Practice Test Google - Professional Data Engineer dumps: Professional Data Engineer
Last Update: 22-04-2024 | Number of Questions: 173

QUESTION N° 1

Your company is in the process of migrating its on-premises data warehousing solutions to BigQuery. The existing data warehouse uses trigger-based change data capture (CDC) to apply updates from multiple transactional database sources on a daily basis. With BigQuery, your company hopes to improve its handling of CDC so that changes to the source systems are available to query in BigQuery in near-real time using log-based CDC streams, while also optimizing for the performance of applying changes to the data warehouse. Which two steps should they take to ensure that changes are available in the BigQuery reporting table with minimal latency while reducing compute overhead? (Choose two.)

A. Perform a DML INSERT, UPDATE, or DELETE to replicate each individual CDC record in real time directly on the reporting table.

B. Insert each new CDC record and corresponding operation type to a staging table in real time.

C. Periodically DELETE outdated records from the reporting table.

D. Periodically use a DML MERGE to perform several DML INSERT, UPDATE, and DELETE operations at the same time on the reporting table.

E. Insert each new CDC record and corresponding operation type in real time to the reporting table, and use a materialized view to expose only the newest version of each unique record.

How to Pass the Professional Data Engineer Exam

Taking the Professional Data Engineer exam is not an easy task. The course materials that are available to pass the test are not always very comprehensive. This book covers the essentials of machine learning and big data, and includes practice exams for every topic. The information is updated often and includes the most common questions that are asked on the actual exam. A good guide to pass the Professional Data Engineer exam will help you get a feel for the course material.

If you want to pass the exam, start with Google Cloud Platform. For now, there are a variety of free resources available online, including the ML Crash Course. Alternatively, you can purchase a course from Google, which includes sample exams and best practices. This way, you can see what kind of questions you may face on the actual exam. Once you have completed the course, you can buy various products and merchandise. The certificate contains a redemption code that you can use to access the merchandising options for a limited time.

Another good way to pass the Professional Data Engineer exam is to gain a Google Cloud certification. If you are a cloud user, you can choose this certification to work with Google Cloud. It requires a 70% minimum score and is valid for two years. The course includes 15 case studies that teach you how to use the Google Cloud platform to build and manage ML models. The course also teaches you how to use Google Cloud services. You can take the course in English or Japanese, and the test has 15 multiple-choice questions.

When choosing an online course, make sure to look at the prerequisites for the exam. The requirements for each exam are different, and it is important to research them thoroughly. You can find many examples of similar certification exams at Exams.com, and this can help you make the right decision. A Google Cloud course can also help you prepare for the exam. It is an excellent option if you are interested in Google's cloud platform and want to become a data engineer.

For a free online course, you can access the Google Cloud mock exams, which simulate the format and structure of the actual test. Using a free service like MachineHack is a great way to prepare for the exam. A course will cover the topics covered on the exam and give you an idea of the type of questions to expect on the exam. It will also teach you how to approach the exam with a positive attitude.

The course is designed by the author of the official Google Cloud Professional Data Engineer exam guide. It combines lectures, quizzes, and practical sessions. A data architect with 20 years of experience, this course teaches you how to build a pipeline to process large volumes of data. In addition, he or she will teach you how to create and maintain Spark and Hadoop clusters. Aside from this, he or she will also teach you how to create custom queries.