Compare certifications · Updated 16 September 2026
Google Data Analytics Certificate vs PL-300: cost, hours, pass rates and which to take
Google Data Analytics Professional Certificate against Microsoft Certified: Power BI Data Analyst Associate (Exam PL-300), from the issuing bodies' own fee schedules.
The Google Data Analytics Certificate costs $147 to $294 all-in and takes 180 to 240 study hours; the PL-300 costs $165 to $350 and takes 40 to 90 hours. The Google Data Analytics Certificate is worth it as a curriculum if you are starting from zero and will follow it with your own portfolio projects; it is not worth it as a credential, because hiring managers see a great many of them and screen on evidence of work instead. PL-300 is worth it if you work in or want to work in a Microsoft-shop organisation where Power BI is the reporting layer, because at USD 165 and 40 to 90 hours it is the cheapest proctored credential an analyst can hold; it is not worth it if your employer runs Tableau, Looker or a warehouse-and-dbt stack.
| Google Data Analytics Certificate | PL-300 | |
|---|---|---|
| Issuing body | Google (delivered on Coursera) | Microsoft |
| Exam fee | USD 49 per month on Coursera in the US and Canada after a 7-day free trial, so roughly USD 147 at a three-month pace or USD 294 at Google's suggested six-month pace; Coursera financial aid can reduce this to zero | USD 165 in the United States (price varies by the country or region in which the exam is proctored, plus local tax) |
| All-in cost | $147–$294 | $165–$350 |
| Study hours | 180–240 | 40–90 |
| Calendar months | 3–6 | 1–3 |
| Levels / exams | 1 | 1 |
| Pass rate | there is no pass rate to quote: the programme is graded coursework with no proctored exam, and Google publishes no completion rate | Microsoft does not publish pass rates; the passing score is 700 on a scale of 1 to 1,000 |
| Format | nine self-paced Coursera courses of video, readings, hands-on labs and graded quizzes, ending in a capstone case study, with no proctored exam | 100 minutes, roughly 40 to 60 items including interactive case studies and drag-and-drop tasks, proctored at Pearson VUE or online |
| Prerequisites | None. No degree, no prior analytics experience and no programming background are required; you need a computer and a Coursera account. | None formally. Microsoft expects proficiency with Power Query and DAX and experience gathering requirements from business stakeholders; Power BI Desktop is free to practise on. |
| Renewal | None: the certificate does not expire, carries no maintenance fee and needs no continuing education. Cancel the subscription when you finish. | Free, every 12 months, through an unproctored open-book assessment on Microsoft Learn taken within six months of expiry. |
| Pay impact | Google and Coursera report that 75% of US certificate graduates report a positive career outcome - a new job, promotion or raise - within six months of completion, and cite over 270,000 open US jobs in data analytics with a median entry-level salary of USD 97,000 (Lightcast job postings data). Note these are the provider's own figures on self-selected graduates, not an independent survey. source | PL-300 does not appear in Skillsoft's top-paying certification rankings, which are dominated by senior cloud and security credentials. Skillsoft's IT Skills and Salary research does find that technology professionals who earn new certifications and skills report higher pay year over year, and Power BI skills are among the most commonly requested in analyst job postings; treat PL-300 as a skills signal for analyst roles rather than a salary premium in its own right. source |
| Careers that use it | Data Analyst, Financial Analyst, Product Manager, Data Scientist | Data Analyst, Financial Analyst, Product Manager, Management Consultant |
| Fees checked | September 2026 | September 2026 |
Is the Google Data Analytics Certificate worth it?
This is worth it as a curriculum, not as a credential. For someone with no analytics background it solves a real problem - what to learn, in what order - for about USD 150-300 and three to six months of evenings, and the capstone gives you something to show. If you are in operations, marketing, finance or support and want to move toward a data role inside your current company, it is close to ideal: cheap, fast, and directly applicable to work you already touch. Coursera financial aid can make it free. It is not worth treating as a job guarantee. Hiring managers see a great many of these certificates and mostly ignore them; what gets interviews is the portfolio you build afterwards and evidence you can answer a messy business question with real data. The programme also teaches R and Tableau, whereas most entry-level analyst postings ask for SQL, Excel and Power BI or Looker, so plan to add SQL depth and a BI tool. And be sceptical of the '75% positive career outcome' figure - it is Google's own self-reported number from graduates who opted into a survey, not independent evidence. Treat this as the first three months of a twelve-month plan.
Is the PL-300 worth it?
PL-300 is one of the best cost-to-benefit certifications for analysts. At USD 165, roughly 40 to 90 hours of study and free annual renewal, it is cheap in money, time and upkeep, and it certifies a skill enterprises actually buy: Power BI is the default BI layer in Microsoft-shop organisations, which is most of the mid-market and a lot of the enterprise. It is particularly good for finance, operations and consulting people who already build Excel models and want a credible reason to be handed reporting work, and for junior analysts who want something concrete on a thin CV. Unlike a completion certificate it is a proctored exam, so it carries more weight than a MOOC badge. It is not worth it if your organisation runs on Tableau, Looker or a modern warehouse plus dbt stack, where Power BI is not the currency; if you are targeting data engineering or data science, where SQL, Python and pipeline work dominate; or if you already build production Power BI semantic models daily, in which case the badge just confirms what your work already shows. The exam also skews toward the tool's own UI and DAX syntax, so it certifies Power BI fluency rather than analytical judgement - pair it with SQL and a portfolio.
Google Data Analytics Certificate vs PL-300 FAQ
Which costs more, the Google Data Analytics Certificate or the PL-300?
All in, the Google Data Analytics Certificate runs $147 to $294 and the PL-300 runs $165 to $350, including membership, required education, study materials and one exam sitting. Exam fees alone: USD 49 per month on Coursera in the US and Canada after a 7-day free trial, so roughly USD 147 at a three-month pace or USD 294 at Google's suggested six-month pace for the Google Data Analytics Certificate and USD 165 in the United States (price varies by the country or region in which the exam is proctored, plus local tax) for the PL-300, checked September 2026 and September 2026 against the issuing bodies.
Which takes longer to study for, the Google Data Analytics Certificate or the PL-300?
Candidates report 180 to 240 study hours over 3 to 6 months for the Google Data Analytics Certificate, against 40 to 90 hours over 1 to 3 months for the PL-300. there is no pass rate to quote: the programme is graded coursework with no proctored exam, and Google publishes no completion rate. Microsoft does not publish pass rates; the passing score is 700 on a scale of 1 to 1,000.
Should I take the Google Data Analytics Certificate or the PL-300 first in 2026?
The Google Data Analytics Certificate is worth it as a curriculum if you are starting from zero and will follow it with your own portfolio projects; it is not worth it as a credential, because hiring managers see a great many of them and screen on evidence of work instead. PL-300 is worth it if you work in or want to work in a Microsoft-shop organisation where Power BI is the reporting layer, because at USD 165 and 40 to 90 hours it is the cheapest proctored credential an analyst can hold; it is not worth it if your employer runs Tableau, Looker or a warehouse-and-dbt stack. Prerequisites differ: None. No degree, no prior analytics experience and no programming background are required; you need a computer and a Coursera account. For the PL-300: None formally. Microsoft expects proficiency with Power Query and DAX and experience gathering requirements from business stakeholders; Power BI Desktop is free to practise on.
Who asks for the Google Data Analytics Certificate versus the PL-300 by name?
No employer requires the Google Data Analytics Certificate by name, and no analyst job posting screens on it. It is most useful to people already inside operations, marketing, finance or support who want an internal move toward reporting work, and graduates can apply through Google's employer consortium of more than 150 United States companies. Employers that name PL-300 in postings are concentrated in Microsoft-shop enterprises and the mid-market: finance and operations teams, insurance, healthcare administration, manufacturing, public sector bodies and the consultancies that build Power BI reporting for them.