This post is about my journey of getting GCP Data Certification in 3 weeks. It was not difficult to get the certification in 3 weeks, but it wasn’t easy either. All I needed to have was the dedication and will power to follow my daily study schedule.
Being a Consultant at Servian, I get involved in multiple digital and data projects where my role varies from being a full stack software developer to a ETL Data Engineer. But never worked with the Google Cloud Platform.
Servian, being a consultancy domain company, always encourages its employees to keep learning new things and get as many certifications as they can. So, I thought of getting my GCP Professional Data Engineering Certification. For almost 4 months, I just thought about taking it up but never really started studying for it. I think it’s the phase of every passionate individual where they want to do something but can’t find time for it. Out of the blue, just to avoid my procrastination, I booked my GCP Data Engineer exam, because I don’t know about passion but fear does make you do things.
Step 1: Planning
It wasn’t easy to study after working for 9 hours. And I knew that success always comes at a price.
So, I tested multiple daily schedules for studying after my work.
Plan A: First and most common one which didn’t work for me was to immediately start studying after arriving home from work. Even though I used to study with total concentration, I wasn’t receptive to new concepts.
Plan B: To make myself productive, I created plan B which helped me not only with GCP preparation but also with other piled up topics.
6.00 pm — 6.30 pm: change and have dinner.
6.00 pm: return from work
6.30 pm — 7.30 pm: Sleep (don’t forget to wake up :-P)
8.00pm — 11.45 pm: Study
The above plan doesn’t seem intimidating at first but it did torture me for a couple of days.
Enough story, now time for some real stuff.
Step 2: Execution
I gathered an ample number of tutorials but I was confused about where I needed to start from, as there were a lot of topics to cover.
But the question is — do we need to study everything for the Data Engineer Certification?
Short Answer: Depends. Because for certain topics, in-depth knowledge is necessary and for certain other topics, a high-level overview will suffice.
Read Article by Kayleigh Rix for more information.
GCP Exam question topics:
• Storage (20%),
• Big Data Processing (35%),
• Machine Learning (18%),
• case studies (same as sample case studies 15%) and
• others (Hadoop, security, stackdriver about 12%).
Week 1: Train yourself
Data Engineering on Google Cloud Platform Specialization on Coursera is the best first step and helps to prepare for about 70–75% of the total exam content. It has a 7-day free trial and if you are consistent with your schedule you can complete it within the allotted time. It’s important to understand the labs because questions asked on GCP exams aren’t straight forward.
We will come back to the other 25–30% later in the post.
Week 2: Test & retrain yourself
Once you complete the Coursera course then it’s time to test your knowledge.
Attempt sample case study. It’s fine if you are not able to get it in the first shot. It’s common and the same has happened to me. Just try to at least understand the case study expectations and break down the task if possible.
Also, attempt GC official sample exam questions to get used to the type of questions expected to be in a real GCP exam and keep note of the unknown topics and incorrectly answered questions.
Now, Coursera has an amazing course on Preparing for the Google Cloud Professional Data Engineer Exam. It walks you through the sample solutions for sample case studies and also provides high-level knowledge of GCP products required to get GCP DE certified.
We still lack those 25–30% of the concepts which majorly belong to IAM, Machine learning and Hadoop Ecosystem (Spark, Beam, Pig, Hive, Kafka, Flink, Sqoop, MapReduce, HDFS vs GFS, Oozie). There is an excellent course on Udemy for GCP Complete Guide which helps you to go through the selected topics and helps gain a good amount of knowledge on those topics of which you are unsure.
If you can’t afford Udemy, then go through the Google Cloud Next video on youtube. It’s good to visit as many topics as you can, but don’t forget to go through the topics like Security, Dataprep, Hadoop Ecosystem, BigQuery, Dataflow, Dataproc etc.
Week 3: Performance tuning
As of now, you should be familiar with all topics and finally, it’s time to hypertune your knowledge parameters.
Start reading sample implementation for Spotify and also the best practices for GCP products.
- Cloud SQL
- Cloud Spanner
- Apache Beam
for more topics click here
I hope you guys have prepared notes for last minute revision. If not then don’t worry, just say thank you to who did the hard work for us.