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Passing the Google Professional-Data-Engineer Certification Exam is a significant achievement that can lead to multiple career opportunities. It can help individuals establish themselves as experts in the field of data engineering and demonstrate their ability to design, implement, and manage complex data processing systems. Moreover, it can also increase their credibility and earning potential, as the demand for certified data engineers is on the rise. Therefore, if you are looking to establish a career in data engineering, obtaining the Google Professional-Data-Engineer Certification is a must.
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Google Professional-Data-Engineer exam is intended for professionals who work with data engineering, data integration, or data analysis. Professional-Data-Engineer exam tests the candidate's knowledge and understanding of Google Cloud Platform tools and services, including BigQuery, Cloud Dataflow, Cloud Pub/Sub, Cloud Storage, and more. Professional-Data-Engineer exam consists of multiple-choice questions and practical scenarios that test the candidate's ability to apply their knowledge and skills to real-world problems. Passing the exam and obtaining the certification demonstrates the individual's proficiency in designing and implementing scalable and reliable data processing systems using Google Cloud Platform technologies.
Google Professional-Data-Engineer Certification Exam is a comprehensive test that covers a wide range of topics related to data engineering. Professional-Data-Engineer exam consists of multiple-choice questions that assess the candidates' knowledge of various Google Cloud Platform services, including BigQuery, Cloud Spanner, Cloud Dataflow, and Cloud Dataproc. Additionally, the exam evaluates the candidates' ability to design data processing systems that are scalable, reliable, and secure. Google Certified Professional Data Engineer Exam Sample Questions (Q289-Q294):NEW QUESTION # 289
You have some data, which is shown in the graphic below. The two dimensions are X and Y, and the shade of each dot represents what class it is. You want to classify this data accurately using a linear algorithm.
To do this you need to add a synthetic feature. What should the value of that feature be?
