HOTSPOT

You need to build a solution to collect the telemetry data for Race Control.

What should you use? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

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Correct Answer:

Explanation:

API: MongoDB

Consistency level: Strong

Use the strongest consistency Strong to minimize convergence time.

Scenario: The data must be written to the Azure datacentre closest to each race and must converge in the least amount of time.

References: https://docs.microsoft.com/en-us/azure/cosmos-db/consistency-levels

HOTSPOT

You are building the data store solution for Mechanical Workflow.

How should you configure Table1? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

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Correct Answer:

Explanation:

Table Type: Hash distributed.

Hash-distributed tables improve query performance on large fact tables.

Index type: Clusted columnstore

Scenario:

Mechanical Workflow has a named Table1 that is 1 TB. Large aggregations are performed on a single column of Table 1.

References: https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-tables-distribute

On which data store you configure TDE to meet the technical requirements?

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What should you include in the Data Factory pipeline for Race Central?

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You are monitoring the Data Factory pipeline that runs from Cosmos DB to SQL Database for Race Central.

You discover that the job takes 45 minutes to run.

What should you do to improve the performance of the job?

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Which two metrics should you use to identify the appropriate RU/s for the telemetry data? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

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Topic 4, ADatum Corporation

Case study

Overview

ADatum Corporation is a retailer that sells products through two sales channels: retail stores and a website.

Existing Environment

ADatum has one database server that has Microsoft SQL Server 2016 installed. The server hosts three mission-critical databases named SALESDB, DOCDB, and REPORTINGDB.

SALESDB collects data from the stored and the website.

DOCDB stored documents that connect to the sales data in SALESDB. The documents are stored in two different JSON formats based on the sales channel.

REPORTINGDB stores reporting data and contains server columnstore indexes. A daily process creates reporting data in REPORTINGDB from the data in SALESDB. The process is implemented as a SQL Server Integration Services (SSIS) package that runs a stored procedure from SALESDB.

Requirements

Planned Changes

ADatum plans to move the current data infrastructure to Azure.

The new infrastructure has the following requirements:

– Migrate SALESDB and REPORTINGDB to an Azure SQL database.

– Migrate DOCDB to Azure Cosmos DB.

– The sales data including the documents in JSON format, must be gathered as it arrives and analyzed online by using Azure Stream Analytics. The analytic process will perform aggregations that must be done continuously, without gaps, and without overlapping.

– As they arrive, all the sales documents in JSON format must be transformed into one consistent format.

– Azure Data Factory will replace the SSIS process of copying the data from SALESDB to REPORTINGDB.

Technical Requirements

The new Azure data infrastructure must meet the following technical requirements:

– Data in SALESDB must encrypted by using Transparent Data Encryption (TDE). The encryption must use your own key.

– SALESDB must be restorable to any given minute within the past three weeks.

– Real-time processing must be monitored to ensure that workloads are sized properly based on actual usage patterns.

– Missing indexes must be created automatically for REPORTINGDB.

– Disk IO, CPU, and memory usage must be monitored for SALESDB.

You need to implement event processing by using Stream Analytics to produce consistent JSON documents.

Which three actions should you perform? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.

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DRAG DROP

You need to replace the SSIS process by using Data Factory.

Which four 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.

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Correct Answer:

Explanation:

Scenario: A daily process creates reporting data in REPORTINGDB from the data in SALESDB. The process is implemented as a SQL Server Integration Services (SSIS) package that runs a stored procedure from SALESDB.

Step 1: Create a linked service to each database

Step 2: Create two datasets

You can create two datasets: InputDataset and OutputDataset. These datasets are of type AzureBlob. They refer to the Azure Storage linked service that you created in the previous section.

Step 3: Create a pipeline

You create and validate a pipeline with a copy activity that uses the input and output datasets.

Step 4: Add a copy activity

References: https://docs.microsoft.com/en-us/azure/data-factory/quickstart-create-data-factory-portal

DRAG DROP

You need to implement the encryption for SALESDB.

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.

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Correct Answer:

Explanation:

Data in SALESDB must encrypted by using Transparent Data Encryption (TDE). The encryption must use your own key.

Step 1: Implement an Azure key vault

You must create an Azure Key Vault and Key to use for TDE

Step 2: Create a key

Step 3: From the settings of the Azure SQL database …

You turn transparent data encryption on and off on the database level.

References: https://docs.microsoft.com/en-us/azure/sql-database/transparent-data-encryption-byok-azure-sql-configure

Which windowing function should you use to perform the streaming aggregation of the sales data?

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