9 Data Analyst Certifications to Pursue (With Skills)

By Indeed Editorial Team

Published June 10, 2022

The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.

A data analyst uses technology tools and methods to examine data, gain valuable insights, and report results to interested individuals. If becoming a leading data analyst is part of your professional goals, consider earning in-demand certifications. By reviewing popular certifications for data analysts, you can select the best option to advance your career. In this article, we discuss why you might earn data analyst certifications, outline nine valuable certifications to pursue, and discuss essential skills and competencies for this career path.

Why earn data analyst certifications?

Earning data analyst certifications can help validate your analytics expertise. These credentials may also help you qualify for mid-level and senior roles. For example, if you have years of experience analyzing data, you can pursue an advanced certification to become a senior data delivery analyst. Consider your analytical qualities and career level to make an informed selection.

Related: How To Become a Data Analyst (With Essential Skills)

9 certifications to advance your data analyst career

Here are in-demand certifications you can earn as a data analyst:

1. CompTIA Data+ certification

Consider pursuing this entry-level credential if you want to validate your understanding of the analytics process. The CompTIA Data+ certification can help you learn to mine, manipulate, visualize, and report data. You can also develop your ability to apply statistical methods and analyze complex data sets. While there aren't certification requirements, gaining practical analytics experience for 18 to 24 months can help you pass the paid exam. CompTIA also offers certification resources, including study guides, instructor-led training, and examination preparation materials. This certification is generally valid for three years before CompTIA requires renewal through its continuing education program.

2. Microsoft Certified Power BI Data Analyst Associate certification

If you use Power BI to analyze data sets, consider becoming a certified Power BI data analyst associate. This credential can help validate your ability to prepare, model, and visualize data. It also covers your ability to deploy and maintain assets using Power BI. Microsoft recommends you understand data repositories and processes before pursuing this certification. You can also enrol in its instructor-led training course, follow available learning paths, and work on data analysis and visualization projects before taking the certification exam.

3. Microsoft Certified Azure Enterprise Data Analyst Associate certification

Azure is Microsoft's public cloud computing platform. If you use cloud services to analyze data sets, consider earning this certification. It can help demonstrate your ability to implement and manage data analytics environments. It also tests your ability to query, explore, visualize, and transform data and implement models. As an advanced certification, you typically require experience using Power BI and performing advanced data analytics.

4. Associate Certified Analytics Professional (aCAP) certification

With a master's degree and three years of professional experience, you can become an Associate Certified Analytics Professional (aCAP). Earning this certification requires you to follow all ethics guidelines and pass the paid exam. This evaluation typically covers business and analytics problems, methodology selection, data methods, model building, deployment, and life cycle management. It typically takes two months to study for the aCAP certification.

5. Certified Analytics Professional (CAP) certification

This certification can help verify your analytical skills and showcase your ability to apply advanced analytics solutions. After applying for the paid certification, you can use the CAP handbook and study guide for your exam preparations. Here are the experience and educational requirements to become a CAP:

  • Three years of experience with a master's degree

  • Five years of experience with a bachelor's degree

  • Seven years of work experience with any degree

6. Cloudera Data Platform (CDP) Generalist certification

This certification can help showcase your ability to use CDP for data analytics. It comprises a 90-minute exam with 60 questions on cloud system providers, network security, user authentication, and your analytics experience. If you're considering transitioning to data science, system architecture, data engineering, and software development, you may also pursue this certification.

7. Cloudera Certified Associate (CCA) Data Analyst certification

This entry-level certification can help demonstrate your experience analyzing data. It covers your ability to use data definition language (DDL) statements to structure data sets. For example, you can expect questions on creating tables, improving query performance, and altering tables. The CCA Data Analyst certification also evaluates your ability to use query language to transform outputs, prepare reports, and calculate sums and averages. The paid exam has a 120-minute limit and involves eight to 12 data analytics tasks on a large data set.

8. SAS Big Data Professional certification

You can pursue this certification if you want to validate your ability to use open source and SAS data management tools for statistical analysis. The credential requires you to pass two exams. While the first exam covers big data preparation, statistics, and visual exploration, the second involves data programming and loading. Upon completion, you can connect with the SAS certification community and showcase your ability to improve data quality for reporting and analytics.

9. Tableau Data Analyst certification

This entry-level certification can help showcase your ability to identify data for exploratory analysis and deliver actionable insights. Tableau offers an exam preparation guide and recommends you use it before applying for the certification. The paid exam has a 120-minute time limit and involves knowledge- and performance-based questions. The Tableau Data Analyst certification is valid for two years.

Read more: The 10 Most Valuable Certifications Today

Data analytics skills to develop

While earning relevant certifications, you can develop these skills to improve your employability:


Analytical skills describe your ability to observe, research, and interpret a topic and data set to develop ideas or solutions. For example, suppose you're working on a financial data set. You may use these qualities to understand how a customer's credit score may affect their interest rates. These skills can also help you identify patterns and evaluate your findings.

Attention to detail

Attention to detail is the ability to be thorough and mindful at work. Developing these skills can help you make conclusions from a data set. For example, showing attention to detail can help you remember to filter outliers or handle missing values before analysis.

Related: How to Be More Detail-Oriented (With Definition and Resume Tips)

Computer literacy

Computer literacy defines your ability to use computer systems to perform tasks. For example, checking for missing values might be easier using a computer function than scanning a data set manually. Similarly, you may apply your computer literacy skills to use cloud services if you require more computation power for analysis tasks.


Organizational skills describe your ability to use resources well. As a data analyst, developing these skills can help you arrange records for easy access and retrieval. You may also use these skills to prepare reports and communicate your findings effectively.


Interpersonal skills describe how you work and interact with others. Working as a data analyst often involves collaborating with technical professionals. For example, you may interact with a database administrator to access data records, communicate your findings to data scientists, and collaborate with researchers.

Read more: Interpersonal Skills: Definitions and Examples


Math skills describe your ability to make measurements and calculations of amounts and sizes. Working as a data analyst requires these skills to develop mathematical and statistical models and interpret results. For example, you might use math skills to interpret your results from decision trees or describe the confidence interval. A confidence interval (CI) is the range of estimates for an unknown parameter.

Read more: 18 Data Analyst Skills for Success

Data analytics competencies

Becoming competent in the following technical concepts can help you succeed as a data analyst:

  • Data visualization: This refers to the graphical representation of data records and information. It involves using charts, graphs, plots, and maps to showcase trends, outliers, and patterns in data sets.

  • Data modelling: This refers to the process of outlining data flows. It involves representing data records and showcasing the association between data objects and conceptual rules.

  • Programming: This is the activity of writing computer programs. It involves implementing logic to facilitate specific computing operations and functionality.

  • Database querying: This is the process of requesting data or information from a database table or combination of tables. You can also query a database to manipulate data records.

  • Statistical analysis: This refers to the science of collecting, exploring, and presenting large data records to discover underlying patterns and trends.

  • Regression analysis: This is the collection of statistical methods for estimating the relationships between a dependent variable and independent variables.

  • Data cleaning: This is the process of fixing, removing, or correcting data records before analysis.

Please note that none of the companies, organizations, and institutions mentioned in this article are affiliated with Indeed.

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