In today's data-driven world, data analytics is critical in assisting businesses and organizations in determining the best course of action for their future undertakings and in developing corporate strategies. Data analytics aids in the extraction of useful insights by gathering, cleaning, and analyzing massive amounts of data, thereby establishing a target for attaining a certain goal. As a result, every industry is utilizing data analytics to boost revenue and market share, develop its business, remain ahead of the competition in a competitive market, and engage and delight its ever-growing customers.
The global data analytics market is growing at an unprecedented rate, and it is estimated to reach a value of over USD 346.33 billion by 2030. Hiring companies are scouting for skilled and experienced data analysts who can harness the data and derive significant insights.
So, if you desire to work in the data analytics domain, then obtaining a data analytics certification is a surefire way to achieving your career objectives. In this article, you will find a list of the different types of data analytics certifications available to choose from based on your technical aptitude and work experience that will help you attain your career goal.
The most popular data analytics certifications in 2023:
There are many certifications available for aspiring as well as seasoned data analysts who are looking to take their baby steps into the industry or trying to advance in their careers. below listed are some of the most popular certifications available that you can choose from, which are best suited to your target.
1. Google Data Analytics Professional Certificate
Google’s data analytical professional certificate is an excellent certificate program in a flexible schedule format that will help you learn in-demand skills that will expedite your career in data analytics in less than 6 months. The program, taught by Google experts, is spread over a series of 8 courses and is geared toward complete beginners with no prior experience. You will learn how to organize and clean data for analysis, execute calculations using spreadsheets, SQL, and R programming, as well as how to visualize and present data findings in dashboards, presentations, and commonly used visualization platforms.
What you will learn: Problem-solving, data cleaning, critical thinking, data ethics, and data visualization.
Platforms and tools you will discover: R programming, spreadsheets, SQL, Tableau, and presentations
Duration: The Google Data Analytics Certificate can be earned in less than 6 months of part-time study (less than 10 hours per week)
2. IBM Data Analyst Professional certificate
With IBM’s Data Analyst Professional certification, you will gain the in-demand skills and hands-on experience to launch a career as a data analyst in as little as 4 months. The program is beginner friendly with no requirements for prior experience or degree and can be learned at your own pace through a 9-course series, where you will master the most up-to-date practical skills and tools through hands-on labs and projects, which is required for a successful career as a data analyst. At the end of the program, you will develop a working knowledge of Python language for analyzing data using Python libraries like Pandas and Numpy, and invoke APIs and Web Services as well as learn how to visualize data and present findings using various charts in Excel spreadsheets and BI tools like IBM Cognos Analytics & Tableau.
Skills and tools you will learn: Excel spreadsheets, Python, Pandas, Jupyter Notebooks, Numpy, Data Visualization (DataViz), Pivot Table, SQL, IBM Cognos Analytics, Dashboard
Duration: The IBM Data Analyst Professional certificate can be earned in less than 4 months at 10 hours a week
3. Microsoft Certified: Power BI Data Analyst Associate
The Microsoft Certified: Power BI Data Analyst Associate is designed for subject matter experts who want to hone their expertise in Power BI to visualize and transform the data, create data models, and share assets. The certification requires one to possess knowledge of delivering actionable insights through data assessment as well as understanding data security, including row-level security and data sensitivity. To be a candidate for this certification, you should also be proficient at using Power Query and writing expressions by using Data Analysis Expressions (DAX). The certification can build your competence in data visualization, preparation, modeling, and analysis.
In order to be certified with Power BI data analyst certification, you must pass Exam PL-300: Microsoft Power BI Data Analyst with a score of 700.
4. AWS Certified Data Analytics- Specialty
The AWS Certified Data Analytics- specialty credential attests to one’s proficiency in gaining data insights using AWS data lakes and analytics services, thus developing critical skills in implementing cloud initiatives. This certification is intended for professionals with at least five years of experience in common data analytics technologies, along with two years of hands-on experience and the competence to design, build, secure, and maintain analytics solutions using Amazon Web Services (AWS). You must take and pass the AWS Certified Data Analytics - Specialty exam (DAS-C01) to obtain this credential, which includes 65 questions in either multiple choice or multiple response format that has to be completed in under 180 minutes.
5. CompTIA Data Analytics Plus certification
CompTIA Data+ is a vendor-neutral data analytics certification for individuals in their early careers who are responsible for establishing and supporting data-driven business decision-making. The CompTIA Data+ exam validates the holder's proficiency in transforming business requirements into data-driven decisions by mining and manipulating data efficiently along with basic statistical methods, as well as knowledge in analyzing complex datasets while adhering to governance and quality standards across the entire data life cycle.
To obtain this certification, you must pass a 90-minute exam with 90 questions with a score of at least 675 on a scale of 100-900. CompTIA suggests that candidates taking this test have 18 - 24 months of prior work in an analyst or reporting position where they have been exposed to databases, tools for analysis, statistics, and the basics of data visualization.
6. Certified Professional in Analytics (CPA) (CAP)
The Certified Analytics Professional (CAP) certification, which is vendor- and technology-neutral, is regarded as the gold standard in data science. The CAP certification validates the professional's competence in seven data analytics disciplines, as well as your ability to extract meaningful insights from difficult data, which is vital for anyone considering a career in data science and analytics. Having a CAP proves your exceptional analytical ability and competency. You must pass the Associate Certified Analytics (aCAP) Professional exam to obtain the CAP credential.
The CAP certification dictates that if you have a master's degree in that field, you must have three years of work experience in that field; if you have a bachelor's degree in that field, you must have five years; and if you have any other degree that is unrelated to analytics, you must have seven years.
7. Microsoft Certified: Azure Data Scientist Associate
The Microsoft Azure Data Scientist Associate certification highly emphasizes your capacity to implement and run machine learning workloads on the Azure cloud platform using data science and machine learning. This certification is a member of the Microsoft Azure family. Predictive analytics, computer vision, natural language processing, machine learning, and AI solutions are all covered in this entry-level certification. You must be proficient in a variety of related tasks, including installing and managing storage, managing identities and governance, deploying and managing resources, and developing and maintaining virtual networks.