Google Professional-Data-Engineer Dumps
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Professional-Data-Engineer FAQs
The Google Professional Data Engineer Exam is a certification test designed to validate your ability to design, build, operationalize, secure, and monitor data processing systems on Google Cloud Platform (GCP).
The Google Professional Data Engineer focuses on GCP services and data engineering practices within Google's ecosystem, while the AWS Certified Big Data – Specialty focuses on big data services and solutions on Amazon Web Services.
The Professional Data Engineer Exam focuses on data engineering tasks such as data processing, machine learning, and data pipelines, while the Associate Cloud Engineer Exam covers foundational skills in deploying and managing applications on GCP.
Google does not publish a specific passing score. Instead, the results are based on a scaled scoring system. Candidates should focus on thoroughly understanding the exam objectives.
The certification can enhance your professional credibility, demonstrate your expertise in data engineering on GCP, and make you a more competitive candidate for advanced data engineering roles.
With this certification, you can pursue roles such as Data Engineer, Data Architect, Machine Learning Engineer, and Big Data Engineer.
Salaries vary based on experience and location, but professionals with this certification can expect to earn between $100,000 and $150,000 per year, with potential for higher earnings in senior roles.
Long-term benefits include career advancement opportunities, higher earning potential, recognition as an expert in data engineering, and the ability to work on cutting-edge data projects.
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Google Professional Data Engineer Exam Questions and Answers
You work for a large fast food restaurant chain with over 400,000 employees. You store employee information in Google BigQuery in a Users table consisting of a FirstName field and a LastName field. A member of IT is building an application and asks you to modify the schema and data in BigQuery so the application can query a FullName field consisting of the value of the FirstName field concatenated with a space, followed by the value of the LastName field for each employee. How can you make that data available while minimizing cost?
You are designing the database schema for a machine learning-based food ordering service that will predict what users want to eat. Here is some of the information you need to store:
The user profile: What the user likes and doesn’t like to eat
The user account information: Name, address, preferred meal times
The order information: When orders are made, from where, to whom
The database will be used to store all the transactional data of the product. You want to optimize the data schema. Which Google Cloud Platform product should you use?
You work for an economic consulting firm that helps companies identify economic trends as they happen. As part of your analysis, you use Google BigQuery to correlate customer data with the average prices of the 100 most common goods sold, including bread, gasoline, milk, and others. The average prices of these goods are updated every 30 minutes. You want to make sure this data stays up to date so you can combine it with other data in BigQuery as cheaply as possible. What should you do?
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