Download Microsoft.DP-200.ExamCollection.2021-02-13.229q.tqb
| Vendor: | Microsoft |
| Exam Code: | DP-200 |
| Exam Name: | Implementing an Azure Data Solution |
| Date: | Feb 13, 2021 |
| File Size: | 25 MB |
Demo Questions
Question 1
You are a data engineer implementing a lambda architecture on Microsoft Azure. You use an open-source big data solution to collect, process, and maintain data. The analytical data store performs poorly.
You must implement a solution that meets the following requirements:
- Provide data warehousing
- Reduce ongoing management activities
- Deliver SQL query responses in less than one second
You need to create an HDInsight cluster to meet the requirements.
Which type of cluster should you create?
- Interactive Query
- Apache Hadoop
- Apache HBase
- Apache Spark
Correct answer: D
Explanation:
Lambda Architecture with Azure:Azure offers you a combination of following technologies to accelerate real-time big data analytics:Azure Cosmos DB, a globally distributed and multi-model database service. Apache Spark for Azure HDInsight, a processing framework that runs large-scale data analytics applications. Azure Cosmos DB change feed, which streams new data to the batch layer for HDInsight to process. The Spark to Azure Cosmos DB Connector Note: Lambda architecture is a data-processing architecture designed to handle massive quantities of data by taking advantage of both batch processing and stream processing methods, and minimizing the latency involved in querying big data. References:https://sqlwithmanoj.com/2018/02/16/what-is-lambda-architecture-and-what-azure-offers-with-its-new-cosmos-db/ Lambda Architecture with Azure:
Azure offers you a combination of following technologies to accelerate real-time big data analytics:
- Azure Cosmos DB, a globally distributed and multi-model database service.
- Apache Spark for Azure HDInsight, a processing framework that runs large-scale data analytics applications.
- Azure Cosmos DB change feed, which streams new data to the batch layer for HDInsight to process.
- The Spark to Azure Cosmos DB Connector
Note: Lambda architecture is a data-processing architecture designed to handle massive quantities of data by taking advantage of both batch processing and stream processing methods, and minimizing the latency involved in querying big data.
References:
https://sqlwithmanoj.com/2018/02/16/what-is-lambda-architecture-and-what-azure-offers-with-its-new-cosmos-db/
Question 2
You develop data engineering solutions for a company. The company has on-premises Microsoft SQL Server databases at multiple locations.
The company must integrate data with Microsoft Power BI and Microsoft Azure Logic Apps. The solution must avoid single points of failure during connection and transfer to the cloud. The solution must also minimize latency.
You need to secure the transfer of data between on-premises databases and Microsoft Azure.
What should you do?
- Install a standalone on-premises Azure data gateway at each location
- Install an on-premises data gateway in personal mode at each location
- Install an Azure on-premises data gateway at the primary location
- Install an Azure on-premises data gateway as a cluster at each location
Correct answer: D
Explanation:
You can create high availability clusters of On-premises data gateway installations, to ensure your organization can access on-premises data resources used in Power BI reports and dashboards. Such clusters allow gateway administrators to group gateways to avoid single points of failure in accessing on-premises data resources. The Power BI service always uses the primary gateway in the cluster, unless it’s not available. In that case, the service switches to the next gateway in the cluster, and so on. References:https://docs.microsoft.com/en-us/power-bi/service-gateway-high-availability-clusters You can create high availability clusters of On-premises data gateway installations, to ensure your organization can access on-premises data resources used in Power BI reports and dashboards. Such clusters allow gateway administrators to group gateways to avoid single points of failure in accessing on-premises data resources. The Power BI service always uses the primary gateway in the cluster, unless it’s not available. In that case, the service switches to the next gateway in the cluster, and so on.
References:
https://docs.microsoft.com/en-us/power-bi/service-gateway-high-availability-clusters
Question 3
You are a data architect. The data engineering team needs to configure a synchronization of data between an on-premises Microsoft SQL Server database to Azure SQL Database.
Ad-hoc and reporting queries are being overutilized the on-premises production instance. The synchronization process must:
- Perform an initial data synchronization to Azure SQL Database with minimal downtime
- Perform bi-directional data synchronization after initial synchronization
You need to implement this synchronization solution.
Which synchronization method should you use?
- transactional replication
- Data Migration Assistant (DMA)
- backup and restore
- SQL Server Agent job
- Azure SQL Data Sync
Correct answer: E
Explanation:
SQL Data Sync is a service built on Azure SQL Database that lets you synchronize the data you select bi-directionally across multiple SQL databases and SQL Server instances. With Data Sync, you can keep data synchronized between your on-premises databases and Azure SQL databases to enable hybrid applications. Compare Data Sync with Transactional Replication References:https://docs.microsoft.com/en-us/azure/sql-database/sql-database-sync-data SQL Data Sync is a service built on Azure SQL Database that lets you synchronize the data you select bi-directionally across multiple SQL databases and SQL Server instances.
With Data Sync, you can keep data synchronized between your on-premises databases and Azure SQL databases to enable hybrid applications.
Compare Data Sync with Transactional Replication
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-sync-data
