FREE PDF QUIZ MICROSOFT - LATEST LATEST DP-203 TEST PDF

Free PDF Quiz Microsoft - Latest Latest DP-203 Test Pdf

Free PDF Quiz Microsoft - Latest Latest DP-203 Test Pdf

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Microsoft DP-203 exam is an excellent way for professionals to validate their skills in data engineering on the Microsoft Azure platform. Passing DP-203 exam demonstrates that a professional has the knowledge and skills required to design and implement data solutions on Azure, which can lead to career advancement and increased job opportunities in the field of data engineering.

Microsoft DP-203 (Data Engineering on Microsoft Azure) Exam is a certification exam designed for individuals who want to demonstrate their knowledge and skills in data engineering on the Microsoft Azure platform. DP-203 exam is an excellent opportunity for data engineers who want to showcase their expertise in designing and implementing data solutions using Azure services.

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Microsoft Data Engineering on Microsoft Azure Sample Questions (Q67-Q72):

NEW QUESTION # 67
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 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?

  • A. No
  • B. Yes

Answer: A

Explanation:
Explanation
If you need to transform data in a way that is not supported by Data Factory, you can create a custom activity, not an Azure Databricks notebook, with your own data processing logic and use the activity in the pipeline.
You can create a custom activity to run R scripts on your HDInsight cluster with R installed.
Reference:
https://docs.microsoft.com/en-US/azure/data-factory/transform-data


NEW QUESTION # 68
You plan to develop a dataset named Purchases by using Azure databricks Purchases will contain the following columns:
* ProductID
* ItemPrice
* lineTotal
* Quantity
* StorelD
* Minute
* Month
* Hour
* Year
* Day
You need to store the data to support hourly incremental load pipelines that will vary for each StoreID. the solution must minimize storage costs. How should you complete the rode? To answer, select the appropriate options In the answer are a.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://intellipaat.com/community/11744/how-to-partition-and-write-dataframe-in-spark-without-deleting-partitions-with-no-new-data


NEW QUESTION # 69
You are designing a monitoring solution for a fleet of 500 vehicles. Each vehicle has a GPS tracking device that sends data to an Azure event hub once per minute.
You have a CSV file in an Azure Data Lake Storage Gen2 container. The file maintains the expected geographical area in which each vehicle should be.
You need to ensure that when a GPS position is outside the expected area, a message is added to another event hub for processing within 30 seconds. The solution must minimize cost.
What should you include in the solution? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-window-functions


NEW QUESTION # 70
From a website analytics system, you receive data extracts about user interactions such as downloads, link clicks, form submissions, and video plays.
The data contains the following columns.

You need to design a star schema to support analytical queries of the data. The star schema will contain four tables including a date dimension.
To which table should you add each column? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/power-bi/guidance/star-schema


NEW QUESTION # 71
You have an Azure Synapse Analytics dedicated SQL pool.
You need to Create a fact table named Table1 that will store sales data from the last three years. The solution must be optimized for the following query operations:
Show order counts by week.
* Calculate sales totals by region.
* Calculate sales totals by product.
* Find all the orders from a given month.
Which data should you use to partition Table1?

  • A. product
  • B. month
  • C. region
  • D. week

Answer: B

Explanation:
Table partitions enable you to divide your data into smaller groups of data. In most cases, table partitions are created on a date column.
Benefits to queries
Partitioning can also be used to improve query performance. A query that applies a filter to partitioned data can limit the scan to only the qualifying partitions. This method of filtering can avoid a full table scan and only scan a smaller subset of data. With the introduction of clustered columnstore indexes, the predicate elimination performance benefits are less beneficial, but in some cases there can be a benefit to queries.
For example, if the sales fact table is partitioned into 36 months using the sales date field, then queries that filter on the sale date can skip searching in partitions that don't match the filter.
Note: Benefits to loads
The primary benefit of partitioning in dedicated SQL pool is to improve the efficiency and performance of loading data by use of partition deletion, switching and merging. In most cases data is partitioned on a date column that is closely tied to the order in which the data is loaded into the SQL pool. One of the greatest benefits of using partitions to maintain data is the avoidance of transaction logging. While simply inserting, updating, or deleting data can be the most straightforward approach, with a little thought and effort, using partitioning during your load process can substantially improve performance.


NEW QUESTION # 72
......

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