GCP PROFESSIONAL DATA ENGINEER EXAM OUTLINES

Dear All,

If you are planning to complete GOOGLE CLOUD PLATFORM Data Engineer exam and if you have below question then you are at right place.

1. What is Data Engineer certificate and what Data Engineers do?
2. Difference between Architect and Data Engineer exam?
3. How much time is required for preparation?
4. What are the services covered?
5. What is the weightage of each service?
6. How to prepare for the exam?
7. What is the pattern of the exam?
8. Sample questions?

Hello friends, I am Bharat Mishra GOOGLE CLOUD PLATFORM Certified Professional Data Engineer. I completed my certification in 2 week time. I have around 18 years of experience in IT. I am associated to data and data management throughout my career. Since year 2004 I am working on DWH platform. I started working on Big data services on GOOGLE CLOUD PLATFORM since 2015. I have earned many technical and management certification including “DWH certified professional”, “Project Management Professional – PMP”, “Scrum Master” and “GOOGLE CLOUD PLATFORM Certified Professional Data Engineer”. I have executed many DWH and Big Data projects. I have very good track record of Technical and management skills. I handled many roles from Data Architect to Project Manager.

1. What is Data Engineer certificate and what Data Engineers do?

Data Engineers are responsible to make data available in Big data environment for ML, Analytics or just for storing data. They are responsible to read the data, transform the data and load the data. The question here is then this role is similar to an ETL or any data load developer, then what is the difference?

So the difference is:

Amount of data – ETL developer deals with GBs of data but DATA ENGINEER deals with TBs of data. Big Data has its own challenges hence need new tools/technology as well as different way for handling data.

Technology – ETL Tools are used to load data into target area but DATA ENGINEER uses big data technologies. There may not be SQL, DB to load data there may be NoSQL DB, Distributed File system and other big data technologies available for usage

Mind Set – This is very important, ETL developer may think of some ETL tricks and tips whereas DATA ENGINEER has to think differently to load huge amount of data. Conventional thinking may not work in Big data environment.

GOOGLE CLOUD PLATFORM Data Engineer certificate test your knowledge around GOOGLE CLOUD PLATFORM services only.

More information on Professional Data Engineer is available on GOOGLE CLOUD PLATFORM link https://cloud.google.com/certification/data-engineer

2. Difference between Architect and Data Engineer exam?

The difference between the length and depth of GOOGLE CLOUD PLATFORM services. Architect certification test your knowledge on all services but not at very detail level. If you know overview of services along with use case of each service that there is a high chance you will pass exam. DATA ENGINEER exam test depth of data and machine leaning related service. Just knowing the service along with use case may not help you in passing the exam. You need in-depth knowledge of important services. You may need to answer few questions related to code/command.

In short Architect exam check your knowledge of all GOOGLE CLOUD PLATFORM services but DATA ENGINEER exam check in-depth knowledge of few services.

3. How much time is required for preparation?

Exam cover all Data and AI related services along with Stack Driver.

IAM & Admin, different type of Storage, Data analytics, AI and machine learning and Databases

4.What are the services covered?

Below picture shows the questions distribution across different services. Others on the graph include all other services like Stack Driver, Data Prep, Data Studio and others.

5. What is the weightage of each service?

There is no single answer to this question. It depends on your knowledge and experience.

I completed my certification in 2 week time. This was possible for me because I am an experienced Data Architect. I am working extensively on some services of GOOGLE CLOUD PLATFORM which includes BigQuery, CloudSQL, Data Flow and Storage. I have vast data handling experience including ETL and Dashboard. Few small services (Data Prep, Data Studio) was very easy for me to understand.

Preparation time is totally depends upon your knowledge and expertise.

6. How to prepare for the exam?

I highly recommend Google Data Engineer course on Coursera. This course is very well structure in terms of presentation and material. It also provide Quicklabs so that you can practice a fully structure practical implementation. Training/Course is not must, but it provides you a good information about all services.

You have to Reading GOOGLE CLOUD PLATFORM documents also. While going through these documents you can prepare short notes for keywords for future reference. You can refer these short notes while revising topics. You have to make sure you fully utilize $300 free credit given by GOOGLE CLOUD PLATFORM to everyone for initial usage. Hands-on is very important it will upscale your skills. This will give you implementation experience and also provides detail information on services.

7. What is the pattern of the exam?

Exam has 50 multiple choice questions.

There will be 2 case studies presented in exam. These case studies includes vision of a company. High level requirement statement of employees including CXO. You have to understand entire case study and answer all questions wrt case study. If statement of CFO is to reduce the cost then services with low cost to be selected. For ex – CFO want to reduce cost of “storage and retrieval” of data then Cloud Storage or Big Table to be selected. If performance is a key criteria along with joins for big size data then BigQuery to be selected.

You will have many use case question to select best service according to requirement, few in-depth question on API usage of a service, commands for a task and others.

Each beta service may have one question. The question will be asked for a basic functionality of the service, you don’t need in-depth knowledge of these services.

8. Additional Information?

Please contact me if you need additional information.

Thanks and all the very best
Bharat Mishra on Data