How I Passed the Google Cloud Professional Data Engineer Certification Exam

Without recommended 3 years of practical experience

In anticipation of the start of classes at the Data Engineer course , we want to share with you a translation of one very interesting story that will probably be useful to future engineers. Go!


Google Hoody: Wearing. Serious working facial expression: present. Photos from the video version of this article on YouTube .

Note. This article is about the Google Cloud Professional Data Engineer certification exam until March 29, 2019. There have been some changes after this date. I included them in the "Advanced" section.

So, you want a new hoodie, like on my cover? Or are you planning on getting a Google Cloud Professional Data Engineer certificate and are wondering how to do it.

In the past few months, I have been taking courses along with using Google Cloud to prepare for the exam for a professional data engineer. Then I tried to pass it and passed it. And a few weeks later my hoodie was delivered. Certificate came faster.

This article will list a few things you might want to learn and the steps I took to get my Google Cloud Professional Data Engineer certificate.

Why would you like to qualify for Google Cloud Professional Data Engineer?

Data is everywhere. And knowledge of how to create systems that can process and use data is in demand. Google Cloud provides the infrastructure for building these systems.

You may already have the skills to use Google Cloud, but how do you demonstrate this to your future employer or client? There are two ways: a portfolio of projects or certification.

The certificate tells prospective clients and employers: “I have the skills, and I made an effort to get accreditation.”

A brief description from Google sums up.

Demonstrate your skills in designing and creating data processing systems, as well as creating machine learning models on the Google Cloud Platform.

If you don’t have the skills yet, getting acquainted with certification training materials means that you will learn all about how to create world-class data processing systems in Google Cloud.

Who would like to qualify for Google Cloud Professional Data Engineer?

You saw the numbers. The cloud is growing. It is already here and is not going to go anywhere. If you have not seen the numbers, believe me, the cloud is growing.

If you're already a data specialist, data engineer, data analyst, machine learning engineer, or looking for a career path in the data world, Google Cloud Professional Data Engineer certification is for you.

The ability to use cloud computing is becoming a requirement for any data-oriented position.

Do you need a certificate to be a good data engineer / data set / machine learning engineer?

Not.

You can still use Google Cloud to work with data transfer solutions without a certificate.

A certificate is just one way to validate existing skills.

How much is it?

The exam costs $ 200. If you fail, you will again have to pay for a new attempt.

Possible costs associated with preparatory courses and the use of the platform itself.

Platform costs are fees for using Google Cloud services. If you are a sophisticated user, you are already aware of this. If not, and you are just getting acquainted with the training materials described in this article, you can create a new Google Cloud account and meet the limits of 300 dollars that Google offers when registering.

We will move on to the cost of the course in a second.

How long is the certification valid?

2 years. After that, you will need to take the exam again.

And since Google Cloud is developing every day, it is likely that what is required for the certificate will change (as I found out, it has already changed by the time I started writing this article).

What do you need to prepare for the exam?

Google recommends over 3 years of industry experience and over 1 year of developing and managing solutions using GCP for professional certification.

I did not have any of the above.

From strength to 6 months of relevant experience. To make up for the shortage, I used a combination of online training resources.

What courses have I taken?

If you are just like me and you do not have recommended requirements, you can take some of the following courses to improve your skills.

The following courses are what I used to prepare for certification. They are listed in order of completion.

I have indicated the cost, timing and usefulness for passing the certification exam for each.



Some of the great online resources that I used to train for the exam. In order: Cloud Guru , Linux Academy, and Coursera .

Coursera Data Engineering on Google Cloud Platform

Price : $ 49 / month (after a 7-day free trial)
Time: 1-2 months, 10+ hours per week
Usefulness : 8/10

Data Engineering on Coursera’s Google Cloud Platform was created in collaboration with Google Cloud.

It is divided into five sub-courses, each of which takes about 10 hours a week of study time.

If you are not familiar with data processing in Google Cloud, this specialization will increase your level from 0 to 1. You will pass a series of practical exercises using an iterative platform called QwikLabs. Before this, lectures by Google Cloud practitioners on how to use various services such as Google BigQuery, Cloud Dataproc, Dataflow and Bigtable will be held.

Introducing Cloud Guru on the Google Cloud Platform

Cost : Free
Time : 1 week, 4-6 hours
Usefulness : 4/10

Do not consider a low utility score as an indicator of course uselessness. This is far from the case. The only reason he gets a lower score is because he is not focused on certifying a professional data engineer (as the name implies).

After completing the Coursera specialization, I took this course as a refresher course because I only used Google Cloud for a few specialized user cases.

If you came from another cloud service provider or have never used Google Cloud before, you might need to take this course. This is a great introduction to the Google Cloud Platform as a whole.

Google Certified Professional Data Engineer from Linux Academy

Cost: $ 49 per month (after a 7-day free trial)
Time : 1–4 weeks, 4+ hours per week
Usefulness : 10/10

After completing the exam and thinking about the courses I took, the most useful Google Certified Professional Linux Academy data engineer .

The video, as well as the Data Dossier e-book (an excellent free training resource that comes with the course) and practice exams have made this course one of the best training resources I have ever used.

I even recommended it as a reference in some Slack notes for the team after the exam.

Notes in Slack

• Some things on the exam were not exams at either Linux Academy, or Cloud Guru, or Google Cloud Practice (expected)
• 1 question with a graph of data points about which equation you should group them (for example, cos (X) or X² + Y²)
• Knowing the differences between Dataflow, Dataproc, Datastore, Bigtable, BigQuery, Pub / Sub and how they can be used is a must.
• Two working examples of exam studies were exactly the same as in practical classes, although I did not address these studies at all during the exam (the questions gave sufficient understanding).
• Knowing the basic syntax of SQL queries is very useful, especially for BigQuery questions.
• The practice exams provided by Linux Academy and GCP are very similar in style to the exam questions, and I will work through each of them several times and will use them to find out your weaknesses.
• A small tip to help with Dataproc: “ Dataproc the croc and Hadoop the elephant plan to Spark a fire and cook a Hive of Pigs ” {The crocodile Dataproc and the elephant Hadoop plan to make a fire ( Spark - spark, spark a fire - make a fire) and cook a swarm ( Hive ) of pigs ( Pig )} (Dataproc deals with Hadoop, Spark, Hive and Pig)
• « The Dataflow is a flowing Beam of light» { the Dataflow is the current beam ( Beam ) light} (Dataflow deals with Apache Beam)
• “Everyone around the world can relate to a well-made ACID washed Spanner” {Anyone around the world could deal with acid cleaned ( ACID ) with a Spanner} (Cloud Spanner is a database designed to raise a cloud with scratch, compatible with ACID and available worldwide)
• Knowing the names of classic variants of relational and non-relational databases (for example, MongoDB, Cassandra) may come in handy.
• IAM roles vary slightly for each service, but it’s useful to understand how to separate users from being able to see data without losing the ability to design workflows (for example, the Dataflow Worker role can design workflows but not see data)

This is probably enough for now. Kilometers are likely to differ from exam to exam. The Linux Academy course will provide 80% of the knowledge.

1-minute Google Cloud videos

Cost : Free
Time : 1-2 hours
Usefulness : 5/10

They were recommended on the Cloud Guru forums. Many of them were not related to Professional Data Engineer certification, however I selected some of them that are suitable.

Some services may seem difficult to complete the course, so it was nice to listen to how a particular service is described in a minute.

Cloud Professional Data Engineer Exam Preparation

Cost : US $ 49 per certificate or free (without certificate)
Time: 1-2 weeks, 6+ hours per week
Usefulness : N / A

I found this resource the day before the scheduled exam. I did not finish it due to time constraints, hence the lack of a utility rating.

However, judging by the course’s overview page, it looks like a great resource to put together everything you’ve learned about Data Engineering on Google Cloud and highlight any weaknesses.

I advised this course as a resource to one of my colleagues who is preparing for certification.

Google Data Engineering Cheat Sheet Meverica Lina

Cost : Free
Time : N / A
Utility : N / A

This was another resource that I came across after the exam. In my opinion, it is comprehensive, but at the same time concise. Plus, it's free. It can be used for reading between practical exams or even after certification to refresh knowledge.

What did I do after the course?

Stepping closer to the end of the course, I booked an exam with a week notice.
Having a deadline is a great motivation to reinforce what you have learned.

I took practical exams from Linux Academy and Google Cloud several times until I was able to complete them with 95% + accuracy every time.


Take the Linux Academy practice exam more than 90% for the first time.

The tests from each platform are similar, but I found that, sorting through the questions that I constantly answered incorrectly, and writing down why I misunderstood them, helped to tighten my weaknesses.

The exam I passed used two examples of research projects for developing data processing systems in Google Cloud as a topic (this has changed since March 29, 2019). And he was with multiple choices all along.

It took me about 2 hours. And it was about 20% more difficult than any of the exams that I passed.

I cannot express the value of practical exams sufficiently.

What would I change if I went again?

More practice exams. More practical knowledge.

Of course, there is always more training that you could do.

Recommended requirements indicate more than 3 years of use of GCP. But I didn’t have this, so I had to deal with what I had.

Additionally

The exam was updated on March 29th. The materials presented in this article still provide a good foundation, but it is important to note some changes.

Various sections of the Google Cloud Professional Data Engineer Exam ( version 1 )

1. Data Processing Systems Design
2. Creation and support of structures and databases.
3. Data Analysis and Machine Learning Connectivity
4. Business process modeling for analysis and optimization
5. Reliability assurance
6. Data visualization and policy support
7. Design for Security and Compliance

Various sections of the Google Cloud Professional Data Engineer Exam ( version 2 )

1. Data Processing Systems Design
2. Construction and operation of data processing systems
3. Operationalization of machine learning models (most of the changes have occurred here) [NEW]
4. Quality Assurance Solutions

Version 2 merged sections 1, 2, 4, and 6 of Version 1 into 1 and 2. It also merged sections 5 and 7 of Version 1 into section 4. And Section 3 of Version 2 was expanded to cover all the new machine learning features of Google Cloud.

Since these changes occurred recently, many training materials did not have the opportunity to update.

However, familiarization with the materials in this article should be enough to cover 70% of what you need. I would combine this with some of your own research on the following questions (they were presented in the second version of the exam).

• Google Machine Learning API (ML)
• Google Cloud Machine Learning Engine
• Google Cloud TPUs (a custom piece of equipment developed by Google specifically for ML training)
• Google Glossary for ML Terms

As you can see, the latest exam update focused on ML features in Google Cloud.

04/29/2019 update : A message from the Linux Academy course teacher, Matthew Ulasein.
Just for reference, we plan to update the Data Engineer course at Linux Academy to reflect new directions that will start somewhere in the middle / end of May.

After exam

When you pass the exam, you will only get a successful or negative result. I advise you to strive for at least 70%, so I aimed at a minimum of 90% in practical exams.

After completing this, you will receive a redemption code by email along with the official Google Cloud Professional Data Engineer certificate. Congratulations!

You can use the redemption code in the exclusive Google Cloud Professional Data Engineer store, which is jam-packed with swag ( SWAG ). There are T-shirts, backpacks and hoodies (they may differ from what will be in the warehouse by the time you get there). I chose a hoodie.

Now you are certified, you can demonstrate your set of skills (officially) and return to what you do best, to design.

See you in two years to go through recertification.

PS: If you have any questions or want to clarify something, you can find me on Twitter and LinkedIn . On YouTube also has a video version of this article.
PPS: many thanks to all the wonderful teachers in all of the above courses and to Max Kelsen for providing resources and time for studying and preparing for the exam.

And everyone who wants to learn more about the course program, features of the online format, skills, competencies and prospects that await graduates after training, we invite you to open day , which will be held today at 20.00.