly the case because so many programs are now being offered online. Between the embrace of remote-first education during the COVID-19 pandemic and employees’ increasing willingness to seek out upskilling opportunities that will allow them to move more quickly between jobs and industries, online courses have never been more popular, with new ones introduced every day. 

According to, almost 25,000 learners graduated from North American bootcamps in 2020, over ten times as many as in 2013. Globally, HolonIQ estimates over $10 billion was spent on micro- and alternative credentials in 2021, with this spending potentially doubling over the next 3–5 years.

remote student enrollment chart in 2022

Online study is also gaining a foothold in traditional universities and colleges. According to Urban Institute, master’s students studying online in 2016 made up almost one-third of the total number of master’s students, up from only 5% in 2000. Of the 1800 college students polled by in 2022, 60% of those who had experienced remote learning during the pandemic lockdowns were likely to seek out online learning opportunities in the future.

While online learners might miss out on a campus experience, studying online offers a high degree of flexibility. Courses are often self-paced or meet during the evenings or on weekends. This allows students to continue working or taking care of familial obligations while they build data skills, which can improve the financial calculus underpinning the decision to pursue or not pursue an educational pathway.

Making a Decision

The combination of new data-centric curricula and new methods of curriculum delivery can make finding the right program difficult. There’s simply so much that is new and relatively untested, especially for the kinds of programs that, like bootcamps, lack an established credentialing body. 

A further complicating factor is the presence of online program managers (OPMs) in the space. OPMs partner with brick & mortar educational institutions to develop online programs, bringing expertise in online curriculum development and student acquisition to complement the subject matter expertise and reputations of traditional colleges and universities. While these partnerships can produce stellar programs, in recent years politicians and journalists have probed the business practices of certain OPMs, with allegations that they might contribute to increases in student debt and utilize dissembling marketing practices.

Given all of this, how can prospective students know they are making the right choice?

At, our mission is to close this knowledge gap and increase consumer confidence so that we can start closing the larger education gap. By offering prospective students transparent information about the quality of the options out there, we believe we can set more aspiring data scientists, data analysts, and business analysts up for success down the road, which will end up benefiting us all.

The world’s leading data programs right at your fingertips

Our comprehensive guides and program recommendations for degrees, bootcamps, and short courses demystify the educational pathways out there and point you to the programs that are right for you.

Information you can trust

Each of our guides, explainers, and deep-dives is painstakingly researched and, where necessary, vetted by data experts.

No empty promises, just actionable insights 

We cut through the hype to give you a realistic picture of the different data fields and your chances in the job market, with practical steps to start moving forward.

Building a Data-Driven Career

But we don’t stop at educational program recommendations: we also want to support you in your career search and even once you’re on the job. That’s why we publish explainers on the different career paths out there and guest articles on the latest techniques and tools being used on the job by real data professionals. Our hopes are that you’ll see us as loyal guides for the total length of your data career: from your first course to your retirement.

Because let’s face it: building a career is difficult, especially if you are transitioning into a new field and building things up from scratch. And if you are transitioning, you want to make sure that it will be worth it — that your investment in education will return competitive compensation. Here’s the good news: data jobs generally offer compensation well in excess of the wages earned by the average American, which the US Bureau of Labor Statistics pegged at $45,760. Data analysts, for example, earn an average of $82,207 per year, while data scientists average $139,631 annually.

What accounts for data professionals’ lucrative compensation compared to the average American? And why do data scientists earn so much more than data analysts? In short: data skills.

Key Skills for Data Science, Data Analytics, and Business Analytics

While data science, data analytics, and business analytics require overlapping skill-sets, data scientists are typically far more adept at designing, developing, and deploying machine learning models. Data analysts and business analysts focus instead on leveraging existing analytics methods, the latter taking approaching data problems with more emphasis on business fundamentals.

Data Analytics, Business Analytics, and Data Science Skills

  • Computer science skills, including programming with Structured Query Language (SQL), Python, R, C++, and others

  • Data management skills, including date collection, data mining, data cleaning, and data storage

  • Statistical analysis skills, including regression analysis, factor analysis, cohort analysis, and others

  • Data visualization using tools like Tableau

  • Soft skills, such as teamwork, leadership, critical thinking, and communication skills

Data Science-Specific Skills

  • Advanced mathematics, such as linear algebra

  • Machine learning skills, including techniques like unsupervised learning, supervised learning, reinforcement learning, and deep learning

Find a match

Interested in building data science, data analytics, or business analytics skills and want to move forward, but don’t know where to start? Head to our program hubs for each to start browsing educational programs that can match your background and experience.

Or maybe you’re data sci-curious but need to learn more before deciding if — or how — to pursue a career. Our career hubs have all the information you need to learn more and feel more confident about your eventual choice.

Perhaps you’re already an active data scientist, data analyst, or business analytics professional but you’re looking to plug into the latest trends, industry gossip, and cutting-edge techniques. If this is the case, check out our field hubs.

Frequently asked questions

We’re a collection of professionals with experience in edtech, marketing, higher education, and the data economy looking to support the data job pipeline by providing expert-research, actionable information, and program recommendations to help individuals at all stages of their careers.

We partner with a number of educational providers to match interested learners with high-quality programs in data science, data analytics, and data visualization. When you click “Get Matched” and enter your contact information, we transmit this information to providers you match with so that their admissions representatives can reach out to you. We are compensated by the providers for making this introduction.

We use information you give to us and the information we collect through automatic data collection technologies to provide you with relevant information on educational opportunities and improve site experience for you and other users. We also disclose your information to certain third parties in accordance with our privacy policy.

Because of the boom in data science and analytics jobs, there are a lot of voices out there professing to have the best information for someone looking to break in. So why trust us? Often, you won’t have to: whenever possible we’ll show our work and point you to our sources. When we make judgment calls, we reach out to real experts to review and approve what we write. If an article is reviewed, you’ll see the expert’s name listed at the top. 

For our partnerships, we commit to transparency: while we might receive financial incentives for pairing interested users with these programs, we always disclose these arrangements prominently. We also don’t enter into partnerships with programs we wouldn’t be comfortable attending ourselves.

In addition to trustworthiness and transparency, we value realism and actionability. So many competitor sites out there promise prospective students astronomical salaries as data scientists or data analysts, but don’t really give them realistic paths to reach these peaks. What’s worse, many programs provide advice merely as a front to drive conversions and sell more leads to their partners.

We’re out to do something different. By maintaining a healthy cynicism about the data science education space but seeking out those programs that really can make a difference in students’ lives, we’re hoping to not only bring more smart and driven people into data science, data analytics, and data visualization positions, but reduce student attrition, unmanageable student debt, and, ultimately, dissatisfied consumers.

Want to learn more?

Data science, data analytics, and business analytics are quickly growing fields, and it can be difficult to keep up with the changes. At the same time, there is so much going on that it can be fascinating to read up on, even if you’re not yet sure where you might fit in. If you’re just interested in learning more, check out the following articles.

What is Data Analytics?

In this article, we introduce data analytics, including core types, techniques, and skills, then preview some exciting data analytics careers and lay out how to get started in a data analytics career.

The Most Popular Programming Languages for Data Science

Here, we lay out the pros and cons of the most popular data science programming languages and suggest how you should go about learning them.

What Does a Data Science Career Path Look Like?

Harvard Business Review named data scientist the “sexiest job of the 21st century,” but what does a data science career really look like?

Is a Data Science Bootcamp Worth It? What You Need to Know to Make Your Decision

In this article, we dive into the costs and benefits associated with data science bootcamps and give you tips for how to determine if one is right for you.

Our Guide to Data Analytics Careers

In this guide, we introduce data analytics, preview some exciting data analytics careers, and lay out some educational pathways to send you on your way.

Business Analyst vs Data Analyst: What’s the Difference?

Business analyst and data analyst are terms often used synonymously. In this explainer, we dive into whether there is a difference, and, if so, what it is.

Our Step-by-Step Guide to Landing a Data Science Job

Data science jobs are in demand and offer substantial salaries. In this article, we lay out the steps you need to land your first one.

Explore Data Science Scholarships

We've curated an up-to-date list of great opportunities that can make your data science journey easier — financially at least — plus information on how you can apply to each.

Become a contributor

At, we strive to always bring our readers the latest and most accurate information on educational pathways, industry happenings, and tools and techniques for data science, data analytics, and business analytics. To do so, we rely on readers like you: we are always on the lookout for new writers.

If you are in a data science, data analytics, or business analytics educational program or career and are interested in becoming a contributor, please reach out to tell us more about yourself and pitch us some ideas for guest pieces. You can learn more, including how we compensate our writers, on our about page. We look forward to hearing from you!