In this blog post series, you will find some suggestions about how to get certified on the Google Cloud Platform.
There is no SAP on Google Cloud certification (yet), but we do have some excellent material to get started. Interested to learn more? You are invited to join the LinkedIn Special Interest Group (SIG) Questions? Please post as comment. Useful? Give us a like and share on social media. Thanks! Latest update: August 31, 2022 |
Google Cloud Certification Program
The Data Engineer is one of the professional-level exams with 3+ years industry experience recommended, including 1+ years on Google Cloud.
- For the program, see cloud.google.com/certification
For the argument why you might want to take up a certification (should you need any convincing, or want to get some funding from your manager), see
To promote its platform, Google has a number of programs to make it easier to get certified, see
| Sign up for a free exam voucher (September 2022) |
Professional Data Engineer
On the exam page, you find all the information you need about the exam, how to prepare, how to register, etc.
Exam Guide
The exam guide lists the topics you need to know. This is an extensive and comprehensive list which should be taken literally: you can expect questions about each of the points mentioned.
For the data engineer exam, the relevant Google Cloud products/services are
- Designing data processing systems, i.e. BigQuery, Cloud Composer, Cloud Dataflow, Cloud Dataproc, Apache Beam, Apache Spark and Hadoop ecosystem, Cloud Pub/Sub, Apache Kafka)
- Building and operationalizing data processing systems, i.e. Cloud Bigtable, Cloud Spanner, Cloud SQL, BigQuery, Cloud Storage, Cloud Datastore, Cloud Memorystore
- Operationalizing machine learning models, i.e. Cloud Machine Learning Engine, BigQuery ML, Kubeflow, Spark ML, Dialogflow, and the ML APIs
- Ensuring solution quality, incl. IAM, Monitoring
Sample Questions
The Sample Questions (20 questions) give an accurate indication of the type of questions you can expect.
Both the question and the answers can be quite verbose and sometimes very similar in wording. You just might need the full 2 hours allocated for real exam to answer the 55 question.
Online Courses
| The online courses mentioned below are a great way to get introduced and familiarise yourself with the content of the exam. However, just watching the videos will NOT suffice to pass the exam. |
Cloud Skill Boost (Qwiklabs)
To prepare for the exam, take the learning path (9 courses, 3 Quests).
The quests present a number of labs, showing you how to perform specific activities ending with a challenge where you need to apply those skills. Excellent training material.
Coursera
The same Google training courses are also available online/on-demand from Coursera, including some of the Qwiklabs hands-on labs. This is a paid service for a certificate of completion with frequent discounts and promotions.
The training consists of six 1-week courses with an exam study guide to wrap it up.
Note that although these courses will teach what the exam is about, it will NOT be enough to pass the exam. You need to study the documentation and other resources (see below).
Not to be missed is exam-prep course: Preparing for the Google Cloud Professional Data Engineer Exam
Pluralsight
The same courses are also available on Pluralsight. You can get a free 10-day trial when you sign up in case your company does not have a corporate subscription (SAP).
The learning path contains 17 hours of video content.
A Cloud Guru, recently acquired by Pluralsight, offers a different course. 20 hours of content with labs, quizzes, and a practice exam. Again, with a free 7-day trial.
Google Machine Learning Crash Course
Although only a handful questions are about machine learning in the exam (for this there is the Professional ML Engineer certification), you are expected to be familiar with the terminology and know when to use L1 or L2 regularisation, for example, when your model is over- or underfitting.
Study Guides
To complement online training, consider reading the study guide by Dan Sullivan. Well-written and comprehensive: gives you a good overall idea about all the material you need to study.
Dan has also published a course on Udemy with 6 hours of video and one practice test
| As mentioned by Dan in the introduction, as with the online courses, the book alone will NOT suffice to pass the exam. |
Not specifically targeted to the certification but on the topic is the more recent publication
- Data Engineering with Google Cloud Platform by Adi Wijaya (March 2022)
Documentation
In addition to the courses and labs, you will need to familiarise yourself with the documentation of the Google Cloud products covered in the exam (BigQuery, Bigtable, Cloud Composer, Dataproc, Dataflow, PubSub, ...)
As you can spent days just reading the docs for BigQuery, the challenge is to map the topic areas of the exam guide (see above) to the documentation.
Certified Directory
Once you get your certification(s), you can choose to be listed in the Google Cloud Credential Holder Directory.
When this article was first posted (Sep 2020), the directory had just tripled from 5,600 credential holders to 15,400 in ten months. Time of writing, there are close to 28K members of which 5,400+ data engineers.
Wait, There is More
For events, webinars, learning groups, and more, visit
For all GCP products, see
There are many articles posted about the certification, a good place to start is
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| Over the years, for the SAP HANA Academy, SAP’s Partner Innovation Lab, and à titre personnel, I have written a little over 300 posts here for the SAP Community. Some articles only reached a few readers. Others attracted quite a few more.For your reading pleasure and convenience, here is a curated list of posts which somehow managed to pass the 10k-view mile stone and, as sign of current interest, still tickle the counters each month. |
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