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Microsoft DP-203 Exam Questions

Microsoft DP-203 Exam Questions Answers

Data Engineering on Microsoft Azure

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Microsoft DP-203 Sample Questions – Free Practice Test & Real Exam Prep

Question #1

You are designing an Azure Data Lake Storage solution that will transform raw JSON filesfor use in an analytical workload.You need to recommend a format for the transformed files. The solution must meet thefollowing requirements:Contain information about the data types of each column in the files.Support querying a subset of columns in the files.Support read-heavy analytical workloads.Minimize the file size.What should you recommend?

  • A. JSON
  • B. CSV
  • C. Apache Avro
  • D. Apache Parquet
Answer: D
Explanation:
Parquet, an open-source file format for Hadoop, stores nested data structures in a flat
columnar format.
Compared to a traditional approach where data is stored in a row-oriented approach, Parquet file format is more efficient in terms of storage and performance.
It is especially good for queries that read particular columns from a “wide” (with many
columns) table since only needed columns are read, and IO is minimized.
Reference: https://www.clairvoyant.ai/blog/big-data-file-formats
Question #2

You have an Azure subscription that contains an Azure Synapse Analytics workspacenamed ws1 and an Azure Cosmos D6 database account named Cosmos1 Costmos1contains a container named container 1 and ws1 contains a serverless1 SQL pool. you need to ensure that you can Query the data in container by using the serverless1 SQLpool.Which three actions should you perform? Each correct answer presents part of the solutionNOTE: Each correct selection is worth one point.

  • A. Enable Azure Synapse Link for Cosmos1
  • B. Disable the analytical store for container1.
  • C. In ws1. create a linked service that references Cosmos1
  • D. Enable the analytical store for container1
  • E. Disable indexing for container1
Answer: A,C,D
Question #3

You are designing a folder structure for the files m an Azure Data Lake Storage Gen2account. The account has one container that contains three years of data.You need to recommend a folder structure that meets the following requirements:• Supports partition elimination for queries by Azure Synapse Analytics serverless SQLpooh • Supports fast data retrieval for data from the current month• Simplifies data security management by departmentWhich folder structure should you recommend?

  • A. \YYY\MM\DD\Department\DataSource\DataFile_YYYMMMDD.parquet
  • B. \Depdftment\DataSource\YYY\MM\DataFile_YYYYMMDD.parquet
  • C. \DD\MM\YYYY\Department\DataSource\DataFile_DDMMYY.parquet
  • D. \DataSource\Department\YYYYMM\DataFile_YYYYMMDD.parquet
Answer: B
Explanation:
Department top level in the hierarchy to simplify security management.
Month (MM) at the leaf/bottom level to support fast data retrieval for data from the current
month.
Question #4

You have an Azure Synapse Analytics dedicated SQL pod. You need to create a pipeline that will execute a stored procedure in the dedicated SQLpool and use the returned result set as the input (or a downstream activity. The solutionmust minimize development effort.Which Type of activity should you use in the pipeline?

  • A. Notebook
  • B. U-SQL
  • C. Script
  • D. Stored Procedure
Answer: D
Question #5

You have an Azure Synapse Analytics dedicated SQL pool that contains a table namedTable1. Table1 contains the following:One billion rowsA clustered columnstore index A hash-distributed column named Product KeyA column named Sales Date that is of the date data type and cannot be nullThirty million rows will be added to Table1 each month.You need to partition Table1 based on the Sales Date column. The solution must optimizequery performance and data loading.How often should you create a partition?

  • A. once per month
  • B. once per year
  • C. once per day
  • D. once per week
Answer: B
Explanation: Need a minimum 1 million rows per distribution. Each table is 60 distributions. 30 millions
rows is added each month. Need 2 months to get a minimum of 1 million rows per
distribution in a new partition.
Note: When creating partitions on clustered columnstore tables, it is important to consider
how many rows belong to each partition. For optimal compression and performance of
clustered columnstore tables, a minimum of 1 million rows per distribution and partition is
needed. Before partitions are created, dedicated SQL pool already divides each table into
60 distributions.
Any partitioning added to a table is in addition to the distributions created behind the
scenes. Using this example, if the sales fact table contained 36 monthly partitions, and
given that a dedicated SQL pool has 60 distributions, then the sales fact table should
contain 60 million rows per month, or 2.1 billion rows when all months are populated. If a
table contains fewer than the recommended minimum number of rows per partition,
consider using fewer partitions in order to increase the number of rows per partition.
Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-datawarehouse-
tables-partition
Question #6

You have an Azure Databricks workspace named workspace! in the Standard pricing tier.Workspace1 contains an all-purpose cluster named cluster). You need to reduce the time ittakes for cluster 1 to start and scale up. The solution must minimize costs. What shouldyou do first?

  • A. Upgrade workspace! to the Premium pricing tier.
  • B. Create a cluster policy in workspace1.
  • C. Create a pool in workspace1.
  • D. Configure a global init script for workspace1.
Answer: C
Explanation:
You can use Databricks Pools to Speed up your Data Pipelines and Scale Clusters
Quickly.
Databricks Pools, a managed cache of virtual machine instances that enables clusters to
start and scale 4 times faster.
Reference:
https://databricks.com/blog/2019/11/11/databricks-pools-speed-up-data-pipelines.html
Question #7

You have an Azure subscription that contains an Azure Data Lake Storage account named myaccount1. The myaccount1 account contains two containers named container1 and contained. The subscription is linked to an Azure Active Directory (Azure AD) tenant that contains a security group named Group1. You need to grant Group1 read access to contamer1. The solution must use the principle of least privilege. Which role should you assign to Group1? 

  • A. Storage Blob Data Reader for container1 
  • B. Storage Table Data Reader for container1 
  • C. Storage Blob Data Reader for myaccount1 
  • D. Storage Table Data Reader for myaccount1 
Answer: A
Question #8

You are designing database for an Azure Synapse Analytics dedicated SQL pool to support workloads for detecting ecommerce transaction fraud. Data will be combined from multiple ecommerce sites and can include sensitive financial information such as credit card numbers. You need to recommend a solution that meets the following requirements: Users must be able to identify potentially fraudulent transactions. Users must be able to use credit cards as a potential feature in models. Users must NOT be able to access the actual credit card numbers. What should you include in the recommendation? 

  • A. Transparent Data Encryption (TDE) 
  • B. row-level security (RLS) 
  • C. column-level encryption 
  • D. Azure Active Directory (Azure AD) pass-through authentication 
Answer: C
Explanation: Use Always Encrypted to secure the required columns. You can configure Always Encrypted for individual database columns containing your sensitive data. Always Encrypted is a feature designed to protect sensitive data, such as credit card numbers or national identification numbers (for example, U.S. social security numbers), stored in Azure SQL Database or SQL Server databases. Reference: https://docs.microsoft.com/en-us/sql/relational-databases/security/encryption/alwaysencrypted-datab...
Question #9

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. region 
  • B. product 
  • C. week
  •  D. month 
Answer: C
Question #10

You plan to create a dimension table in Azure Synapse Analytics that will be less than 1 GB. You need to create the table to meet the following requirements: • Provide the fastest Query time. • Minimize data movement during queries. Which type of table should you use? 

  • A. hash distributed 
  • B. heap
  •  C. replicated 
  • D. round-robin
 Answer: C
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