How to Pass the Google Cloud Professional Data Engineer Certification
I am a certified Google Cloud Profession Data Engineer now! I passed the certification exam in 14 days after failing it in the first attempt. In this blog, I will share how I passed the GCP professional cloud architect certification especially my lesson learned from the first attempt. I collected my learning path, study materials, and test experience immediately after the exam. So I hope the information I provided here may help others to earn this one of the most valuable cloud certifications.
Exam Difficulty Level
The exam is more difficult than the similar one in AWS – AWS Certified Data Analytics – Specialty exam. I usually got my IT certification in the first attempt. But this time I did twice. The big challenge is that you need to choose the best solution from all workable answers in some questions. At the time of writing this blog, the GCP Professional Data Engineer Certification exam is a two-hour exam with 50 questions. The questions in the exam focused on real scenario-based use cases and your hands-on experience in GCP.
Learning Path and Study Materials
There are no prerequisites for this exam. But I passed GCP Professional Cloud Architect (PCA) certification four months ago before this exam. The knowledge from GCP PCA did save me a lot of learning time of GCP PDE exam. The following is my learning path to prepare for this exam:
- Training courses: You can find many good structured online courses for this exam. Take the free trial opportunity of those courses to find the one fit with your learning style. I took Data Engineering with a Google Cloud Professional Certificate training path from Coursera. Pluralsight also offers the same training path. There are 6 Courses in this Professional Certificate training. These courses provide you comprehensive information on GCP, hands-on labs in Qwiklabs and sample exam questions. Take the benefit of the free enrollment option. Save PDFs of the slides from these courses to review them before the exam. At the time of writing this blog, Google Cloud also offers free training available for a limited time on Associate Cloud Engineer, Professional Cloud Architect, and Professional Data Engineer. Please also take advantage of this offer.
- Hands-on experience: This exam will expect you to not only understand Big Data and Machine Learning Fundamentals but also be able to design, build, operationalize, secure, and monitor data processing systems. So you should gain hands-on experience with Google Cloud free tier. Coursera and Pluralsight courses provide hands-on labs. I did all hands-on practice in Qwiklabs. You will face the exam questions very similar to the hands-on practice from Qwiklabs.
- Learning videos and Google cloud documentation: I collected the GCP Professional Cloud Architect Certification Learning Videos (for learning GCP knowledge) and Google Cloud Professional Data Engineer Certification Learning Videos. You can also learn each Google Cloud service from GCP documentation. I also provided the Last-minute Cheat Sheets for Google Cloud Professional Data Engineer Certification Exam that you can use them before your exam.
You will receive either Pass or Fail at the end of the exam. There is no official passing score from Google. It will take 7 to 10 days for Google to evaluate your remote test result before Google releases your certification information. If you failed on the first attempt then you need to wait 14 days to re-register for your next attempt and pay for each attempt. I registered the exam on the same day when I felt I was ready. Here is my lesson learned from the exam:
- You should have enough time to read and understand each question. So don’t rush in to complete the exam. It does have long description questions that are a little bit longer than you saw on Google sample questions. I did have two very similar sample questions in the first attempt and one sample question in the second attempt. So use Google sample questions as much as you can and try to understand the key points of these questions.
- If you’re stumped on something, don’t spend too much time on it. Just flag those questions for later review and select your best guess.
- If you failed on the first attempt like me, instead of spending time to blame yourself just write down all the topics/questions that you suspect you might be wrong. In my case, I wrote down the window and functions in DataFlow, difference between Kafka and Pub/Sub, BigQuery table access etc. for further learning. The exam will test your deep knowledge and your hands-on experience in big data analytics and machine learning. So even you have basic knowledge of GCP services or passed GCP professional cloud architect certification like me, you still need to deep diving into these topics. Please check my last-minute cheat sheets for more details.
Hopefully, my experience will help you to study more effectively. Good luck on your exam!
- Hands-on with DynamoDB
- AWS Data Warehouse – Build with Redshift and QuickSight
- AWS Relational Database Solution: Hands-on with AWS RDS
- Which is Right Hadoop Solution for You?
- Apache Hadoop Ecosystem Cheat Sheet
- Data Storage for Big Data: Aurora, Redshift or Hadoop?
- AWS Kinesis Data Streams vs. Kinesis Data Firehose
- Streaming Platforms: Apache Kafka vs. AWS Kinesis
- AWS Machine Learning on AWS Redshift Data
- Why Use AWS Redshift Spectrum with Data Lake
- How to Design AWS DynamoDB Data Modeling
- When Should Use Amazon DynamoDB Accelerator (AWS DAX)?
- Web Application with Aurora Serverless Cluster
- Top IT Certifications for 2018
- How I Passed AWS CSAA in 3 Months
- How to Pass AWS Certified Big Data Specialty
- AWS Elastic Beanstalk or AWS Elastic Container Service for Kubernetes (AWS EKS)
- How to Use AWS CodeStar to Manage Lambda Java Project from Source to Test Locally