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NEW QUESTION: 1
データマスキング要件を満たすために、各列にどのマスキング関数を実装する必要がありますか？回答するには、回答エリアで適切なオプションを選択します。
注：それぞれの正しい選択には1ポイントの価値があります。
Answer:
Explanation:
NEW QUESTION: 2
Which of the following statements pertaining to Secure Sockets Layer (SSL) is false?
A. The SSL protocol was developed by Netscape to secure Internet client-server transactions.
B. Web pages using the SSL protocol start with HTTPS
C. The SSL protocol's primary use is to authenticate the client to the server using public key cryptography and digital certificates.
D. SSL can be used with applications such as Telnet, FTP and email protocols.
Answer: C
Explanation:
Explanation/Reference:
All of these statements pertaining to SSL are true except that it is primary use is to authenticate the client to the server using public key cryptography and digital certificates. It is the opposite, Its primary use is to authenticate the server to the client.
The following reference(s) were used for this question:
KRUTZ, Ronald L. & VINES, Russel D., The CISSP Prep Guide: Mastering the Ten Domains of Computer Security, John Wiley & Sons, 2001, Chapter 4: Cryptography (page 170).
NEW QUESTION: 3
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?
A. Create a view in BigQuery that concatenates the FirstName and LastName field values to produce the FullName.
B. 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.
C. 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.
D. 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.
Answer: C
Explanation:
Import and Export to Bigquery from Cloud Storage is FREE. Also, when u store the csv files, Cloud Storage is cheaper than Bigquery. For processing Dataproc is cheaper than Dataflow.