Test Flashcards

For a corporation, you create data engineering solutions. Multiple sites in the firm have on-premises Microsoft SQL Server databases. Microsoft Power BI and Microsoft Azure Logic Apps must be used to integrate data. During the connection and transfer to the cloud, the solution must avoid single points of failure. Latency must also be minimized in the solution. Data communication between on-premises databases and Microsoft Azure must be safe. What are your options?

Answer: Install an Azure on-premises data gateway as a cluster at each location

To ensure high availability, minimize latency, and avoid single points of failure when integrating on-premises SQL Server databases with Azure services like Power BI and Logic Apps, you should install an Azure on-premises data gateway as a cluster at each location. A gateway cluster provides redundancy and load balancing, while placing gateways at each site reduces network latency for data access. This setup ensures secure and resilient data communication.

Azure HDInsight clusters are managed by the data engineering team. Because much of the data pipeline process happens in minutes, the team spends a lot of time constructing and removing clusters on a regular basis. You must implement a system that allows you to quickly deploy additional HDInsight clusters. What changes should you make?

Answer: Azure Resource Manager templates

To quickly and consistently deploy additional Azure HDInsight clusters, Azure Resource Manager (ARM) templates are the most effective solution. ARM templates allow you to define the entire infrastructure and configuration of your HDInsight clusters declaratively in a JSON file. This enables automated, repeatable, and standardized deployments, significantly reducing the time and effort spent on manual cluster setup and teardown.

You're a data architect, right? The data engineering team must set up data synchronization between an on-premises Microsoft SQL Server database and a cloud-based Microsoft SQL Server database. SQL Database on Azure. The on-premises production instance is overburdened with ad-hoc and reporting queries. The synchronization process must include the following steps: With minimal downtime, perform an initial data synchronization to Azure SQL Database. After initial synchronization, perform bi-directional data synchronization. This synchronization solution must be implemented. Which method of synchronization should you use?

Answer: Azure SQL Data Sync

Azure SQL Data Sync is the ideal solution for implementing bi-directional data synchronization between an on-premises Microsoft SQL Server database and an Azure SQL Database. It supports both initial data synchronization with minimal downtime and continuous bi-directional synchronization thereafter. This service is specifically designed for hybrid scenarios requiring ongoing data consistency between cloud and on-premises SQL environments.

A business has a SaaS solution that makes use of Azure SQL Database and elastic pools. Each customer organization has its own database in the solution. Peak consumption periods for customer organizations occur at various times throughout the year. To save money, you should use the Azure SQL Database elastic pool. Which option, if any, should you set up?

Answer: eDTUs and max data size

To save money with Azure SQL Database elastic pools, especially when customer peak consumption periods vary, you should configure the eDTUs (elastic Database Transaction Units) and the max data size. eDTUs represent the combined measure of CPU, memory, and I/O resources, allowing databases within the pool to share resources and burst when needed. By setting appropriate eDTU limits and maximum storage, you can optimize costs by provisioning for the aggregate demand rather than individual peaks.

Several on-premises Microsoft SQL Server databases are managed by a corporation. You must use a Microsoft SQL Server backup method to move the databases to Microsoft Azure. What type of data technology should you employ?

Answer: Azure SQL Database Managed Instance

Azure SQL Database Managed Instance is the most suitable Azure data technology for migrating on-premises Microsoft SQL Server databases using a native SQL Server backup method. Managed Instance offers near 100% compatibility with the latest SQL Server database engine, allowing direct backup and restore operations (via Azure Blob Storage). This minimizes migration effort and ensures compatibility with existing applications and features.

You're a data engineer for a corporation, and you've been tasked with setting up an Azure Data Lake Gen 2 storage account. Your organization wishes to ingest data from a variety of sources into the storage account. To ingest data from a local workstation, what should you use?

Answer: AzCopy Tool

To ingest data from a local workstation into an Azure Data Lake Storage Gen2 account, the AzCopy Tool is the most appropriate choice. AzCopy is a command-line utility designed for high-performance data transfer to and from Azure Storage, including ADLS Gen2. It efficiently handles large files and directories, making it ideal for local-to-cloud data movement.

An Azure Data Lake Gen 2 storage account has been created by a corporation. They wish to ingest data from numerous data sources into the storage account. Which of the following methods may they utilize to consume data from web server log files?

Answer: Azure Data Factory

Azure Data Factory (ADF) is the recommended method for consuming and ingesting web server log files into an Azure Data Lake Storage Gen2 account. ADF is a cloud-based ETL service that can orchestrate and automate data movement from various sources, including log files (e.g., from an HTTP endpoint or a staging blob storage), to ADLS Gen2. It provides robust scheduling, monitoring, and transformation capabilities for such recurring ingestion pipelines.

Andy is employed by TPT Ltd. He receives Twitter data through Azure Event and outputs it to an Azure Blob storage account using Azure Stream Analytics. Every two minutes, Andy is to output the total number of tweets received in the previous two minutes; each tweet is tallied just once. Andy should utilize which of the provided windowing functions to achieve the requirement?

Answer: A two-minute Tumbling window

A two-minute Tumbling window is the correct windowing function for this requirement. A tumbling window divides the data stream into distinct, non-overlapping, and contiguous time segments. By using a two-minute tumbling window, each tweet will fall into exactly one window and be counted once, providing the total number of tweets received in each successive two-minute interval.

You have Microsoft SQL Server installed on an Azure virtual computer. There is a table named Table1 on the server. Using an Azure Data Factory V2 copy activity, copy the data from Table1 to an Azure Data Lake Storage Gen2 account. What kind of integration runtime should you go with?

Answer: self-hosted integration runtime

When copying data from a SQL Server instance running on an Azure virtual machine (which is typically within a private virtual network) to Azure Data Lake Storage Gen2 using Azure Data Factory, a self-hosted integration runtime (SHIR) is required. The SHIR agent must be installed on a machine within the same virtual network as the SQL Server, enabling secure and private connectivity between ADF and the data source without exposing it to the public internet.