Our Guide to Data Analyst Certificates and Certifications

The US Bureau of Labor Statistics foresees 23% growth in the “Operations Research Analyst” — or data analyst — market over the next decade, with an additional 24,000 jobs up for grabs. Those landing these jobs can expect above-average compensation: the BLS pegs the median salary for someone in one of these roles at $82,360, well above the $58,260 that they estimate the average American earned in 2021.

Whether you’re just at the beginning of your working life and contemplating which direction to go in or you’ve already been working for a while but are looking for a new challenge, data analyst certifications offer a great way to gain the skill sets needed to succeed in this exciting and lucrative career path, as well as an accolade to put on your resume that will appeal to recruiters.

In this article, we’ll dive deeper into what exactly a data analyst does, discuss the reasons to pursue  a data analyst certification or certificate, and then present our picks for the best programs out there to help you choose the best one for you.

What is a data analyst?

Data analyst is a title that’s common across different business verticals — so the day-to-day of two data analysts at different companies might look very different. Typically, however, a data analyst gathers data and readies it for analysis, and then analyzes it to yield business insights that the analyst will communicate to relevant stakeholders, often through data visualizations.

One of the more outwardly famous products a data analyst touches is the “Spotify Wrapped” end-of-year playlist recap. It uses the data of millions of users to personalize and visualize their listening patterns.

What are data analytics?

Data analysts work within the larger field of data analytics, though the terms data analysis and data analytics are frequently used interchangeably. There are four main types of data analytics that are important to keep in mind: descriptive, diagnostic, prescriptive, and predictive.

Descriptive data analytics

Descriptive data analytics involve the analysis of historical data to answer the question, “What happened?” In retail, companies employ descriptive data analytics for tasks like tracking inventory and sales.

Diagnostic data analytics

Diagnostic data analytics involve the analysis of data to answer the question, “Why did this happen?” In marketing, diagnostic data analytics can be employed to help understand why some campaigns are more successful than others.

Prescriptive data analytics

Prescriptive data analytics involve analyzing data to answer the question, “What should we do next?” In logistics, prescriptive data analytics are becoming more and more important as companies like Amazon seek to deliver goods to millions of customers as efficiently as possible.

Predictive data analytics

Predictive data analytics involve the analysis of data to answer the question, “What might happen in the future?” In manufacturing, companies frequently employ predictive data analytics to predict future buying patterns and manage their supply chains accordingly.

What’s the difference between data analytics and business analytics?

Another distinction that can be confusing is the distinction between data analytics and business analytics. Google “data analytics vs business analytics” and you’ll find dozens of articles all telling you the definitive difference. But the truth is, oftentimes the work being done under the name of business analytics or business intelligence is no different than what data analysts do. This holds especially true for smaller companies where employees will necessarily have a broader set of responsibilities.

At larger companies, you might start seeing a business analyst start focusing more squarely on developing insights that will directly contribute to increasing a company’s revenues, decreasing its costs, expanding its market, or entering a new one, while a data analyst’s work might focus more on the day-to-day operations of the organization. In this case, a business analyst or business intelligence expert will certainly need to have a certain level of business acumen. But even at enterprise companies, these distinctions will often not be terribly clear.

What’s the difference between data science and data analytics?

Another one we hear a lot about is the distinction between data science and data analytics. While there is also overlap between these two, we believe there is a meaningful difference:

Data analytics concerns the tools and techniques surrounding the process of data analysis. Often, but not always, data analytics professionals will use existing tools and techniques on existing databases.

Data science, on the other hand, concerns the development and deployment of new tools and techniques and new ways to gather data for analysis. The analytics involved in data science will thus likely be more advanced and will frequently involve machine learning. Oftentimes, data analysts and other data analytics professionals will employ methods and tools developed by data scientists. If you’re interested in data science, check out our articles on:

Why get a data analyst certificate or certification?

What does it mean to be a certified data analyst these days? Who are these programs for, and what can they get you? How do they improve on traditional higher education, and what’s the difference between a certificate and a certification?

Let’s start off by dispelling some myths, the first of which being that there is really any such thing as a certified data analyst. While many educational providers offer certificates and certifications, being a “certified data analyst” simply isn’t the same as being a board-certified doctor, a bar-certified lawyer, a certified financial advisor (CFA), or a certified public accountant (CPA). 

These credentials just mentioned are administered centrally by official professional organizations and oftentimes carry legal weight. To achieve certification, applicants have to pass standard exams and other forms of peer review.

A data analyst or data analytics certificate or certification is decentralized, specific to the educational provider granting it, and doesn’t bring with it any affordances other than signaling to potential employers that the holder has successfully completed a course of study. Accordingly, a data analyst or data analytics certificate or certification is only as good as the organization granting it.

Certificate or Certification?

While you won’t always see a consistent difference in how these terms are used out in the field, in general a certificate attests to the completion of an educational program and a certification the satisfactory completion of an exam testing a skill or skill set. Notable examples of the later include Microsoft’s Power BI Data Analyst Associate certification, the AWS Data Analytics certification, the CompTIA Data+ certification, and the Cloudera Certified Associate Data Analyst credential.

The Upshot?

While it’s true that data analytics certificates and certifications aren’t accredited or granted by any centralized body, we mention this not to dissuade you from pursuing a data analytics certificate or certification, but rather ensure that you are fully informed about what it means to do so. These credentials, even if they are different from other professional credentials, do offer aspiring data analysts important advantages that, if fully understood, can be quite advantageous. Here, we will focus on the vetting a data analytics credential can signal to potential employers, the skill sets that accompany the credential, and the cost and convenience.


It might hurt to read, but it’s true: employers don’t always care what certifications or certificates their data analyst applicants have. Instead, they care about what these applicants are able to do (more on this soon).

But in certain cases, one of these credentials can help a non-traditional candidate land an interview when the contents of their resume would otherwise have them tossed in the “Reject” pile. 

Take, for instance, Sarah, who studied French Film and Cultural Studies at Vassar College and hasn’t yet held a data analytics job. Upon seeing Sarah’s application for a data analyst position, a recruiter would probably assume that Sarah had little to no experience in quantitative reasoning or programming and not give it another glance. But a data analytics certificate might get Sarah’s application a second glance, a skim of the cover letter, a perusal of the resume. 

Or, for another example, take Thom, an IT professional looking to transition into data analytics. A recruiter would likely be happy to see Thom’s extensive experience working with computers and knowledge of programming languages, but would wonder if he was ready to step up to a heavy analytics role. Here again, a data analyst certification could help convince the recruiter that Thom might be ready — or at least ready enough to warrant a 10-minute screening call.


But these are fringe cases — the biggest advantage of a data analyst certification is the skills that are taught or certified! To get your name on that digital certificate or certification, you will have to successfully demonstrate that you have learned the materials, successfully put together your own capstone project, or pass an exam to demonstrate your handle on a data analytics skill set.

Skills taught and tested for data analytics certificates and certifications include:

Programming skills and other tools, including SQL, Python, R, Tableau, SAS Enterprise Miner, and Excel

Statistical analysis, including linear regression and predictive modeling

Key data analytics processes, including data collection, data cleaning, data mining, and data visualization

Advanced concepts, including machine learning, data ethics, big data, and introductions to data science 

Soft skills, including project management and decision-making

Cost and Convenience

Many seeking to break into data analytics don’t want to spend the time or money needed for a four-year degree in statistics, computer science, or finance. With a data analyst certificate program or certification, you have another option that is substantially less expensive (often 10–100x less!) and allows them to study online on their own time. This is especially advantageous if you aren’t yet sure you want to go down the data analytics path but are willing to invest in learning more.

Alternatively, if you want to dive head-first into data analytics with a four-year degree, check out our recommendations for data analytics bachelor’s programs. If you already have an undergraduate degree and would rather seek a master’s degree than a certification, our recommendations for data analytics master’s degrees and business analytics master’s degrees will be helpful.

Our Picks for Best Data Analyst Certificate and Certification Programs

What’s our approach?

Online, you can find countless sites purporting to rank the best data analyst certificate and certification programs. Often, they’ll support their rankings by laying out different criteria by which they evaluate and order the programs they feature, separating the “best” from the “rest.” 

But while publishing ranking methodologies does lend some objectivity to their program rankings, these sites are missing the bigger issue: ranking in the first place, identifying the “best” programs, presumes that just one kind of student is seeking a data analytics credential.

For our picks, we’ve foregone ranking and focused instead on pointing interested aspiring data analysts to the programs that will deliver — to varying degrees — the vetting, skills, and cost and convenience advantages that we believe comprise the value of data analytics certifications and certifications. Our hopes are that interested individuals will be able to find something that works for them.

google logo of the G

Google’s Data Analytics Certificate

Google’s Data Analytics Certificate aims to teach students job-ready skills to help them land an entry-level job with one of the 150 employers in an employer consortium that includes SiriusXM, Snapchat, Target, and Verizon. Students learn core data analytics skills over 7 courses focusing on topics like data cleansing, data analysis, data visualization, and R programming, before applying these skills through a hands-on capstone project.

  • Length: 6 months, with under 10 hours of study per week

  • Modality: Self-paced, online

  • Prerequisites: None

  • Syllabus Highlights: “Ask Questions to Make Data-Driven Decisions,” “Analyze Data to Answer Questions,” “Share Data Through the Art of Visualization,” “Data Analysis with R Programming”

  • Reported Outcomes: 75% of graduates report career improvement
    Cost: $39/month of attendance on Coursera

Cornell-University seal

Cornell’s Data Analytics Certificate Program

Cornell’s Data Analytics Certificate Program aims to give students who have a basic understanding of statistics a usable foundation in business analytics. Through three courses focused on data visualization, data-driven decision making, and predictive analytics, students learn to build dashboards that monitor key performance indicators (KPIs), develop incisive business questions, and create regression models that can predict the future.

  • Length: 9 weeks (3 3-week courses), 3-5 hours per week

  • Modality: Self-paced, online

  • Prerequisites: Statistics

  • Syllabus Highlights: “Understanding and Visualizing Data,” “Implementing Scientific Decision Making,” “Using Predictive Data Analysis”

  • Reported Outcomes: None reported
    Cost: $2,625

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Columbia Engineering Data Analytics Bootcamp

Columbia Engineering’s Data Analytics Bootcamp offers courses in Excel, Python, databases, and machine learning, as well as a final project that students are able to collaborate on with their peers. Throughout the bootcamp, students have access to academic and career support, including a Career Engagement Network that helps students prepare their resumes and portfolios and practice interviewing.

  • Length: 24 weeks, part-time (9 hours of live classes per week, 20+ hours of homework per week)

  • Modality: Live, online

  • Prerequisites: None

  • Syllabus Highlights: “Excel crash course,” “Python data analytics,” “Machine learning and other advanced topics”

  • Reported Outcomes: None reported, though positive testimonials

  • Cost: $14,745

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Microsoft Certified: Power BI Data Analyst Associate

Microsoft’s Data Analyst Associate certification program is more narrow in scope than the other certifications we are highlighting, focusing on Microsoft’s Power BI software, but it covers many of the same skills — data preparation, data modeling, data visualization — as the other certifications on the list at a fraction of the cost. Students are able to access the curriculum for free and need to pay just $165 to take the certification exam. In general, this course would be best for someone who already has experience as a data analyst and is looking to explore new software.

  • Length: Self-paced

  • Modality: Self-paced, online

  • Prerequisites: None

  • Syllabus Highlights: “Getting started with Microsoft data analytics,” “Model data in Power BI,” “Visualize data in Power BI”

  • Reported Outcomes: None reported

  • Cost: $165 for certification exam