Google Cloud Professional Data Engineer

Google Cloud Professional Data Engineer

Google Cloud Professional Data Engineer

Google Cloud provides a number of professional certification programmed that examine professionals’ knowledge of various Google Cloud services in various fields. It has a prominent certification programmed called “Google Cloud Certified Professional Data Engineer” in the subject of data science. This certification, which is based on an exam, assesses the abilities of applicants who work as or are equal to data engineers and awards them a certificate. We’ll go through this certification programmed in depth here, with a focus on how to prepare for it.

Google Cloud Certified Professional Data Engineer certification

The Google Cloud Certified Professional Data Engineer certification is appropriate for people who work in the field of data science and whose responsibilities include handling data, processing data, and doing extensive feature engineering on data in order to prepare it for modelling. Professionals whose day-to-day responsibilities include gathering, transforming, and disseminating data for data-driven decision making should pursue this certification, which will help them stand out from the crowd.

Although there are no precise requirements for this certification, Google suggests that candidates have at least three years of industry experience, with at least one year of that work being relevant to building and managing data-related solutions with Google Cloud. This certification tests the candidate’s ability to design, implement, and operationalize data processing systems and machine learning solutions with guaranteed quality, which is why this experience is suggested. It also expects a data engineer to be able to utilize, deploy, and train pre-existing machine learning models on a continual basis.

Concerning the Exam

Candidates must pass a Google-conducted test in order to get the Google Cloud Certified Professional Data Engineer credential. This exam may be taken from anywhere in the globe via an online proctoring service or from one of the certified test centers. Candidates must pay a reservation fee of $200 USD to register for the test. Only English and Japanese are offered for this exam.

The following are the most significant test details:

  • Duration: 2 Hours
  • Number of questions: 50
  • Format: Multiple choice questions

The exam’s questions cover a variety of topics, including the following:

  1. Data processing system design
  2. Creating and implementing data processing systems
  3. Putting machine learning models into practice
  4. Assuring the quality of the solution

Candidates taking this test should familiarize themselves with the aforementioned topics and ensure that they have a firm grasp on these skills. Although Google does not provide official information on the minimum passing score, successful applicants claim that you must achieve at least 70% to pass the exam.

Preparation Procedures

As previously said, aspiring applicants are required to possess a variety of abilities and expertise. To achieve these requirements and score well on the exam, one must prepare well. The measures that a candidate should do in order to reach the goal are listed below:-

  1. Get the Required Information:First and foremost, you must gather all of the necessary information for this exam. The features of this certification programmed may be found on its official website. The overview of subjects to which the questions in this test relate is the second vital element to collect. This outline may be found at this URL. Along with this, Google also provides example questions for this test, which may be obtained via this URL. You may get a sense of the scope and depth of the test by looking at the contents overview and sample questions.
  2. Prepare with Courses:Google Cloud has a variety of courses that cover the abilities required for this certification. This link will take you to a list of these courses. Some of these courses are offered directly by Google Cloud, while others are available through Coursera. These courses are organized in a learning path to help students prepare for this certification by providing relevant information.
  3. Learn about Google Cloud Services:Here you’ll find information about a range of Google Cloud services, as well as use cases and implementations. You should check over all of the materials connected to data engineering and data processing and learn about them. In addition, numerous documentation and blogs about Google Cloud services, including their applications and use cases, may be found here. All you have to do now is sort through the materials depending on the exam’s outline. These materials will assist you in gaining a thorough grasp of the Google Cloud services that are important to you.
  4. Take Mock Test: MachineHack, India’s premier hackathon and assessment platform, offers various mock examinations on key professional certifications. These sample exams are offered for free in order to assist applicants. These are created using information provided by certification bodies as well as comments from successful candidates. On MachineHack, you may take a Google Cloud Certified Professional Data Engineer Certification Mock test to simulate taking the exam in real life. Here you will find the same levels of questions from all of the required subjects that must be completed within the time limit. You will be able to determine your degree of test readiness after completing this mock exam.
  5. Repeat the Steps:Rep steps 2–4 until you achieve a good mock score.


Remarks at the End

Nothing is difficult or impossible if it is properly approached and prepared. The Google Cloud Certified Professional Data Engineer certification is a good fit for data engineering professionals since it allows them to stand out from the crowd. They must pass an exam that needs thorough preparation in order to obtain this certificate. Candidates can study for this exam by using Google Cloud’s extensive learning materials, which are supplemented with a practice examination available on the MachineHack platform.


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