Data Engineering on Microsoft Azure

• #241

  You have an Azure Synapse Analytics dedicated SQL pool named Pool1 that contains an external table named Sales. Sales contains sales data. Each row in Sales contains data on a single sale, including the name of the salesperson. You need to implement row-level security (RLS). The solution must ensure that the salespeople can access only their respective sales. What should you do?

  • ACreate: A materialized view in Pool1. Restrict row access by using: The CONTAINS predicate.
  • BCreate: Database scoped credentials in Pool1. Restrict row access by using: A table-valued function.
  • CCreate: A security policy for Sales. Restrict row access by using: A masking rule.
  • DCreate: A security policy for Sales. Restrict row access by using: A table-valued function.
  解答を表示
• #242

  You are planning a streaming data solution that will use Azure Databricks. The solution will stream sales transaction data from an online store. The solution has the following specifications: The output data will contain items purchased, quantity, line total sales amount, and line total tax amount. Line total sales amount and line total tax amount will be aggregated in Databricks. Sales transactions will never be updated. Instead, new rows will be added to adjust a sale. You need to recommend an output mode for the dataset that will be processed by using Structured Streaming. The solution must minimize duplicate data. What should you recommend?

  • AAppend.
  • BUpdate.
  • CComplete.
  解答を表示
• #243

  Solution: You use an Azure Data Factory schedule trigger to execute a pipeline that executes an Azure Databricks notebook, and then inserts the data into the data warehouse. Dow this meet the goal?

  • AYes.
  • BNo.
  解答を表示

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