I wrote the Google Cloud Platform (GCP) Professional Data Engineer (PDE) exam on December 27th and was relieved to see a ‘Pass’ on the screen after the exam. I received the official certification on December 29th. However, before sending your official certification, Google further checks your examing conditions and results.
A bit about me
I've been in tech for about two years and recently moved from Cloud Engineering to the Data Engineering teams in my company. One of my projections was to become a certified GCP and Azure Data Engineer in the first six months. I passed the PDE after three months. This article highlights my preparation process and the resources I used as well as answers to some of the questions I've received.
The Exam Experience
The online proctored exam was scheduled for noon on December 27th. I was prepared and checked in about 20 minutes early. However, the exam didn’t start until 12:48 pm. I am guessing the end of the year is a busy time for Kryterion. I restarted my PC once because the LockDown browser got stuck for a few minutes, and I had to check in again. Asides from the initial delay, the exam went smoothly.
I had 50 scenario-based questions with 2 hours to answer them all. The time was enough to go over the questions again. Scenarios on Identity and Access Management (IAM), Bigquery, dataflow, storage and database solutions technology, Pub/Sub and machine learning.
Preparation and Resources
I spent at least two hours every day for about two months preparing for the exam using several resources.
I participated in a cohort-based eight weeks guided learning program organised by Google - The PDE Get Certified program. I had access to Cloud Skills Boost, a dedicated cohort coordinator, technical trainers, and all my questions were answered.
I completed most courses in Data Engineering, Data Analyst, and Machine Learning learning paths on Cloud Skills Boost and practised all hands-on labs. The labs helped me gain practical experience with GCP.
I attended a 6-week “Road to certification” training session hosted by GDG Berlin and Munich for the Professional Data Engineer exam. The training was interactive and informative, with lots of practical use cases shared by data engineers.
I reached out to Amarachi Ogu because she recently passed the exam.
However, these resources weren’t enough to pass the PDE exam. Here are some in-depth resources I used:
Studied the Professional Data Engineer Certification Guide to get a breadth of topics.
The data analytics section of GCP Documentation.
Read many articles from folks who passed the PDE exam, Sathish VJ, Kshitij Bhadage.
I watched a few videos on GCP and took the practice exam for the PDE exam on Cloud Academy; it’s helpful to note that I failed every single attempt.
I saw this Youtube video by Dan Sullivan a week before the exam, and I took meaningful notes. It sums up everything you need to pass the exam and details like IAM policies for data analytics service.
Choosing the right GCP service for a scenario.
Studying became much more enjoyable when I could map GCP services and the right business solutions. Here is a post from GCP that shows the differences between BigTable and BigQuery - link. Understanding what each data analytics service does at a basic level is helpful. For instance:
BigQuery and BigTable are similar only because they have Big in their names but provide different big data solutions.
Dataproc for Hadoop ecosystem workloads (This is a semi-IaaS solution because you can manage the compute engines yourself after the cluster has been created).
BigQuery for serverless data warehousing with SQL support.
Google Cloud Storage is a data lake because it offers storage for unstructured data.
Cloud Spanner and Cloud SQL for relational databases for global and regional workloads, respectively.
Dataflow for batch and streaming data pipelines.
Cloud composer as a managed service implementation of Apache Airflow.
2023 Certification Plans
I already scheduled the GCP Database engineer exam because of its overlap with the PDE exam. I will also take the Azure Data Engineer Associate exam and the AWS Certified Data Analytics - Specialty. I plan to be a multi-cloud certified Data Professional in 2023.
Someone asked why I took the GCP PDE certification first.
I was presented with learning opportunities that I couldn’t say no to. After all, free learning requires time and dedication, which I was willing to give.
My note while prepping for the exam, at this time, I knew I was struggling with data streaming, hence the "concentrate more on streaming".
Finally...
Passing the PDE is a good way to end the year. I am happy I could achieve the cert.
Thank you so much for reading. Wishing you a prosperous new year!