Cloud computing is revolutionizing how businesses manage their data. Businesses are turning to cloud engineers to help them make sense of this new paradigm.
A cloud professional engineer can help organizations make better use of their data, by analyzing key metrics, identifying trends, and developing strategies for improving business operations.
In this study guide you will find information on:
- Who is a data engineer
- Why become a data engineer
- GCP Professional Data Engineer certification exam details
- Free and paid resources
- Important exam topics
- Pro exam tips
- What's next
- Conclusion
So, let begin our journey for GCP Professional Cloud Data certification
Who Is a Data Engineer?
Data engineers are professionals who design and build databases that store information for applications, as well as ensuring those databases are protected from hackers. The data engineer is taking on the central role in the world of IT. For some knowledge professionals, data engineering is a career choice that has never been more important or in-demand.
Why Become a Data Engineer?
A data engineer is a professional who designs and builds the databases that store data for applications, as well as ensuring that those databases are adequately protected from hackers.
As per Talent.com the average salary for a Google Professional Data Engineer in the USA is around $147,000 per year. The lowest entry-level salary of a Google Data Engineer is $141,375 per year, whereas the highest pay-out for experienced data engineers is recorded to be $175,000 per year.
With experience over time, the salary will also hike gradually.
The job responsibilities of a cloud data engineer typically include:
- Analyzing and organizing complex raw data, and perform exploratory analyses to answer business problems. A Data Engineer can perform complex data analysis to find trends and patterns and reporting on the results in the form of dashboards, reports and data visualizations.
- Building required infrastructure for optimal extraction, transformation and loading of data from various data sources using public cloud platforms like Google Cloud, Amazon Web Services or Azure Cloud.
- Build data pipelines that enable the organization to collect data points from millions of users and process the results in near real-time. Use these tools to provide actionable insight into key business performance metrics including operational efficiency and customer acquisition.
- Working with stakeholders including data, design, product and executive teams and assisting them with Predictive and Prescriptive modeling to enable them make good business decisions.
- Working with stakeholders including the Executive, Product, Data and Design teams to support their data infrastructure needs while assisting with data-related technical issues.
GCP Professional Data Engineer Certification Exam Details
There are no prerequisites for Google Cloud Professional Data Engineer certification.
| Duration of the Exam | 2 Hours |
| Exam Fee | $200 USD |
| Exam format | Multiple Choice (Single Answer and Multiple Answers) |
| Number of Questions | 50 |
Resources To Pass GCP Professional Data Engineer Certification
First and foremost, make sure you acclimate yourself with the official exam guide. The topics included changes frequently, and often the training material do not change. So it is important to stay current on the exam topics. Below are some more resources to help you pass the actual exam.
1. Google, every now and then provides free training for its courses. So, before you go anywhere else, check out this learning path - official training link.
2. Free Sample questions from GCP. Click here.
3. Paid Practice exam. These practice tests will will help you to prepare better.
Related
4. Here is a free handy course book from Linux Academy. This book is slightly dated, but the contents are still relevant.
5. Google has excellent documentation on architecture. Here is an important link for all topics related to BigData and Analytics, databases.
6. Free Google Machine Learning CrashCourse.
7. Sign up for a Google Cloud Webinar.
8. Here is a good cheat sheet on Github.
Important Exam Topics For GCP Professional Data Engineer Exam
As per Google this certification is suited for the role definition: “A Data Engineer should also be able to leverage, deploy, and continuously train pre-existing machine learning models.” You don't need to have industry experience, but having the basic knowledge of machine learning, and various GCP services is crucial to pass this certification.
You should understand all the topics covered in the exam-guide. Below are some of the exam topics that you'd see some questions on.
Designing data processing systems
Important topics for the exam include the following:
- Datastore, BigTable - including Development and Production instances, Disk Types (HDD vs. SSD, quotas, performance, BigQuery, Cloud Dataproc, Cloud Spanner, CloudSQL
- High Availability, Replication including Read Replicas for failover
- Migration from sql to no-sql
- Cloud SQL SLA
- Cloud Pub-Sub, Kafka, Cloud Dataflow, and windowing
- Encryption
Building and operationalizing data processing systems
Important topics for the exam include the following:
- HDFS vs. Google Cloud Storage for Dataproc workloads, Migrating Hadoop jobs.
- Building and designing pipelines
- Google Cloud Logging
- Overview of Google Databases Products
Operationalizing machine learning models
Important topics for the exam include the following:
- Regularization
- Overfitting/Underfitting
- Machine Learning workflow
- Google Cloud Vision
- Natural Language
- Google Cloud Artificial Intelligence (AI) Platform
- Google Cloud TPUs
- Finally read through Google Cloud ML key term glossary
Ensuring solution quality
Important topics for the exam include the following:
- BigTable Performance and Quotas and Limits
- Best Practices recommended by Google Cloud.
Pro Exam Tips For GCP Professional Data Engineer Exam
- Nothing beats hands-on practice in Google Console. So, if you don't have practical knowledge, create your Google Developer account and do some hands-on labs as you progress through various topics described above.
- For exam preparation, you need to practice through exam questions. Google has free questions listed in the resources section of this blog. It is highly recommended that you use these practice exam questions for getting that last minute practice.
- If you are not sure of the answer choice, flag questions for review later. Do not spend more time on one question.
- Use the process of elimination for removing answer choices that make no sense at all. Your probability of guessing the right answer increases by eliminating wrong choices.
What's Next
Once you have cleared your Google Cloud Professional Data Engineer Exam, it's time to move on to next certifications. But first, you should celebrate your success.
Don't forget to share your experiences with others if you found this blog helpful. Sharing your experience can help many others save their time and energy while preparing for the exam, and we all understand how valuable time is for everyone.
Here is an invitation from Reviewnprep’s community to share your journey and encourage others. And you get $5 Amazon Gift card for doing so!!
As a cloud engineer it is important to keep up with various offerings from Google. Check out other Google Cloud Platform Certifications offered.
Alternatively, you can check out Career Journey tool, a one-stop-shop on how to prepare for a certification.
Career Journey is a free tool from ReviewNPrep that allows you to navigate certifications based on your current industry or role.
The tool will help you determine which Google certification would be suitable for you and provides excellent baseline content such as duration, cost, and even expected salary boost.
Conclusion
With over 1 billion people using Gmail, YouTube or Android every month, it’s hard to deny that anything made by Google has the potential to be revolutionary. When it comes to data engineering, it’s no different. This field is constantly evolving and offering new opportunities for professionals who are hungry for more knowledge and challenge in their cloud career.
