DP-203 EXAMS QUESTIONS AND ANSWERS & DUMPS PDF FOR DATA ENGINEERING ON MICROSOFT AZURE

DP-203 exams questions and answers & dumps PDF for Data Engineering on Microsoft Azure

DP-203 exams questions and answers & dumps PDF for Data Engineering on Microsoft Azure

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Microsoft Data Engineering on Microsoft Azure Sample Questions (Q220-Q225):

NEW QUESTION # 220
You have an Apache Spark DataFrame named temperatures. A sample of the data is shown in the following table.

You need to produce the following table by using a Spark SQL query.

How should you complete the query? To answer, drag the appropriate values to the correct targets. Each value may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:
Text Description automatically generated

Box 1: PIVOT
PIVOT rotates a table-valued expression by turning the unique values from one column in the expression into multiple columns in the output. And PIVOT runs aggregations where they're required on any remaining column values that are wanted in the final output.
Reference:
https://learnsql.com/cookbook/how-to-convert-an-integer-to-a-decimal-in-sql-server/
https://docs.microsoft.com/en-us/sql/t-sql/queries/from-using-pivot-and-unpivot


NEW QUESTION # 221
You need to output files from Azure Data Factory.
Which file format should you use for each type of output? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:

Box 1: Parquet
Parquet stores data in columns, while Avro stores data in a row-based format. By their very nature, column- oriented data stores are optimized for read-heavy analytical workloads, while row-based databases are best for write-heavy transactional workloads.
Box 2: Avro
An Avro schema is created using JSON format.
AVRO supports timestamps.
Note: Azure Data Factory supports the following file formats (not GZip or TXT).
* Avro format
* Binary format
* Delimited text format
* Excel format
* JSON format
* ORC format
* Parquet format
* XML format
Reference:
https://www.datanami.com/2018/05/16/big-data-file-formats-demystified


NEW QUESTION # 222
You have files and folders in Azure Data Lake Storage Gen2 for an Azure Synapse workspace as shown in the following exhibit.

You create an external table named ExtTable that has LOCATION='/topfolder/'.
When you query ExtTable by using an Azure Synapse Analytics serverless SQL pool, which files are returned?

  • A. File1.csv, File2.csv, File3.csv, and File4.csv
  • B. File2.csv and File3.csv only
  • C. File1.csv and File4.csv only
  • D. File1.csv only

Answer: C

Explanation:
To run a T-SQL query over a set of files within a folder or set of folders while treating them as a single entity or rowset, provide a path to a folder or a pattern (using wildcards) over a set of files or folders.
Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql/query-data-storage#query-multiple-files-or-folders


NEW QUESTION # 223
You have an Azure Synapse Analytics dedicated SQL pool named Pool1 that contains a table named Sales. Sales has row-level security (RLS) applied. RLS uses the following predicate filter.

A user named SalesUser1 is assigned the db_datareader role for Pool1. Which rows in the Sales table are returned when SalesUser1 queries the table?

  • A. all the rows
  • B. only the rows for which the value in the SalesRep column is Manager
  • C. only the rows for which the value in the User_Name column is SalesUser1
  • D. only the rows for which the value in the SalesRep column is SalesUser1

Answer: C


NEW QUESTION # 224
You plan to create an Azure Synapse Analytics dedicated SQL pool.
You need to minimize the time it takes to identify queries that return confidential information as defined by the company's data privacy regulations and the users who executed the queues.
Which two components should you include in the solution? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

  • A. audit logs sent to a Log Analytics workspace
  • B. dynamic data masking for columns that contain confidential information
  • C. resource tags for databases that contain confidential information
  • D. sensitivity-classification labels applied to columns that contain confidential information

Answer: A,D

Explanation:
A: You can classify columns manually, as an alternative or in addition to the recommendation-based classification:

* Select Add classification in the top menu of the pane.
* In the context window that opens, select the schema, table, and column that you want to classify, and the information type and sensitivity label.
* Select Add classification at the bottom of the context window.
C: An important aspect of the information-protection paradigm is the ability to monitor access to sensitive data. Azure SQL Auditing has been enhanced to include a new field in the audit log called data_sensitivity_information. This field logs the sensitivity classifications (labels) of the data that was returned by a query. Here's an example:

Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/database/data-discovery-and-classification-overview


NEW QUESTION # 225
......

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