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Microsoft DP-203 certification exam is an excellent credential for data professionals who want to demonstrate their expertise in data engineering on Azure. Data Engineering on Microsoft Azure certification can help candidates enhance their career prospects and open up new job opportunities. With the right preparation and study, candidates can pass the Microsoft DP-203 certification exam and become certified data engineers on Azure.
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Skills measured* Monitor and optimize data storage and data processing (10-15%)
* Design and implement data security (10-15%)
* Design and develop data processing (25-30%)
* Design and implement data storage (40-45%)
Microsoft Data Engineering on Microsoft Azure Sample Questions (Q125-Q130):NEW QUESTION # 125 You have an Azure Active Directory (Azure AD) tenant that contains a security group named Group1. You have an Azure Synapse Analytics dedicated SQL pool named dw1 that contains a schema named schema1.
You need to grant Group1 read-only permissions to all the tables and views in schema1. The solution must use the principle of least privilege.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select.
Answer: Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/data-share/how-to-share-from-sql
NEW QUESTION # 126 You have the Azure Synapse Analytics pipeline shown in the following exhibit.
You need to add a set variable activity to the pipeline to ensure that after the pipeline's completion, the status of the pipeline is always successful.
What should you configure for the set variable activity?
* A. a failure dependency on the Upon Failure activity
* B. a skipped dependency on the Upon Failure activity
* C. a skipped dependency on the Upon Success activity
* D. a success dependency on the Business Activity That Fails activity
Answer: DExplanation:
A failure dependency means that the activity will run only if the previous activity fails. In this case, setting a failure dependency on the Upon Failure activity will ensure that the set variable activity will run after the pipeline fails and set the status of the pipeline to successful.
NEW QUESTION # 127 You use Azure Data Lake Storage Gen2 to store data that data scientists and data engineers will query by using Azure Databricks interactive notebooks. Users will have access only to the Data Lake Storage folders that relate to the projects on which they work.
You need to recommend which authentication methods to use for Databricks and Data Lake Storage to provide the users with the appropriate access. The solution must minimize administrative effort and development effort.
Which authentication method should you recommend for each Azure service? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer: Explanation:
Explanation
Table Description automatically generated
Box 1: Personal access tokens
You can use storage shared access signatures (SAS) to access an Azure Data Lake Storage Gen2 storage account directly. With SAS, you can restrict access to a storage account using temporary tokens with fine-grained access control.
You can add multiple storage accounts and configure respective SAS token providers in the same Spark session.
Box 2: Azure Active Directory credential passthrough
You can authenticate automatically to Azure Data Lake Storage Gen1 (ADLS Gen1) and Azure Data Lake Storage Gen2 (ADLS Gen2) from Azure Databricks clusters using the same Azure Active Directory (Azure AD) identity that you use to log into Azure Databricks. When you enable your cluster for Azure Data Lake Storage credential passthrough, commands that you run on that cluster can read and write data in Azure Data Lake Storage without requiring you to configure service principal credentials for access to storage.
After configuring Azure Data Lake Storage credential passthrough and creating storage containers, you can access data directly in Azure Data Lake Storage Gen1 using an adl:// path and Azure Data Lake Storage Gen2 using an abfss:// path:
Reference:
https://docs.microsoft.com/en-us/azure/databricks/data/data-sources/azure/adls-gen2/azure-datalake-gen2-sas-acc
https://docs.microsoft.com/en-us/azure/databricks/security/credential-passthrough/adls-passthrough
NEW QUESTION # 128 You need to design a data ingestion and storage solution for the Twitter feeds. The solution must meet the customer sentiment analytics requirements.
What should you include in the solution? To answer, select the appropriate options in the answer area NOTE: Each correct selection b worth one point.
Answer: Explanation:
Explanation
Graphical user interface, text Description automatically generated
Box 1: Configure Evegent Hubs partitions
Scenario: Maximize the throughput of ingesting Twitter feeds from Event Hubs to Azure Storage without purchasing additional throughput or capacity units.
Event Hubs is designed to help with processing of large volumes of events. Event Hubs throughput is scaled by using partitions and throughput-unit allocations.
Event Hubs traffic is controlled by TUs (standard tier). Auto-inflate enables you to start small with the minimum required TUs you choose. The feature then scales automatically to the maximum limit of TUs you need, depending on the increase in your traffic.
Box 2: An Azure Data Lake Storage Gen2 account
Scenario: Ensure that the data store supports Azure AD-based access control down to the object level.
Azure Data Lake Storage Gen2 implements an access control model that supports both Azure role-based access control (Azure RBAC) and POSIX-like access control lists (ACLs).
Reference:
https://docs.microsoft.com/en-us/azure/event-hubs/event-hubs-features
https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-access-control
NEW QUESTION # 129 You have an Azure Data Lake Storage Gen2 account that contains a JSON file for customers. The file contains two attributes named FirstName and LastName.
You need to copy the data from the JSON file to an Azure Synapse Analytics table by using Azure Databricks. A new column must be created that concatenates the FirstName and LastName values.
You create the following components:
A destination table in Azure Synapse
An Azure Blob storage container
A service principal
In which order should you perform the actions? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer: Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/azure-databricks/databricks-extract-load-sql-data-warehouse
NEW QUESTION # 130......
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