DP-300 Exam Question 116

You Save an Azure SCX database named DB1.
You need to query the fragmentation information of data and indexes for the tables in D61.
Which command should you run?
  • DP-300 Exam Question 117

    You have an Azure SQL database named DB1. DB1 has a table named Table1 that contains the following columns.

    You plan to enable Always Encrypted for Table1.
    Which two columns support encryption? Each correct answer presents a complete solution.
    NOTE: Each correct selection is worth one point
  • DP-300 Exam Question 118

    You have an Azure AD tenant and a logical Microsoft SQL server named SQL1 that hosts several Azure SQL databases.
    You plan to assign Azure AD users permissions to the databases automatically by using Azure Automation.
    You need to create the required Automation accounts.
    Which two accounts should you create? Each correct answer presents part of the solution.
    NOTE: Each correct selection is worth one point.
  • DP-300 Exam Question 119

    You plan to deploy Instance1 by using the following script.

    You need to specify the licenseType and storagenedundancy parameters. The deployment must meet the availability requirements and the business requirements for DB1 and DB2.
    To what should you set each parameter? To answer, select the appropriate options in the answer area.

    DP-300 Exam Question 120

    Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
    After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
    You have an Azure Data Lake Storage account that contains a staging zone.
    You need to design a daily process to ingest incremental data from the staging zone, transform the data by executing an R script, and then insert the transformed data into a data warehouse in Azure Synapse Analytics.
    Solution: You schedule an Azure Databricks job that executes an R notebook, and then inserts the data into the data warehouse.
    Does this meet the goal?