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July 23, 2019 mavis

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Security and optimization
All cloud data must be encrypted at rest and in transit. The solution must support: parallel processing of customer data
hyper-scale storage of images
global region data replication of processed image data
You need to recommend a solution for storing the image tagging data. What should you recommend?
A. Azure File Storage
B. Azure Cosmos DB
C. Azure Blob Storage
D. Azure SQL Database
E. Azure SQL Data Warehouse

Correct Answer: C
Explanation
Explanation/Reference:
Explanation:
Image data must be stored in a single data store at minimum cost.
Note: Azure Blob storage is Microsoft’s object storage solution for the cloud. Blob storage is optimized for storing massive amounts of unstructured data. Unstructured data is data that does not adhere to a particular data model or definition, such as text or binary data.
Blob storage is designed for:
Serving images or documents directly to a browser. Storing files for distributed access.
Streaming video and audio.
Writing to log files.
Storing data for backup and restore, disaster recovery, and archiving. Storing data for analysis by an on-premises or Azure-hosted service. References:
https://docs.microsoft.com/en-us/azure/storage/blobs/storage-blobs-introduction

Technical
The solution has the following technical requirements:
Tagging data must be uploaded to the cloud from the New York office location.
Tagging data must be replicated to regions that are geographically close to company office locations. Image data must be stored in a single data store at minimum cost.
Customer data must be analyzed using managed Spark clusters. Power BI must be used to visualize transformed customer data. All data must be backed up in case disaster recovery is required.
Security and optimization
All cloud data must be encrypted at rest and in transit. The solution must support: parallel processing of customer data
hyper-scale storage of images
global region data replication of processed image data You need to design the solution for analyzing customer data. What should you recommend?
A. Azure Databricks
B. Azure Data Lake Storage
C. Azure SQL Data Warehouse
D. Azure Cognitive Services
E. Azure Batch

Correct Answer: A
Explanation
Explanation/Reference:
Explanation:
Customer data must be analyzed using managed Spark clusters. You create spark clusters through Azure Databricks.
References:
https://docs.microsoft.com/en-us/azure/azure-databricks/quickstart-create-databricks-workspace-portal

Security and optimization
All cloud data must be encrypted at rest and in transit. The solution must support: parallel processing of customer data
hyper-scale storage of images
global region data replication of processed image data You need to recommend a solution for storing customer data. What should you recommend?
A. Azure SQL Data Warehouse
B. Azure Stream Analytics
C. Azure Databricks
D. Azure SQL Database

Correct Answer: C
Explanation
Explanation/Reference:
Explanation:
From the scenario:
Customer data must be analyzed using managed Spark clusters.
All cloud data must be encrypted at rest and in transit. The solution must support: parallel processing of customer data. References:
https://www.microsoft.com/developerblog/2019/01/18/running-parallel-apache-spark-notebook-workloads-on-azure-databricks/

You need to design a backup solution for the processed customer data. What should you include in the design?
A. AzCopy
B. AdlCopy
C. Geo-Redundancy
D. Geo-Replication

Correct Answer: C
Explanation
Explanation/Reference:
Explanation:
Scenario: All data must be backed up in case disaster recovery is required.
Geo-redundant storage (GRS) is designed to provide at least 99.99999999999999% (16 9’s) durability of objects over a given year by replicating your data to a secondary region that is hundreds of miles away from the primary region. If your storage account has GRS enabled, then your data is durable even in the case of a complete regional outage or a disaster in which the primary region isn’t recoverable.
References:
https://docs.microsoft.com/en-us/azure/storage/common/storage-redundancy-grs

You plan to use an Azure SQL data warehouse to store the customer data. You need to recommend a disaster recovery solution for the data warehouse. What should you include in the recommendation?
A. AzCopy
B. Read-only replicas
C. AdlCopy
D. Geo-Redundant backups

Correct Answer: D
Explanation
Explanation/Reference:
Explanation:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/backup-and-restore

New Question
Case Study 2 Requirements Business
The company identifies the following business requirements:
You must transfer all images and customer data to cloud storage and remove on-premises servers. You must develop an analytical processing solution for transforming customer data.
You must develop an image object and color tagging solution. Capital expenditures must be minimized.
Cloud resource costs must be minimized.
Technical
The solution has the following technical requirements:
Tagging data must be uploaded to the cloud from the New York office location.
Tagging data must be replicated to regions that are geographically close to company office locations. Image data must be stored in a single data store at minimum cost.
Customer data must be analyzed using managed Spark clusters. Power BI must be used to visualize transformed customer data. All data must be backed up in case disaster recovery is required.
Security and optimization
All cloud data must be encrypted at rest and in transit. The solution must support: parallel processing of customer data
hyper-scale storage of images
global region data replication of processed image data Drag and Drop Question
You need to design the image processing solution to meet the optimization requirements for image tag data.
What should you configure? To answer, drag the appropriate setting to the correct drop targets. Each source may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Select and Place:
Correct Answer:
Explanation

Explanation/Reference:
Explanation:
Tagging data must be uploaded to the cloud from the New York office location.
Tagging data must be replicated to regions that are geographically close to company office locations.

Security and optimization
All cloud data must be encrypted at rest and in transit. The solution must support: parallel processing of customer data
hyper-scale storage of images
global region data replication of processed image data Hotspot Question
You need to design the image processing and storage solutions.

What should you recommend? To answer, select the appropriate configuration in the answer area. NOTE: Each correct selection is worth one point.
Hot Area:
Correct Answer:
Explanation
Explanation/Reference:
Explanation:
From the scenario:
The company identifies the following business requirements:
You must transfer all images and customer data to cloud storage and remove on-premises servers. You must develop an image object and color tagging solution.
The solution has the following technical requirements:
Image data must be stored in a single data store at minimum cost. All data must be backed up in case disaster recovery is required.
All cloud data must be encrypted at rest and in transit. The solution must support: hyper-scale storage of images
References:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/batch-processing https://docs.microsoft.com/en-us/azure/sql-database/sql-database-service-tier-hyperscale

New Question
Case Study 2 Requirements Business
The company identifies the following business requirements:
You must transfer all images and customer data to cloud storage and remove on-premises servers. You must develop an analytical processing solution for transforming customer data.
You must develop an image object and color tagging solution. Capital expenditures must be minimized.
Cloud resource costs must be minimized.
Technical
The solution has the following technical requirements:
Tagging data must be uploaded to the cloud from the New York office location.
Tagging data must be replicated to regions that are geographically close to company office locations. Image data must be stored in a single data store at minimum cost.
Customer data must be analyzed using managed Spark clusters. Power BI must be used to visualize transformed customer data. All data must be backed up in case disaster recovery is required.
Security and optimization
All cloud data must be encrypted at rest and in transit. The solution must support: parallel processing of customer data
hyper-scale storage of images
global region data replication of processed image data
Drag and Drop Question
You need to design the encryption strategy for the tagging data and customer data.
What should you recommend? To answer, drag the appropriate setting to the correct drop targets. Each source may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
Select and Place:
Correct Answer:
Explanation

Explanation/Reference:
Explanation:
All cloud data must be encrypted at rest and in transit.
Box 1: Transparent data encryption
Encryption of the database file is performed at the page level. The pages in an encrypted database are encrypted before they are written to disk and decrypted when read into memory.

Box 2: Encryption at rest
Encryption at Rest is the encoding (encryption) of data when it is persisted.
References:
https://docs.microsoft.com/en-us/sql/relational-databases/security/encryption/transparent-data-encryption?view=sql-server-2017 https://docs.microsoft.com/en-us/azure/security/azure-security-encryption-atrest

New Question
Case Study 3 Background
Current environment
The company has the following virtual machines (VMs):
Requirements
Storage and processing
You must be able to use a file system view of data stored in a blob.
You must build an architecture that will allow Contoso to use the DB FS filesystem layer over a blob store. The architecture will need to support data files, libraries, and images. Additionally, it must provide a web-based interface to documents that contain runnable command, visualizations, and narrative text such as a notebook.
CONT_SQL3 requires an initial scale of 35000 IOPS.
CONT_SQL1 and CONT_SQL2 must use the vCore model and should include replicas. The solution must support 8000 IOPS. The storage should be configured to optimized storage for database OLTP workloads.

Migration
You must be able to independently scale compute and storage resources.
You must migrate all SQL Server workloads to Azure. You must identify related machines in the on-premises environment, get disk size data usage information.
Data from SQL Server must include zone redundant storage.
You need to ensure that app components can reside on-premises while interacting with components that run in the Azure public cloud. SAP data must remain on-premises.
The Azure Site Recovery (ASR) results should contain per-machine data.

Business requirements
You must design a regional disaster recovery topology.
The database backups have regulatory purposes and must be retained for seven years.
CONT_SQL1 stores customers sales data that requires ETL operations for data analysis. A solution is required that reads data from SQL, performs ETL, and outputs to Power BI. The solution should use managed clusters to minimize costs. To optimize logistics, Contoso needs to analyze customer sales data to see if certain products are tied to specific times in the year.
The analytics solution for customer sales data must be available during a regional outage.

Security and auditing
Contoso requires all corporate computers to enable Windows Firewall. Azure servers should be able to ping other Contoso Azure servers.
Employee PII must be encrypted in memory, in motion, and at rest. Any data encrypted by SQL Server must support equality searches, grouping, indexing, and joining on the encrypted data.
Keys must be secured by using hardware security modules (HSMs). CONT_SQL3 must not communicate over the default ports

Cost
All solutions must minimize cost and resources.
The organization does not want any unexpected charges.
The data engineers must set the SQL Data Warehouse compute resources to consume 300 DWUs.
CONT_SQL2 is not fully utilized during non-peak hours. You must minimize resource costs for during non-peak hours.

You need to design a solution to meet the SQL Server storage requirements for CONT_SQL3. Which type of disk should you recommend?
A. Standard SSD Managed Disk
B. Premium SSD Managed Disk
C. Ultra SSD Managed Disk

Correct Answer: C
Explanation

Explanation/Reference:
Explanation:
CONT_SQL3 requires an initial scale of 35000 IOPS. Ultra SSD Managed Disk Offerings
The following table provides a comparison of ultra solid-state-drives (SSD) (preview), premium SSD, standard SSD, and standard hard disk drives (HDD) for managed disks to help you decide what to use.
References:
https://docs.microsoft.com/en-us/azure/virtual-machines/windows/disks-types

New Question
Case Study 3 Background
Current environment
The company has the following virtual machines (VMs):

Requirements
Storage and processing
You must be able to use a file system view of data stored in a blob.
You must build an architecture that will allow Contoso to use the DB FS filesystem layer over a blob store. The architecture will need to support data files, libraries, and images. Additionally, it must provide a web-based interface to documents that contain runnable command, visualizations, and narrative text such as a notebook.
CONT_SQL3 requires an initial scale of 35000 IOPS.
CONT_SQL1 and CONT_SQL2 must use the vCore model and should include replicas. The solution must support 8000 IOPS. The storage should be configured to optimized storage for database OLTP workloads.

You need to recommend an Azure SQL Database service tier. What should you recommend?
A. Business Critical

B. General Purpose
C. Premium
D. Standard
E. Basic

Correct Answer: C
Explanation

Explanation/Reference:
Explanation:
The data engineers must set the SQL Data Warehouse compute resources to consume 300 DWUs. Note: There are three architectural models that are used in Azure SQL Database:
General Purpose/Standard Business Critical/Premium Hyperscale
Incorrect Answers:
A: Business Critical service tier is designed for the applications that require low-latency responses from the underlying SSD storage (1-2 ms in average), fast recovery if the underlying infrastructure fails, or need to off-load reports, analytics, and read-only queries to the free of charge readable secondary replica of the primary database.
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-service-tier-business-critical

CONT_SQL3 requires an initial scale of 35000 IOPS.
CONT_SQL1 and CONT_SQL2 must use the vCore model and should include replicas. The solution must support 8000 IOPS. The storage should be configured to optimized storage for database OLTP workloads.

You need to recommend the appropriate storage and processing solution? What should you recommend?
A. Enable auto-shrink on the database.
B. Flush the blob cache using Windows PowerShell.
C. Enable Apache Spark RDD (RDD) caching.
D. Enable Databricks IO (DBIO) caching.

E. Configure the reading speed using Azure Data Studio.

Correct Answer: C
Explanation

Explanation/Reference:
Explanation:
Scenario: You must be able to use a file system view of data stored in a blob. You must build an architecture that will allow Contoso to use the DB FS filesystem layer over a blob store.
Databricks File System (DBFS) is a distributed file system installed on Azure Databricks clusters. Files in DBFS persist to Azure Blob storage, so you won’t lose data even after you terminate a cluster.
The Databricks Delta cache, previously named Databricks IO (DBIO) caching, accelerates data reads by creating copies of remote files in nodes’ local storage using a fast intermediate data format. The data is cached automatically whenever a file has to be fetched from a remote location. Successive reads of the same data are then performed locally, which results in significantly improved reading speed.
References:
https://docs.databricks.com/delta/delta-cache.html#delta-cache