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Reliable Test DP-203 Test - DP-203 Free Brain Dumps

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Microsoft DP-203: Data Engineering on Microsoft Azure is a certification exam that validates the skills and knowledge of professionals in data engineering on Azure. DP-203 exam covers various topics such as data storage, data processing, data transformation, and data integration using Azure services. DP-203 exam is suitable for data engineers who work with Azure services such as Azure Data Factory, Azure Databricks, Azure Stream Analytics, and Azure Synapse Analytics. Data Engineering on Microsoft Azure certification is globally recognized and is highly valued by employers, making it an excellent choice for professionals who want to advance their careers in data engineering.

What is Microsoft DP-203 Certification

Microsoft DP-203 (Designing Data Platform Solutions on Microsoft Azure) certification is a great way to validate your hands-on experience with cloud platforms, data architecture, and database technologies. This exam is designed to determine the competency of candidates to design distributed data solutions for enterprise applications based on Azure technologies. Before you begin studying for this exam, there are a few terms that you should familiarize yourself with. First and foremost, you should understand the difference between Microsoft SQL Server, Microsoft SQL Database, and Microsoft Azure SQL Database. Exam objectives are associated with these products; therefore, it is important to know when you will be tested on each one. Microsoft DP-203 Dumps tests a candidate's knowledge of Microsoft technologies used for building a data platform and cloud environment. Microsoft DP-203 is a certification of data engineers. The certification exam is designed to test the skills of designing, deploying, and managing Microsoft HDInsight and Microsoft Azure SQL Data Warehouse clusters for business intelligence and analytics solutions.

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Microsoft DP-203 (Data Engineering on Microsoft Azure) Certification Exam is a professional level certification exam offered by Microsoft for data engineers who design and implement data solutions on Azure. Data Engineering on Microsoft Azure certification is intended for professionals who have a working knowledge of Azure data services, including Azure SQL Database, Azure Data Lake Storage, Azure Synapse Analytics, and Azure Stream Analytics.

Microsoft Data Engineering on Microsoft Azure Sample Questions (Q24-Q29):

NEW QUESTION # 24
You have data stored in thousands of CSV files in Azure Data Lake Storage Gen2. Each file has a header row followed by a properly formatted carriage return (/r) and line feed (/n).
You are implementing a pattern that batch loads the files daily into an enterprise data warehouse in Azure Synapse Analytics by using PolyBase.
You need to skip the header row when you import the files into the data warehouse. Before building the loading pattern, you need to prepare the required database objects in Azure Synapse Analytics.
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.
NOTE: Each correct selection is worth one point

Answer:

Explanation:

Explanation
A picture containing timeline Description automatically generated

Step 1: Create an external data source that uses the abfs location
Create External Data Source to reference Azure Data Lake Store Gen 1 or 2 Step 2: Create an external file format and set the First_Row option.
Create External File Format.
Step 3: Use CREATE EXTERNAL TABLE AS SELECT (CETAS) and configure the reject options to specify reject values or percentages To use PolyBase, you must create external tables to reference your external data.
Use reject options.
Note: REJECT options don't apply at the time this CREATE EXTERNAL TABLE AS SELECT statement is run. Instead, they're specified here so that the database can use them at a later time when it imports data from the external table. Later, when the CREATE TABLE AS SELECT statement selects data from the external table, the database will use the reject options to determine the number or percentage of rows that can fail to import before it stops the import.
Reference:
https://docs.microsoft.com/en-us/sql/relational-databases/polybase/polybase-t-sql-objects
https://docs.microsoft.com/en-us/sql/t-sql/statements/create-external-table-as-select-transact-sql

NEW QUESTION # 25
What should you do to improve high availability of the real-time data processing solution?

A. Deploy a High Concurrency Databricks cluster.
B. Deploy identical Azure Stream Analytics jobs to paired regions in Azure.
C. Set Data Lake Storage to use geo-redundant storage (GRS).
D. Deploy an Azure Stream Analytics job and use an Azure Automation runbook to check the status of the job and to start the job if it stops.

Answer: B

Explanation:
Explanation
Guarantee Stream Analytics job reliability during service updates
Part of being a fully managed service is the capability to introduce new service functionality and improvements at a rapid pace. As a result, Stream Analytics can have a service update deploy on a weekly (or more frequent) basis. No matter how much testing is done there is still a risk that an existing, running job may break due to the introduction of a bug. If you are running mission critical jobs, these risks need to be avoided.
You can reduce this risk by following Azure's paired region model.
Scenario: The application development team will create an Azure event hub to receive real-time sales data, including store number, date, time, product ID, customer loyalty number, price, and discount amount, from the point of sale (POS) system and output the data to data storage in Azure Reference:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-job-reliability

NEW QUESTION # 26
You are deploying a lake database by using an Azure Synapse database template.
You need to add additional tables to the database. The solution must use the same grouping method as the template tables.
'Which grouping method should you use?

A. facts and dimensions
B. partition style
C. business area
D. size

Answer: C

Explanation:
Business area: This is how the Azure Synapse database templates group tables by default. Each template consists of one or more enterprise templates that contain tables grouped by business areas. For example, the Retail template has business areas such as Customer, Product, Sales, and Store123. Using the same grouping method as the template tables can help you maintain consistency and compatibility with the industry-specific data model.
https://techcommunity.microsoft.com/t5/azure-synapse-analytics-blog/database-templates-in-azure-synapse-analytics/ba-p/2929112

NEW QUESTION # 27
You are designing a partition strategy for a fact table in an Azure Synapse Analytics dedicated SQL pool. The table has the following specifications:
* Contain sales data for 20,000 products.
* Use hash distribution on a column named ProduclID,
* Contain 2.4 billion records for the years 20l9 and 2020.
Which number of partition ranges provides optimal compression and performance of the clustered columnstore index?

A. 0
B. 2,400
C. 1
D. 2

Answer: C

NEW QUESTION # 28
You have a SQL pool in Azure Synapse.
You plan to load data from Azure Blob storage to a staging table. Approximately 1 million rows of data will be loaded daily. The table will be truncated before each daily load.
You need to create the staging table. The solution must minimize how long it takes to load the data to the staging table.
How should you configure the table? 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/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-partition
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-distribute

NEW QUESTION # 29
......

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