QUESTION: 45 Exam Topic: 4, Main Questions Set B

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?

BigQuery
Cloud SQL
Cloud Bigtable
Cloud Datastore

Answer(s): A

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QUESTION: 46 Exam Topic: 4, Main Questions Set B

Your company is loading comma-separated values (CSV) files into Google BigQuery. The data is fully imported successfully; however, the imported data is not matching byte-to-byte to the source file.
What is the most likely cause of this problem?

The CSV data loaded in BigQuery is not flagged as CSV.
The CSV data has invalid rows that were skipped on import.
The CSV data loaded in BigQuery is not using BigQuery's default encoding.
The CSV data has not gone through an ETL phase before loading into BigQuery.

Answer(s): B

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QUESTION: 47 Exam Topic: 4, Main Questions Set B

Your company produces 20,000 files every hour. Each data file is formatted as a comma separated values (CSV) file that is less than 4 KB. All files must be ingested on Google Cloud Platform before they can be processed. Your company site has a 200 ms latency to Google Cloud, and your Internet connection bandwidth is limited as 50 Mbps. You currently deploy a secure FTP (SFTP) server on a virtual machine in Google Compute Engine as the data ingestion point. A local SFTP client runs on a dedicated machine to transmit the CSV files as is. The goal is to make reports with data from the previous day available to the executives by 10:00 a.m. each day. This design is barely able to keep up with the current volume, even though the bandwidth utilization is rather low.

You are told that due to seasonality, your company expects the number of files to double for the next three months.
Which two actions should you take? (choose two.)

Introduce data compression for each file to increase the rate file of file transfer.
Contact your internet service provider (ISP) to increase your maximum bandwidth to at least 100 Mbps.
Redesign the data ingestion process to use gsutil tool to send the CSV files to a storage bucket in parallel.
Assemble 1,000 files into a tape archive (TAR) file. Transmit the TAR files instead, and disassemble the CSV files in the cloud upon receiving them.
Create an S3-compatible storage endpoint in your network, and use Google Cloud Storage Transfer Service to transfer on-premices data to the designated storage bucket.

Answer(s): C,E

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QUESTION: 48 Exam Topic: 4, Main Questions Set B

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?

Create a view in BigQuery that concatenates the FirstName and LastName field values to produce the FullName.
Add a new column called FullName to the Users table. Run an UPDATE statement that updates the FullName column for each user with the concatenation of the FirstName and LastName values.
Create a Google Cloud Dataflow job that queries BigQuery for the entire Users table, concatenates the FirstName value and LastName value for each user, and loads the proper values for FirstName, LastName, and FullName into a new table in BigQuery.
Use BigQuery to export the data for the table to a CSV file. Create a Google Cloud Dataproc job to process the CSV file and output a new CSV file containing the proper values for FirstName, LastName and FullName. Run a BigQuery load job to load the new CSV file into BigQuery.

Answer(s): C

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Free Google Cloud Certified Professional Data Engineer Exam Braindumps (page: 12)

QUESTION: 45 Exam Topic: 4, Main Questions Set B

QUESTION: 46 Exam Topic: 4, Main Questions Set B

QUESTION: 47 Exam Topic: 4, Main Questions Set B

QUESTION: 48 Exam Topic: 4, Main Questions Set B