Ultimate Guide to Prepare DP-200 with Accurate PDF Questions [Jan 13, 2022]
Pass Microsoft With VCETorrent Exam Dumps
Schedule exam
Languages: English, Japanese, Chinese (Simplified), Korean
Retirement date: **
This exam measures your ability to accomplish the following technical tasks: implement data storage solutions; manage and develop data processing; and monitor and optimize data solutions.
How to study the DP-200 Exam
VCETorrent expert team recommends you to prepare some notes on these topics along with it don’t forget to practice Microsoft DP-200 Exam dumps which been written by our expert team, Both these will help you a lot to clear this exam with good marks.
NEW QUESTION 69
You manage the Microsoft Azure Databricks environment for a company. You must be able to access a private Azure Blob Storage account. Data must be available to all Azure Databricks workspaces. You need to provide the data access.
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.
Answer:
Explanation:
References:
https://docs.databricks.com/spark/latest/data-sources/azure/azure-storage.html
NEW QUESTION 70
A company builds an application to allow developers to share and compare code. The conversations, code snippets, and links shared by people in the application are stored in a Microsoft Azure SQL Database instance.
The application allows for searches of historical conversations and code snippets.
When users share code snippets, the code snippet is compared against previously share code snippets by using a combination of Transact-SQL functions including SUBSTRING, FIRST_VALUE, and SQRT. If a match is found, a link to the match is added to the conversation.
Customers report the following issues:
* Delays occur during live conversations
* A delay occurs before matching links appear after code snippets are added to conversations You need to resolve the performance issues.
Which technologies should you use? To answer, drag the appropriate technologies to the correct issues. Each technology 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.
Answer:
Explanation:
Explanation
Box 1: memory-optimized table
In-Memory OLTP can provide great performance benefits for transaction processing, data ingestion, and transient data scenarios.
Box 2: materialized view
To support efficient querying, a common solution is to generate, in advance, a view that materializes the data in a format suited to the required results set. The Materialized View pattern describes generating prepopulated views of data in environments where the source data isn't in a suitable format for querying, where generating a suitable query is difficult, or where query performance is poor due to the nature of the data or the data store.
These materialized views, which only contain data required by a query, allow applications to quickly obtain the information they need. In addition to joining tables or combining data entities, materialized views can include the current values of calculated columns or data items, the results of combining values or executing transformations on the data items, and values specified as part of the query. A materialized view can even be optimized for just a single query.
References:
https://docs.microsoft.com/en-us/azure/architecture/patterns/materialized-view
NEW QUESTION 71
You need to ensure that phone-based poling data can be analyzed in the PollingData database.
How should you configure Azure Data Factory?
- A. Use a schedule trigger
- B. Use an event-based trigger
- C. Use manual execution
- D. Use a tumbling schedule trigger
Answer: A
Explanation:
Explanation/Reference:
Explanation:
When creating a schedule trigger, you specify a schedule (start date, recurrence, end date etc.) for the trigger, and associate with a Data Factory pipeline.
Scenario:
All data migration processes must use Azure Data Factory
All data migrations must run automatically during non-business hours
References:
https://docs.microsoft.com/en-us/azure/data-factory/how-to-create-schedule-trigger Testlet 3 Overview Current environment Contoso relies on an extensive partner network for marketing, sales, and distribution. Contoso uses external companies that manufacture everything from the actual pharmaceutical to the packaging.
The majority of the company's data reside in Microsoft SQL Server database. Application databases fall into one of the following tiers:
The company has a reporting infrastructure that ingests data from local databases and partner services.
Partners services consists of distributors, wholesales, and retailers across the world. The company performs daily, weekly, and monthly reporting.
Requirements
Tier 3 and Tier 6 through Tier 8 application must use database density on the same server and Elastic pools in a cost-effective manner.
Applications must still have access to data from both internal and external applications keeping the data encrypted and secure at rest and in transit.
A disaster recovery strategy must be implemented for Tier 3 and Tier 6 through 8 allowing for failover in the case of server going offline.
Selected internal applications must have the data hosted in single Microsoft Azure SQL Databases.
Tier 1 internal applications on the premium P2 tier
Tier 2 internal applications on the standard S4 tier
The solution must support migrating databases that support external and internal application to Azure SQL Database. The migrated databases will be supported by Azure Data Factory pipelines for the continued movement, migration and updating of data both in the cloud and from local core business systems and repositories.
Tier 7 and Tier 8 partner access must be restricted to the database only.
In addition to default Azure backup behavior, Tier 4 and 5 databases must be on a backup strategy that performs a transaction log backup eve hour, a differential backup of databases every day and a full back up every week.
Back up strategies must be put in place for all other standalone Azure SQL Databases using Azure SQL- provided backup storage and capabilities.
Databases
Contoso requires their data estate to be designed and implemented in the Azure Cloud. Moving to the cloud must not inhibit access to or availability of data.
Databases:
Tier 1 Database must implement data masking using the following masking logic:
Tier 2 databases must sync between branches and cloud databases and in the event of conflicts must be set up for conflicts to be won by on-premises databases.
Tier 3 and Tier 6 through Tier 8 applications must use database density on the same server and Elastic pools in a cost-effective manner.
Applications must still have access to data from both internal and external applications keeping the data encrypted and secure at rest and in transit.
A disaster recovery strategy must be implemented for Tier 3 and Tier 6 through 8 allowing for failover in the case of a server going offline.
Selected internal applications must have the data hosted in single Microsoft Azure SQL Databases.
Tier 1 internal applications on the premium P2 tier
Tier 2 internal applications on the standard S4 tier
Reporting
Security and monitoring
Security
A method of managing multiple databases in the cloud at the same time is must be implemented to streamlining data management and limiting management access to only those requiring access.
Monitoring
Monitoring must be set up on every database. Contoso and partners must receive performance reports as part of contractual agreements.
Tiers 6 through 8 must have unexpected resource storage usage immediately reported to data engineers.
The Azure SQL Data Warehouse cache must be monitored when the database is being used. A dashboard monitoring key performance indicators (KPIs) indicated by traffic lights must be created and displayed based on the following metrics:
Existing Data Protection and Security compliances require that all certificates and keys are internally managed in an on-premises storage.
You identify the following reporting requirements:
Azure Data Warehouse must be used to gather and query data from multiple internal and external
databases
Azure Data Warehouse must be optimized to use data from a cache
Reporting data aggregated for external partners must be stored in Azure Storage and be made
available during regular business hours in the connecting regions
Reporting strategies must be improved to real time or near real time reporting cadence to improve
competitiveness and the general supply chain
Tier 9 reporting must be moved to Event Hubs, queried, and persisted in the same Azure region as the
company's main office
Tier 10 reporting data must be stored in Azure Blobs
Issues
Team members identify the following issues:
Both internal and external client application run complex joins, equality searches and group-by clauses.
Because some systems are managed externally, the queries will not be changed or optimized by Contoso External partner organization data formats, types and schemas are controlled by the partner companies
Internal and external database development staff resources are primarily SQL developers familiar with
the Transact-SQL language.
Size and amount of data has led to applications and reporting solutions not performing are required
speeds
Tier 7 and 8 data access is constrained to single endpoints managed by partners for access
The company maintains several legacy client applications. Data for these applications remains isolated
form other applications. This has led to hundreds of databases being provisioned on a per application basis
NEW QUESTION 72
You have an Azure SQL database that contains a table named Customer. Customer contains the columns shown in the following table.
You apply a masking rule as shown in the following table.
Which users can view the email addresses of the customers?
- A. All users who are granted the UNMASK permission to the Customer_Email column only.
- B. Server administrators only.
- C. Server administrators and all users who are granted the UNMASK permission to the Customer_Email column only.
- D. Server administrators and all users who are granted the SELECT permission to the Customer_Email column only.
Answer: A
Explanation:
Explanation
Grant the UNMASK permission to a user to enable them to retrieve unmasked data from the columns for which masking is defined.
Reference:
https://docs.microsoft.com/en-us/sql/relational-databases/security/dynamic-data-masking
NEW QUESTION 73
You have a self-hosted integration runtime in Azure Data Factory.
The current status of the integration runtime has the following configurations:
Status: Running
Type: Self-Hosted
Version: 4.4.7292.1
Running / Registered Node(s): 1/1
High Availability Enabled: False
Linked Count: 0
Queue Length: 0
Average Queue Duration: 0.00s
The integration runtime has the following node details:
Name: X-M
Status: Running
Version: 4.4.7292.1
Available Memory: 7697MB
CPU Utilization: 6%
Network (In/Out): 1.21KBps/0.83KBps
Concurrent Jobs (Running/Limit): 2/14
Role: Dispatcher/Worker
Credential Status: In Sync
Use the drop-down menus to select the answer choice that completes each statement based on the information presented.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: fail until the node comes back online
We see: High Availability Enabled: False
Note: Higher availability of the self-hosted integration runtime so that it's no longer the single point of failure in your big data solution or cloud data integration with Data Factory.
Box 2: lowered
We see:
Concurrent Jobs (Running/Limit): 2/14
CPU Utilization: 6%
Note: When the processor and available RAM aren't well utilized, but the execution of concurrent jobs reaches a node's limits, scale up by increasing the number of concurrent jobs that a node can run Reference:
https://docs.microsoft.com/en-us/azure/data-factory/create-self-hosted-integration-runtime
NEW QUESTION 74
You have an Azure SQL database that contains a table named Customer. Customer contains the columns shown in the following table.
You plan to implement a dynamic data mask for the Customer_Phone column. The mask must meet the following requirements:
The first six numerals of the customer phone numbers must be masked.
The last four digits of the customer phone numbers must be visible.
Hyphens must be preserved and displayed.
How should you configure the dynamic data mask? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/sql/relational-databases/security/dynamic-data-masking?view=sql-server-ver15
NEW QUESTION 75
You have an Azure SQL database named DB1 in the Each US 2 region.
You need to build a secondary geo-replicated copy of DB1 in the West US region on a new server.
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.
Answer:
Explanation:
Step 1: From the Geo-replication settings of DB1, select West US
The following steps create a new secondary database in a geo-replication partnership.
1. In the Azure portal, browse to the database that you want to set up for geo-replication.
2. (Step 1) On the SQL database page, select geo-replication, and then select the region to create the secondary database.
3. (Step 2-3) Select or configure the server and pricing tier for the secondary database.
Step 2: Create a target server and select a pricing tier
Step 3: On the secondary server, create logins that match the SIDs on the primary server.
NEW QUESTION 76
You manage security for a database that supports a line of business application.
Private and personal data stored in the database must be protected and encrypted.
You need to configure the database to use Transparent Data Encryption (TDE).
Which five actions should you perform in sequence? To answer, select the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation:
Step 1: Create a master key
Step 2: Create or obtain a certificate protected by the master key
Step 3: Set the context to the company database
Step 4: Create a database encryption key and protect it by the certificate
Step 5: Set the database to use encryption
Example code:
USE master;
GO
CREATE MASTER KEY ENCRYPTION BY PASSWORD = '<UseStrongPasswordHere>';
go
CREATE CERTIFICATE MyServerCert WITH SUBJECT = 'My DEK Certificate';
go
USE AdventureWorks2012;
GO
CREATE DATABASE ENCRYPTION KEY
WITH ALGORITHM = AES_128
ENCRYPTION BY SERVER CERTIFICATE MyServerCert;
GO
ALTER DATABASE AdventureWorks2012
SET ENCRYPTION ON;
GO
References:
https://docs.microsoft.com/en-us/sql/relational-databases/security/encryption/transparent-data-encryption
NEW QUESTION 77
You need to receive an alert when Azure SQL Data Warehouse consumes the maximum allotted resources.
Which resource type and signal should you use to create the alert in Azure Monitor? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Resource type: SQL data warehouse
DWU limit belongs to the SQL data warehouse resource type.
Signal: DWU USED
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-insights-alerts-portal
NEW QUESTION 78
You are processing streaming data from vehicles that pass through a toll booth.
You need to use Azure Stream Analytics to return the license plate, vehicle make, and hour the last vehicle passed during each 10-minute window.
How should you complete the query? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: MAX
The first step on the query finds the maximum time stamp in 10-minute windows, that is the time stamp of the last event for that window. The second step joins the results of the first query with the original stream to find the event that match the last time stamps in each window.
Query:
WITH LastInWindow AS
(
SELECT
MAX(Time) AS LastEventTime
FROM
Input TIMESTAMP BY Time
GROUP BY
TumblingWindow(minute, 10)
)
SELECT
Input.License_plate,
Input.Make,
Input.Time
FROM
Input TIMESTAMP BY Time
INNER JOIN LastInWindow
ON DATEDIFF(minute, Input, LastInWindow) BETWEEN 0 AND 10
AND Input.Time = LastInWindow.LastEventTime
Box 2: TumblingWindow
Tumbling windows are a series of fixed-sized, non-overlapping and contiguous time intervals.
Box 3: DATEDIFF
DATEDIFF is a date-specific function that compares and returns the time difference between two DateTime fields, for more information, refer to date functions.
Reference:
https://docs.microsoft.com/en-us/stream-analytics-query/tumbling-window-azure-stream-analytics
NEW QUESTION 79
You have a table named SalesFact in an Azure SQL data warehouse. SalesFact contains sales data from the past 36 months and has the following characteristics:
* Is partitioned by month
* Contains one billion rows
* Has clustered columnstore indexes
All the beginning of each month, you need to remove data SalesFact that is older than 36 months as quickly as possible.
Which three actions should you perform in sequence in a stored procedure? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
Answer:
Explanation:
Explanation
Step 1: Create an empty table named SalesFact_work that has the same schema as SalesFact.
Step 2: Switch the partition containing the stale data from SalesFact to SalesFact_Work.
SQL Data Warehouse supports partition splitting, merging, and switching. To switch partitions between two tables, you must ensure that the partitions align on their respective boundaries and that the table definitions match.
Loading data into partitions with partition switching is a convenient way stage new data in a table that is not visible to users the switch in the new data.
Step 3: Drop the SalesFact_Work table.
References:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-tables-partition
NEW QUESTION 80
A company plans to analyze a continuous flow of data from a social media platform by using Microsoft Azure Stream Analytics. The incoming data is formatted as one record per row.
You need to create the input stream.
How should you complete the REST API segment? To answer, select the appropriate configuration in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: CSV
A comma-separated values (CSV) file is a delimited text file that uses a comma to separate values. A CSV file stores tabular data (numbers and text) in plain text. Each line of the file is a data record.
JSON and AVRO are not formatted as one record per row.
Box 2: "type":"Microsoft.ServiceBus/EventHub",
Properties include "EventHubName"
References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-define-inputs
https://en.wikipedia.org/wiki/Comma-separated_values
NEW QUESTION 81
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this scenario, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have a container named Sales in an Azure Cosmos DB database. Sales has 120 GB of data. Each entry in Sales has the following structure.
The partition key is set to the OrderId attribute.
Users report that when they perform queries that retrieve data by ProductName, the queries take longer than expected to complete.
You need to reduce the amount of time it takes to execute the problematic queries.
Solution: You create a lookup collection that uses ProductName as a partition key and OrderId as a value.
Does this meet the goal?
- A. No
- B. Yes
Answer: B
Explanation:
Explanation
One option is to have a lookup collection "ProductName" for the mapping of "ProductName" to "OrderId".
References:
https://azure.microsoft.com/sv-se/blog/azure-cosmos-db-partitioning-design-patterns-part-1/
NEW QUESTION 82
Which masking functions should you implement for each column to meet the data masking requirements? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: Default
Default uses a zero value for numeric data types (bigint, bit, decimal, int, money, numeric, smallint, smallmoney, tinyint, float, real).
Only Show a zero value for the values in a column named ShockOilWeight.
Box 2: Credit Card
The Credit Card Masking method exposes the last four digits of the designated fields and adds a constant string as a prefix in the form of a credit card.
Example: XXXX-XXXX-XXXX-1234
Only show the last four digits of the values in a column named SuspensionSprings.
Scenario:
The company identifies the following data masking requirements for the Race Central data that will be stored in SQL Database:
Only Show a zero value for the values in a column named ShockOilWeight.
Only show the last four digits of the values in a column named SuspensionSprings.
NEW QUESTION 83
You develop data engineering solutions for a company.
You need to ingest and visualize real-time Twitter data by using Microsoft Azure.
Which three technologies should you use? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
- A. Azure Stream Analytics Job that queries Twitter data from an Event Grid
- B. Logic App that sends Twitter posts which have target keywords to Azure
- C. Event Hub instance
- D. Event Grid subscription
- E. Event Grid topic
- F. Azure Stream Analytics Job that queries Twitter data from an Event Hub
Answer: B,C,F
Explanation:
Explanation
You can use Azure Logic apps to send tweets to an event hub and then use a Stream Analytics job to read from event hub and send them to PowerBI.
References:
https://community.powerbi.com/t5/Integrations-with-Files-and/Twitter-streaming-analytics-step-by-step/td-p/959
NEW QUESTION 84
A company builds an application to allow developers to share and compare code. The conversations, code snippets, and links shared by people in the application are stored in a Microsoft Azure SQL Database instance. The application allows for searches of historical conversations and code snippets.
When users share code snippets, the code snippet is compared against previously share code snippets by using a combination of Transact-SQL functions including SUBSTRING, FIRST_VALUE, and SQRT. If a match is found, a link to the match is added to the conversation.
Customers report the following issues:
Delays occur during live conversations
A delay occurs before matching links appear after code snippets are added to conversations You need to resolve the performance issues.
Which technologies should you use? To answer, drag the appropriate technologies to the correct issues. Each technology 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.
Answer:
Explanation:
Explanation
Box 1: memory-optimized table
In-Memory OLTP can provide great performance benefits for transaction processing, data ingestion, and transient data scenarios.
Box 2: materialized view
To support efficient querying, a common solution is to generate, in advance, a view that materializes the data in a format suited to the required results set. The Materialized View pattern describes generating prepopulated views of data in environments where the source data isn't in a suitable format for querying, where generating a suitable query is difficult, or where query performance is poor due to the nature of the data or the data store.
These materialized views, which only contain data required by a query, allow applications to quickly obtain the information they need. In addition to joining tables or combining data entities, materialized views can include the current values of calculated columns or data items, the results of combining values or executing transformations on the data items, and values specified as part of the query. A materialized view can even be optimized for just a single query.
References:
https://docs.microsoft.com/en-us/azure/architecture/patterns/materialized-view
NEW QUESTION 85
Which masking functions should you implement for each column to meet the data masking requirements? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/database/dynamic-data-masking-overview Overview ADatum Corporation is a retailer that sells products through two sales channels: retail stores and a website.
NEW QUESTION 86
Use the following login credentials as needed:
Azure Username: xxxxx
Azure Password: xxxxx
The following information is for technical support purposes only:
Lab Instance: 10543936
You need to replicate db1 to a new Azure SQL server named db1-copy10543936 in the US West region.
To complete this task, sign in to the Azure portal.
Answer:
Explanation:
See the explanation below.
Explanation
1. In the Azure portal, browse to the database db1-copy10543936 that you want to set up for geo-replication.
2. On the SQL database page, select geo-replication, and then select the region to create the secondary database: US West region
3. Select or configure the server and pricing tier for the secondary database.
4. Click Create to add the secondary.
5. The secondary database is created and the seeding process begins.
6. When the seeding process is complete, the secondary database displays its status.
Reference:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-active-geo-replication-portal
NEW QUESTION 87
Your company uses Microsoft Azure SQL Database configure with Elastic pool. You use Elastic Database jobs to run queries across all databases in the pod.
You need to analyze, troubleshoot, and report on components responsible for running Elastic Database jobs.
You need to determine the component responsible for running job service tasks.
Which components should you use for each Elastic pool job services task? To answer, drag the appropriate component to the correct task. Each component 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.
Answer:
Explanation:
Explanation
Execution results and diagnostics: Azure Storage
Job launcher and tracker: Job Service
Job metadata and state: Control database
The Job database is used for defining jobs and tracking the status and history of job executions. The Job database is also used to store agent metadata, logs, results, job definitions, and also contains many useful stored procedures, and other database objects, for creating, running, and managing jobs using T-SQL.
References:
https://docs.microsoft.com/en-us/azure/sql-database/sql-database-job-automation-overview
NEW QUESTION 88
You are implementing Azure Stream Analytics functions.
Which windowing function should you use for each requirement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Tumbling
Tumbling window functions are used to segment a data stream into distinct time segments and perform a function against them, such as the example below. The key differentiators of a Tumbling window are that they repeat, do not overlap, and an event cannot belong to more than one tumbling window.
Box 2: Hoppping
Hopping window functions hop forward in time by a fixed period. It may be easy to think of them as Tumbling windows that can overlap, so events can belong to more than one Hopping window result set. To make a Hopping window the same as a Tumbling window, specify the hop size to be the same as the window size.
Box 3: Sliding
Sliding window functions, unlike Tumbling or Hopping windows, produce an output only when an event occurs. Every window will have at least one event and the window continuously moves forward by an € (epsilon). Like hopping windows, events can belong to more than one sliding window.
References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-window-functions
NEW QUESTION 89
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this scenario, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You are developing a solution that will use Azure Stream Analytics. The solution will accept an Azure Blob storage file named Customers. The file will contain both in-store and online customer details. The online customers will provide a mailing address.
You have a file in Blob storage named LocationIncomes that contains based on location. The file rarely changes.
You need to use an address to look up a median income based on location. You must output the data to Azure SQL Database for immediate use and to Azure Data Lake Storage Gen2 for long-term retention.
Solution: You implement a Stream Analytics job that has one streaming input, one reference input, one query, and two outputs.
Does this meet the goal?
- A. No
- B. Yes
Answer: A
Explanation:
Explanation
We need one reference data input for LocationIncomes, which rarely changes.
We need two queries, on for in-store customers, and one for online customers.
For each query two outputs is needed.
Note: Stream Analytics also supports input known as reference data. Reference data is either completely static or changes slowly.
References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-add-inputs#stream-and-reference-inpu
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-define-outputs
NEW QUESTION 90
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?
- A. SQL Server Agent job
- B. Data Migration Assistant (DMA)
- C. Azure SQL Data Sync
- D. backup and restore
- E. transactional replication
Answer: C
Explanation:
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
NEW QUESTION 91
A company is deploying a service-based data environment. You are developing a solution to process this data.
The solution must meet the following requirements:
* Use an Azure HDInsight cluster for data ingestion from a relational database in a different cloud service
* Use an Azure Data Lake Storage account to store processed data
* Allow users to download processed data
You need to recommend technologies for the solution.
Which technologies should you use? To answer, select the appropriate options in the answer area.
Answer:
Explanation:
Explanation
Box 1: Apache Sqoop
Apache Sqoop is a tool designed for efficiently transferring bulk data between Apache Hadoop and structured datastores such as relational databases.
Azure HDInsight is a cloud distribution of the Hadoop components from the Hortonworks Data Platform (HDP).
NEW QUESTION 92
......
Microsoft Implementing an Azure Data Solution Exam Certification Details:
| Sample Questions | Microsoft Implementing an Azure Data Solution Sample Questions |
| Passing Score | 700 / 1000 |
| Number of Questions | 40-60 |
| Schedule Exam | Pearson VUE |
| Exam Name | Microsoft Certified - Azure Data Engineer Associate |
| Duration | 120 mins |
| Exam Price | $165 (USD) |
| Exam Code | DP-200 |
| Books / Training | Course DP-200T01-A: Implementing an Azure Data Solution |
Latest DP-200 Exam Dumps - Valid and Updated Dumps: https://www.vcetorrent.com/DP-200-valid-vce-torrent.html