Microsoft DP-203 유효한 시험대비자료 만약 떨어지셨다면 우리는 덤프비용전액을 환불해드립니다, 이와 같은 피타는 노력으로 만들어진 DP-203 덤프는 이미 많은 분들을 도와DP-203시험을 패스하여 자격증을 손에 넣게 해드렸습니다, Microsoft DP-203 유효한 시험대비자료 합격가능한 높은 시험적중율, 제일 빠른 시일내에 제일 간단한 방법으로Microsoft인증 DP-203시험을 패스하는 방법이 없냐구요, 하지만 저희는 수시로 Microsoft DP-203시험문제 변경을 체크하여 Data Engineering on Microsoft Azure덤프를 가장 최신버전으로 업데이트하도록 최선을 다하고 있습니다, Microsoft DP-203 유효한 시험대비자료 덤프 구매후 업데이트 서비스.

그리고 제 옆자리를 손바닥을 톡톡 두드리며 도현에게 물었다, 무의식중에, DP-203높은 통과율 덤프샘플문제그 아픔을 알고, 통통한 면발에 고루 묻은 소스와 함께 잘 보니 양파도 함께 볶아 넣은 것 같았다, 그녀의 심장에 화흔처럼 새겨진 그분의 얼굴이.

DP-203 덤프 다운받기

은설이 황당해하며 묻자, 유경은 갑자기 아픈 척 엄살을 부렸다, 어차피DP-203높은 통과율 덤프샘플문제조금 늦게 알려준다고 해서 달라지는 것은 없을 것이다, 그리고.별말씀을, 아.사진만 봤을 때는 별문제 없었다, 제가, 제가 아직은 몸이 다 회복을.

물고기가 다 도망가잖아, 그러는 운검 나리야말로 아무 죄 없는 백성을 해DP-203인증시험치려고 하신 게 부끄럽지도 않으십니까, 이건 감동이 아니라 황당함이다, 그와 함께 진한 단 냄새가 로벨리아의 코를 찔렀다, 너는 애인도 있는 애가.

강 팀장은 점심에 외근이지, 그런데 또 그때 갈고닦은 실력이 교도소에 오니DP-203높은 통과율 시험덤프까 이렇게 빛을 발하더라고요, 황제가 하사한 물건들을 조선까지 가져가기 위해서는 사람들이 많이 필요했기 때문이다, 한열구 쪽으로 한 남자가 다가왔다.

이게 누구래, 그런데 부족해도 한참 부족했다, 하루에 두세 군데 꼴로 은월의(https://www.passtip.net/DP-203-pass-exam.html)깃발이 꽂힌 곳을 만날 수 있었다, 꿈이라면 깨어나고 싶지 않을 만큼.그녀의 예쁜 눈이 곱게 휘었다, 수문장은 부하들에게 문을 열라는 신호를 보냈다.

방정맞은 집 전화 소리에 고은이 비닐장갑을 벗고 거실로 달려갔다, 매사에 조심 또 조심하여라.이레가 스승들의 따뜻한 말에 감사의 마음을 전했다, Microsoft DP-203 덤프로Microsoft DP-203시험을 패스하여 자격즉을 쉽게 취득해보지 않으실래요?

DP-203 유효한 시험대비자료 시험준비에 가장 좋은 기출문제 모은 덤프자료

주아의 머릿속엔 낮에 들었던 혜원의 말이 내내 맴돌(https://www.passtip.net/DP-203-pass-exam.html)았다, 잠시만 기다려주시겠어요, 검사 측은 지금 사태의 심각성을 부풀리고 사안의 초점을 흐리고 있습니다.

Data Engineering on Microsoft Azure 덤프 다운받기

NEW QUESTION 46
You have an Azure Databricks workspace named workspace! in the Standard pricing tier. Workspace! contains an all-purpose cluster named cluster). You need to reduce the time it takes for cluster 1 to start and scale up. The solution must minimize costs. What should you do first?

• A. Create a pool in workspace1.
• B. Upgrade workspace! to the Premium pricing tier.
• C. Configure a global init script for workspace1.
• D. Create a cluster policy in workspace1.

Answer: A

Explanation:
Topic 2, Contoso
Transactional Date
Contoso has three years of customer, transactional, operation, sourcing, and supplier data comprised of 10 billion records stored across multiple on-premises Microsoft SQL Server servers. The SQL server instances contain data from various operational systems. The data is loaded into the instances by using SQL server integration Services (SSIS) packages.
You estimate that combining all product sales transactions into a company-wide sales transactions dataset will result in a single table that contains 5 billion rows, with one row per transaction.
Most queries targeting the sales transactions data will be used to identify which products were sold in retail stores and which products were sold online during different time period. Sales transaction data that is older than three years will be removed monthly.
You plan to create a retail store table that will contain the address of each retail store. The table will be approximately 2 MB. Queries for retail store sales will include the retail store addresses.
You plan to create a promotional table that will contain a promotion ID. The promotion ID will be associated to a specific product. The product will be identified by a product ID. The table will be approximately 5 GB.
Streaming Twitter Data
The ecommerce department at Contoso develops and Azure logic app that captures trending Twitter feeds referencing the company's products and pushes the products to Azure Event Hubs.
Planned Changes
Contoso plans to implement the following changes:
* Load the sales transaction dataset to Azure Synapse Analytics.
* Integrate on-premises data stores with Azure Synapse Analytics by using SSIS packages.
* Use Azure Synapse Analytics to analyze Twitter feeds to assess customer sentiments about products.
Sales Transaction Dataset Requirements
Contoso identifies the following requirements for the sales transaction dataset:
* Partition data that contains sales transaction records. Partitions must be designed to provide efficient loads by month. Boundary values must belong: to the partition on the right.
* Ensure that queries joining and filtering sales transaction records based on product ID complete as quickly as possible.
* Implement a surrogate key to account for changes to the retail store addresses.
* Ensure that data storage costs and performance are predictable.
* Minimize how long it takes to remove old records.
Customer Sentiment Analytics Requirement
Contoso identifies the following requirements for customer sentiment analytics:
* Allow Contoso users to use PolyBase in an A/ure Synapse Analytics dedicated SQL pool to query the content of the data records that host the Twitter feeds. Data must be protected by using row-level security (RLS). The users must be authenticated by using their own A/ureAD credentials.
* Maximize the throughput of ingesting Twitter feeds from Event Hubs to Azure Storage without purchasing additional throughput or capacity units.
* Store Twitter feeds in Azure Storage by using Event Hubs Capture. The feeds will be converted into Parquet files.
* Ensure that the data store supports Azure AD-based access control down to the object level.
* Minimize administrative effort to maintain the Twitter feed data records.
* Purge Twitter feed data records;itftaitJ are older than two years.
Data Integration Requirements
Contoso identifies the following requirements for data integration:
Use an Azure service that leverages the existing SSIS packages to ingest on-premises data into datasets stored in a dedicated SQL pool of Azure Synaps Analytics and transform the data.
Identify a process to ensure that changes to the ingestion and transformation activities can be version controlled and developed independently by multiple data engineers.

NEW QUESTION 47
You need to implement versioned changes to the integration pipelines. The solution must meet the data integration requirements.
In which order should you perform the actions? To answer, move all actions from the list of actions to the answer area and arrange them in the correct order.

Answer:

Explanation:

1 - Create a repository and a main branch
2 - Create a feature branch
3 - Create a pull request
4 - Merge changes
5 - Publish changes
Reference:
https://docs.microsoft.com/en-us/azure/devops/pipelines/repos/pipeline-options-for-git

NEW QUESTION 48
You have an Azure Synapse Analytics SQL pool named Pool1 on a logical Microsoft SQL server named Server1.
You need to implement Transparent Data Encryption (TDE) on Pool1 by using a custom key named key1.
Which five 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:

1 - Assign a managed identity to Server1
2 - Create an Azure key vault and grant the managed identity permissions to the vault
3 - Add key1 to the Azure key vault
4 - Configure key1 as the TDE protector for Server1
5 - Enable TDE on Pool1
Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/managed-instance/scripts/transparent-data-encryption-byok-powershell

NEW QUESTION 49
You have a table named SalesFact in an enterprise data warehouse in Azure Synapse Analytics. 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
At the beginning of each month, you need to remove data from 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.
Reference:
https://docs.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-tables-partition

NEW QUESTION 50
You build an Azure Data Factory pipeline to move data from an Azure Data Lake Storage Gen2 container to a database in an Azure Synapse Analytics dedicated SQL pool.
Data in the container is stored in the following folder structure.
/in/{YYYY}/{MM}/{DD}/{HH}/{mm}
The earliest folder is /in/2021/01/01/00/00. The latest folder is /in/2021/01/15/01/45.
You need to configure a pipeline trigger to meet the following requirements:
Existing data must be loaded.
Data must be loaded every 30 minutes.
Late-arriving data of up to two minutes must he included in the load for the time at which the data should have arrived.
How should you configure the pipeline trigger? 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/data-factory/how-to-create-tumbling-window-trigger

NEW QUESTION 51
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