Google Professional-Data-Engineer Exam With Confidence Using Practice Dumps

You have a BigQuery dataset named "customers". All tables will be tagged by using a Data Catalog tag template named "gdpr". The template contains one mandatory field, "has sensitive data~. with a boolean value. All employees must be able to do a simple search and find tables in the dataset that have either true or false in the "has sensitive data" field. However, only the Human Resources (HR) group should be able to see the data inside the tables for which "hass-ensitive-data" is true. You give the all employees group the bigquery.metadataViewer and bigquery.connectionUser roles on the dataset. You want to minimize configuration overhead. What should you do next?

You need to store and analyze social media postings in Google BigQuery at a rate of 10,000 messages per minute in near real-time. Initially, design the application to use streaming inserts for individual postings. Your application also performs data aggregations right after the streaming inserts. You discover that the queries after streaming inserts do not exhibit strong consistency, and reports from the queries might miss in-flight data. How can you adjust your application design?

A TensorFlow machine learning model on Compute Engine virtual machines (n2-standard -32) takes two days to complete framing. The model has custom TensorFlow operations that must run partially on a CPU You want to reduce the training time in a cost-effective manner. What should you do?