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Exam DP-201 topic 2 question 45 discussion

Actual exam question from Microsoft's DP-201
Question #: 45
Topic #: 2
[All DP-201 Questions]

HOTSPOT -
You design data engineering solutions for a company.
You must integrate on-premises SQL Server data into an Azure solution that performs Extract-Transform-Load (ETL) operations have the following requirements:
✑ Develop a pipeline that can integrate data and run notebooks.
✑ Develop notebooks to transform the data.
✑ Load the data into a massively parallel processing database for later analysis.
You need to recommend a solution.
What should you recommend? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:

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Suggested Answer:
by H_S at March 15, 2021, 12:15 p.m.

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Needium
Highly Voted 4 years, 2 months ago
I would rather have Integrate on premises data to Cloud : ADF Develop notebooks to Transform Data : DataBricks Run Notebooks : ADF (Azure Databricks notebooks can be run within an ADF pipeline) Load the Data : Use ADF to load the Data Store the Transformed Data: Azure Synapse Analyses
upvoted 29 times
maciejt
4 years, 2 months ago
Exactly that was my take before seeing the solution.
upvoted 1 times
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cadio30
4 years ago
Azure databricks can handle the loading of data from the notebook to the external tables of Azure Synapse unless the requirement is explicitly to export the file to another storage then use of ADF is the appropriate
upvoted 2 times
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Wendy_DK
Highly Voted 4 years ago
Given answer is right. Remember requirement: Load the data into a massively parallel processing database for later analysis. ADF and Batch can work together. ref: https://docs.microsoft.com/en-us/azure/data-factory/v1/data-factory-data-processing-using-batch
upvoted 8 times
BobFar
4 years ago
I am agree with you.
upvoted 1 times
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Bhagya123456
Most Recent 3 years, 9 months ago
Given Solution is 100% Correct. Do not confuse people with absurd arguments. I can do all the activities through Synapse Analysis also. That doesn't mean I will choose 5 times Synapse Analyses.
upvoted 2 times
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tes
3 years, 11 months ago
Just one change Run notebook is better done from ADF as we can orchestrate the sequence better. When run from databricks, it may not know the time of data retrieveal and also the next step, Azure Batch cannot be called from ADB
upvoted 1 times
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Ous01
4 years ago
Why note using Databricks to load the data? When the notebook finishes the process, it also can load the data into Synapse. Databricks can easily uploads results to Synapse, Azure SQL, and Azure Cosmos DB.
upvoted 3 times
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VG2007
4 years, 1 month ago
Given Solution is correct.. no confusions.. why anyone will use ADB to develop notebook and then use ADF to run them unless it is specifically specified ?
upvoted 4 times
Larrave
3 years, 6 months ago
Because they were asking for a Data Engineering solution and having everything handled within one orchestration/etl tool makes definitely sense.
upvoted 1 times
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davita8
4 years, 1 month ago
Load the data - Azure data factory transformed data-azure sql data warehouse
upvoted 3 times
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aditya_064
4 years, 1 month ago
Shouldn't Load the data (Box 4) be Azure Synapse Analytics ? It's the only one with a MPP engine, which is exactly what is mentioned in the question
upvoted 2 times
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maciejt
4 years, 2 months ago
Why Azure Batch is better than ADF to load data? ADF could be used to: Integrate from on-prem to azure, invoke notebook (developed in data bricks), then load data into warehouse, all within one pipeline.
upvoted 1 times
BobFar
4 years ago
I guess for loading the data into a massively parallel processing database , azure data batch is the better solution. https://docs.microsoft.com/en-us/azure/data-factory/v1/data-factory-data-processing-using-batch
upvoted 1 times
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Geo_Barros
4 years, 2 months ago
Regarding loading the data, I think Azure Data Factory could also be an appropriate answer.
upvoted 3 times
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H_S
4 years, 2 months ago
azure data factory could be used to load the data too
upvoted 3 times
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