[Sep-2025] Microsoft DP-203 Dumps – Reduce Your Chance of Failure in DP-203 Exam
To help you achieve your ultimate goal, we suggest the actual Microsoft DP-203 dumps for your Data Engineering on Microsoft Azure exam preparation to use as your guideline.
NEW QUESTION # 171
You are designing an Azure Databricks cluster that runs user-defined local processes. You need to recommend a cluster configuration that meets the following requirements:
* Minimize query latency.
* Maximize the number of users that can run queues on the cluster at the same time
* Reduce overall costs without compromising other requirements Which cluster type should you recommend?
- A. High Concurrency with Autoscaling
- B. Standard with Autoscaling
- C. High Concurrency with Auto Termination
- D. Standard with Auto termination
Answer: A
Explanation:
A High Concurrency cluster is a managed cloud resource. The key benefits of High Concurrency clusters are that they provide fine-grained sharing for maximum resource utilization and minimum query latencies.
Databricks chooses the appropriate number of workers required to run your job. This is referred to as autoscaling. Autoscaling makes it easier to achieve high cluster utilization, because you don't need to provision the cluster to match a workload.
Reference:
https://docs.microsoft.com/en-us/azure/databricks/clusters/configure
NEW QUESTION # 172
You have two Azure Storage accounts named Storage1 and Storage2. Each account holds one container and has the hierarchical namespace enabled. The system has files that contain data stored in the Apache Parquet format.
You need to copy folders and files from Storage1 to Storage2 by using a Data Factory copy activity. The solution must meet the following requirements:
No transformations must be performed.
The original folder structure must be retained.
Minimize time required to perform the copy activity.
How should you configure the copy activity? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Graphical user interface, text, application, chat or text message Description automatically generated
Box 1: Parquet
For Parquet datasets, the type property of the copy activity source must be set to ParquetSource.
Box 2: PreserveHierarchy
PreserveHierarchy (default): Preserves the file hierarchy in the target folder. The relative path of the source file to the source folder is identical to the relative path of the target file to the target folder.
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/format-parquet
https://docs.microsoft.com/en-us/azure/data-factory/connector-azure-data-lake-storage
NEW QUESTION # 173
You have an Azure Synapse Analytics dedicated SQL pool mat contains a table named dbo.Users.
You need to prevent a group of users from reading user email addresses from dbo.Users. What should you use?
- A. Transparent Data Encryption (TDD
- B. column-level security
- C. row-level security
- D. Dynamic data masking
Answer: B
NEW QUESTION # 174
You have an Azure Data Lake Storage Gen2 account named account1 that stores logs as shown in the following table.
You do not expect that the logs will be accessed during the retention periods.
You need to recommend a solution for account1 that meets the following requirements:
Automatically deletes the logs at the end of each retention period
Minimizes storage costs
What should you include in the recommendation? To answer, select the appropriate options in the answer are a.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/storage/blobs/access-tiers-overview
NEW QUESTION # 175
You have an Azure Synapse Analytics dedicated SQL pool.
You need to Create a fact table named Table1 that will store sales data from the last three years. The solution must be optimized for the following query operations:
Show order counts by week.
* Calculate sales totals by region.
* Calculate sales totals by product.
* Find all the orders from a given month.
Which data should you use to partition Table1?
- A. month
- B. week
- C. region
- D. product
Answer: A
Explanation:
Explanation
Table partitions enable you to divide your data into smaller groups of data. In most cases, table partitions are created on a date column.
Benefits to queries
Partitioning can also be used to improve query performance. A query that applies a filter to partitioned data can limit the scan to only the qualifying partitions. This method of filtering can avoid a full table scan and only scan a smaller subset of data. With the introduction of clustered columnstore indexes, the predicate elimination performance benefits are less beneficial, but in some cases there can be a benefit to queries.
For example, if the sales fact table is partitioned into 36 months using the sales date field, then queries that filter on the sale date can skip searching in partitions that don't match the filter.
Note: Benefits to loads
The primary benefit of partitioning in dedicated SQL pool is to improve the efficiency and performance of loading data by use of partition deletion, switching and merging. In most cases data is partitioned on a date column that is closely tied to the order in which the data is loaded into the SQL pool. One of the greatest benefits of using partitions to maintain data is the avoidance of transaction logging. While simply inserting, updating, or deleting data can be the most straightforward approach, with a little thought and effort, using partitioning during your load process can substantially improve performance.
Reference:
https://learn.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-partitio
NEW QUESTION # 176
You are designing an Azure Synapse Analytics dedicated SQL pool.
Groups will have access to sensitive data in the pool as shown in the following table.
You have policies for the sensitive data. The policies vary be region as shown in the following table.
You have a table of patients for each region. The tables contain the following potentially sensitive columns.
You are designing dynamic data masking to maintain compliance.
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/azure-sql/database/dynamic-data-masking-overview
NEW QUESTION # 177
You have an Azure Synapse Analytics serverless SQL pool named Pool1 and an Azure Data Lake Storage Gen2 account named storage1. The AllowedBlobpublicAccess porperty is disabled for storage1.
You need to create an external data source that can be used by Azure Active Directory (Azure AD) users to access storage1 from Pool1.
What should you create first?
- A. a remote service binding
- B. database scoped credentials
- C. an external resource pool
- D. an external library
Answer: B
NEW QUESTION # 178
You need to design a data ingestion and storage solution for the Twitter feeds. The solution must meet the customer sentiment analytics requirements.
What should you include in the solution? To answer, select the appropriate options in the answer area NOTE: Each correct selection b worth one point.
Answer:
Explanation:
Explanation
Graphical user interface, text Description automatically generated
Box 1: Configure Evegent Hubs partitions
Scenario: Maximize the throughput of ingesting Twitter feeds from Event Hubs to Azure Storage without purchasing additional throughput or capacity units.
Event Hubs is designed to help with processing of large volumes of events. Event Hubs throughput is scaled by using partitions and throughput-unit allocations.
Event Hubs traffic is controlled by TUs (standard tier). Auto-inflate enables you to start small with the minimum required TUs you choose. The feature then scales automatically to the maximum limit of TUs you need, depending on the increase in your traffic.
Box 2: An Azure Data Lake Storage Gen2 account
Scenario: Ensure that the data store supports Azure AD-based access control down to the object level.
Azure Data Lake Storage Gen2 implements an access control model that supports both Azure role-based access control (Azure RBAC) and POSIX-like access control lists (ACLs).
Reference:
https://docs.microsoft.com/en-us/azure/event-hubs/event-hubs-features
https://docs.microsoft.com/en-us/azure/storage/blobs/data-lake-storage-access-control
NEW QUESTION # 179
You have an Azure subscription that contains a storage account. The account contains a blob container named blob1 and an Azure Synapse Analytic serve-less SQL pool You need to Query the CSV files stored in blob1. The solution must ensure that all the files in a (older named csv and all its subfolders are queried 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:
NEW QUESTION # 180
You have an Azure Synapse Analytics dedicated SQL pool.
You need to create a table named FactInternetSales that will be a large fact table in a dimensional model.
FactInternetSales will contain 100 million rows and two columns named SalesAmount and OrderQuantity.
Queries executed on FactInternetSales will aggregate the values in SalesAmount and OrderQuantity from the last year for a specific product. The solution must minimize the data size and query execution time.
How should you complete the code? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: (CLUSTERED COLUMNSTORE INDEX
CLUSTERED COLUMNSTORE INDEX
Columnstore indexes are the standard for storing and querying large data warehousing fact tables. This index uses column-based data storage and query processing to achieve gains up to 10 times the query performance in your data warehouse over traditional row-oriented storage. You can also achieve gains up to 10 times the data compression over the uncompressed data size. Beginning with SQL Server 2016 (13.x) SP1, columnstore indexes enable operational analytics: the ability to run performant real-time analytics on a transactional workload.
Note: Clustered columnstore index
A clustered columnstore index is the physical storage for the entire table.
Diagram Description automatically generated
To reduce fragmentation of the column segments and improve performance, the columnstore index might store some data temporarily into a clustered index called a deltastore and a B-tree list of IDs for deleted rows. The deltastore operations are handled behind the scenes. To return the correct query results, the clustered columnstore index combines query results from both the columnstore and the deltastore.
Box 2: HASH([ProductKey])
A hash distributed table distributes rows based on the value in the distribution column. A hash distributed table is designed to achieve high performance for queries on large tables.
Choose a distribution column with data that distributes evenly
Reference: https://docs.microsoft.com/en-us/sql/relational-databases/indexes/columnstore-indexes-overview
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-overview
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-distribu
NEW QUESTION # 181
You have the following table named Employees.
You need to calculate the employee_type value based on the hire_date value.
How should you complete the Transact-SQL statement? To answer, drag the appropriate values to the correct targets. Each value 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:
Reference:
https://docs.microsoft.com/en-us/sql/t-sql/language-elements/case-transact-sql
NEW QUESTION # 182
You need to design the partitions for the product sales transactions. The solution must meet the sales transaction dataset requirements.
What should you include in the solution? 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-overview-what-is
NEW QUESTION # 183
You plan to develop a dataset named Purchases by using Azure databricks Purchases will contain the following columns:
* ProductID
* ItemPrice
* lineTotal
* Quantity
* StorelD
* Minute
* Month
* Hour
* Year
* Day
You need to store the data to support hourly incremental load pipelines that will vary for each StoreID. the solution must minimize storage costs. How should you complete the rode? To answer, select the appropriate options In the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: partitionBy
We should overwrite at the partition level.
Example:
df.write.partitionBy("y","m","d")
mode(SaveMode.Append)
parquet("/data/hive/warehouse/db_name.db/" + tableName)
Box 2: ("StoreID", "Year", "Month", "Day", "Hour", "StoreID")
Box 3: parquet("/Purchases")
Reference:
https://intellipaat.com/community/11744/how-to-partition-and-write-dataframe-in-spark-without-deleting-partitio
NEW QUESTION # 184
Which Azure Data Factory components should you recommend using together to import the daily inventory data from the SQL server to Azure Data Lake Storage? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 185
You are planning the deployment of Azure Data Lake Storage Gen2.
You have the following two reports that will access the data lake:
Report1: Reads three columns from a file that contains 50 columns.
Report2: Queries a single record based on a timestamp.
You need to recommend in which format to store the data in the data lake to support the reports. The solution must minimize read times.
What should you recommend for each report? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Report1: CSV
CSV: The destination writes records as delimited data.
Report2: AVRO
AVRO supports timestamps.
Not Parquet, TSV: Not options for Azure Data Lake Storage Gen2.
Reference:
https://streamsets.com/documentation/datacollector/latest/help/datacollector/UserGuide/Destinations/ADLS- G2-D.html
NEW QUESTION # 186
You are planning the deployment of Azure Data Lake Storage Gen2.
You have the following two reports that will access the data lake:
* Report1: Reads three columns from a file that contains 50 columns.
* Report2: Queries a single record based on a timestamp.
You need to recommend in which format to store the data in the data lake to support the reports. The solution must minimize read times.
What should you recommend for each report? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Report1: CSV
CSV: The destination writes records as delimited data.
Report2: AVRO
AVRO supports timestamps.
Not Parquet, TSV: Not options for Azure Data Lake Storage Gen2.
Reference:
https://streamsets.com/documentation/datacollector/latest/help/datacollector/UserGuide/Destinations/ADLS-G2-
NEW QUESTION # 187
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 # 188
You have an Azure Data Factory pipeline that performs an incremental load of source data to an Azure Data Lake Storage Gen2 account.
Data to be loaded is identified by a column named LastUpdatedDate in the source table.
You plan to execute the pipeline every four hours.
You need to ensure that the pipeline execution meets the following requirements:
* Automatically retries the execution when the pipeline run fails due to concurrency or throttling limits.
* Supports backfilling existing data in the table.
Which type of trigger should you use?
- A. on-demand
- B. tumbling window
- C. event
- D. schedule
Answer: B
Explanation:
Explanation
In case of pipeline failures, tumbling window trigger can retry the execution of the referenced pipeline automatically, using the same input parameters, without the user intervention. This can be specified using the property "retryPolicy" in the trigger definition.
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/how-to-create-tumbling-window-trigger
NEW QUESTION # 189
You have an Azure Storage account that generates 200.000 new files daily. The file names have a format of (YYY)/(MM)/(DD)/|HH])/(CustornerID).csv.
You need to design an Azure Data Factory solution that will toad new data from the storage account to an Azure Data lake once hourly. The solution must minimize load times and costs.
How should you configure the solution? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
See the answer below in explanation.
Explanation
Answer as below
NEW QUESTION # 190
You are designing a real-time dashboard solution that will visualize streaming data from remote sensors that connect to the internet. The streaming data must be aggregated to show the average value of each 10-second interval. The data will be discarded after being displayed in the dashboard.
The solution will use Azure Stream Analytics and must meet the following requirements:
Minimize latency from an Azure Event hub to the dashboard.
Minimize the required storage.
Minimize development effort.
What should you include in the solution? 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/stream-analytics/stream-analytics-power-bi-dashboard
NEW QUESTION # 191
You plan to create a table in an Azure Synapse Analytics dedicated SQL pool.
Data in the table will be retained for five years. Once a year, data that is older than five years will be deleted.
You need to ensure that the data is distributed evenly across partitions. The solution must minimize the amount of time required to delete old data.
How should you complete the Transact-SQL statement? To answer, drag the appropriate values to the correct targets. Each value 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: HASH
Box 2: OrderDateKey
In most cases, table partitions are created on a date column.
A way to eliminate rollbacks is to use Metadata Only operations like partition switching for data management.
For example, rather than execute a DELETE statement to delete all rows in a table where the order_date was in October of 2001, you could partition your data early. Then you can switch out the partition with data for an empty partition from another table.
Reference:
https://docs.microsoft.com/en-us/sql/t-sql/statements/create-table-azure-sql-data-warehouse
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql/best-practices-dedicated-sql-pool
NEW QUESTION # 192
You have an Azure Synapse Analytics dedicated SQL pool that hosts a database named DB1 You need to ensure that D81 meets the following security requirements:
* When credit card numbers show in applications, only the last four digits must be visible.
* Tax numbers must be visible only to specific users.
What 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:
NEW QUESTION # 193
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