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Data Warehousing with Microsoft Azure Synapse Analytics Week 6 | Course Practice Exam Quiz Answers 

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Data Warehousing with Microsoft Azure Synapse Analytics Week 6 | Course Practice Exam Quiz Answers

 

Course Practice Exam Quiz Answers

Question 1)
Select from the following options to complete the missing text in the statement.
A data warehouse that is built on a Massively Parallel Processing (MPP) system are built for processing and analyzing large datasets. As such they perform well with ____________ that can be distributed across compute nodes and storage.

  • Multiple small batch sizes
  • Fewer and larger batch sizes

Question 2)
Which transformation is used to load data into a destination data store or compute resource?

  • Sink
  • Source
  • Window

Question 3)
When working with Data Lake Storage Gen2 many small files can negatively affect performance. The recommended file size for Data Lake Storage Gen2 is between which of the following sizes?

  • 10GB to 100GB
  • 1GB to 10GB
  • 256MB to 1GB
  • 256MB to 100GB

Question 4)
What distribution option would you use for a product dimension table that will contain 1,000 records in Synapse Analytics?

  • DISTRIBUTION = ROUND_ROBIN.
  • DISTRIBUTION = REPLICATE.
  • DISTRIBUTION = HASH([ProductId]).

Question 5)
Which of the following are true in respect of fact tables? Select all options that apply.

  • A fact table contains numeric measure columns.
  • A fact table contains dimension key columns that relate to dimension tables.
  • Fact tables store observations or events.
  • A fact table describes business entities.

Question 6)
A Star schema is a modelling approach widely adopted by relational data warehouses. It requires modelers to classify their model tables as either dimension or fact. Which of the following are features of dimension tables? Select all options that apply.

  • A dimension table contains a key column (or columns)
  • A dimension table describes business entities
  • A dimension stores numeric measure columns

Question 7)
Resource classes are pre-determined resource limits in Synapse SQL pool that govern compute resources and concurrency for query execution. Resource classes can help you configure resources for your queries by setting limits on the number of queries that run concurrently and, on the compute-resources assigned to each query.

Which of the following statements are correct? Select all options that apply.

  • Larger resource classes increase the maximum memory per query, but reduce concurrency.
  • Smaller resource classes reduce the maximum memory per query, but increase concurrency.
  • Smaller resource classes reduce the concurrency, but increase maximum memory per query.
  • Larger resource classes increase concurrency, but reduce the maximum memory per query,

Question 8)
SQL Pools have the concept of concurrency slots, which manage the allocation of memory to connected users. Which of the following should you consider to optimize the load execution operations? Select all options that apply.

  • Reducing or minimizing the number of simultaneous load jobs that are running.
  • Assigning lower resource classes that reduce the number of active running tasks.
  • Assigning higher resource classes that reduce the number of active running tasks.
  • Increase the number of simultaneous load jobs that are running.

Question 9)
Which of the following hubs would you use to create a workload classifier in Azure Synapse Studio?

  • Develop
  • Manage
  • Integrate
  • Data

Question 10)
When data is loaded into Synapse Analytics dedicated SQL pools, the datasets are broken up and dispersed among the compute nodes for processing, and then written to a decoupled and scalable storage layer. What term is used to describe this action?

  • Separating
  • Shredding
  • Sharing
  • Sharding

Question 11)
Select from the following options to complete the missing word in the sentence.

Dedicated SQL Pools create a _______________________ index when no index options are specified on a table.

  • Non-clustered
  • Clustered columnstore
  • Clustered

Question 12)
Materialized views are prewritten queries with joins and filters whose definition is saved and the results persisted to pools. Which of the following pools are the results for Materialized views persisted to?

  • Dedicated SQL Pool
  • Serverless SQL Pool

Question 13)
In Azure Synapse SQL, you should enable result-set caching when you expect results from queries to return the same values. This option stores a copy of the result set on the control node so that queries do not need to pull data from the storage subsystem or compute nodes.

Materialized views are prewritten queries with joins and filters whose definition is saved and the results persisted to pools. Which of the following pools are the results for Materialized views persisted to?

  • 24 Hours
  • 36 Hours
  • 12 Hours
  • 48 Hours

Question 14)
The Azure Synapse Studio experience provides an integrated notebook experience. Within this notebook experience, you can attach a SQL or Apache Spark pool, and develop and execute transformation pipelines using which of the following?

  • Scala
  • SparkSQL
  • JSON
  • Python

Question 15)
In Azure Synapse Analytics the authentication process between two systems can be seamless. However, there are some prerequisites. Which of the following role memberships are required to successfully authenticate? Select all options that apply.

  • The account used needs to be a member of db_exporter role in the database or SQL pool from which you transfer data to or from.
  • The account used needs to be a member of Storage Blob Data Contributor role in the database or SQL pool from which you transfer data to or from.
  • The account used needs to be a member of the Storage Blob Data Contributor role on the default storage account.
  • The account used needs to be a member of the db_exporter role on the default storage account.

Question 16)
When is it unnecessary to use import statements for transferring data between a dedicated SQL and Apache Spark pool?

  • Use the PySpark connector
  • When using the integrated notebook experience from Azure Synapse Studio
  • Use token-based authentication.

Question 17)
SQL pool in Azure Synapse supports standard and materialized views. Which of the following are features of Materialized views? Select all options that apply.

  • View content is generated each time the view is used.
  • View content is pre-processed and stored in SQL pool during view creation. The view is updated as data is added to the underlying tables.
  • Speed to retrieve view data from complex queries is Slow.
  • Speed to retrieve view data from complex queries is Fast.

Question 18)
Which of the following statements is a benefit of materialized views?

  • Reducing the execution time for complex queries with JOINs and aggregate functions.
  • Increased high availability
  • Increased resiliency benefits

Question 19)
Conditional access is a feature that enables you to define the conditions under which a user can connect to your Azure subscription and access services. Conditional access policies use signals as a basis to determine if conditional access should first be applied. Common signals include? Select all options that apply.

  • Multi Factor Authentication
  • Microsoft Cloud App Security (MCAS)
  • IP address information
  • Device platforms or type
  • User or group membership names

Question 20)
You want to configure a private endpoint. You open up Azure Synapse Studio, go to the manage hub, and see that the private endpoint is greyed out. Why is the option not available?

  • A conditional access policy has to be defined first.
  • A managed virtual network has not been created.
  • Azure Synapse Studio does not support the creation of private endpoints.

 

 

Question 21)
Which transformation in the Mapping Data Flow is used to routes data rows to different streams based on matching conditions?

  • Lookup
  • GetMetadata activity
  • Conditional Split

Question 22)
True or False?
When data is stored in Data Lake Storage Gen2, the file size, number of files, and folder structure can have an impact on performance.

  • False
  • True

Question 23)
What is the difference between a star schema and a snowflake schema?

  • A star schema has one fact table while a snowflake schema has multiple fact tables.
  • A star schema uses surrogate keys while a snowflake schema uses business keys.
  • All dimensions in a star schema join directly to the fact table (denormalized) while some dimension tables in a snowflake schema are normalized.
  • All dimensions in a star schema are normalized while all dimensions in a snowflake schema join directly to the fact table (denormalized).

Question 24)
Which of the following statements are true in respect of a Star schema? Select all options that apply.

  • Star schemas have a high level of Data redundancy.
  • Star schema dimension tables are a denormalized data structure.
  • A Star schema contains a fact table surrounded by dimension tables.
  • In a Star schema Cube processing might be slow because of the complex join.
  • A Star schema will have a fact table surrounded by dimension tables which are in turn surrounded by dimension tables.

Question 25)
What distribution option would be best for a sales fact table that will contain billions of records?

  • DISTRIBUTION = HEAP
  • DISTRIBUTION = REPLICATE
  • DISTRIBUTION = HASH([SalesOrderNumber])

Question 26)
In Azure Synapse Analytics configured with a dedicated SQL pool, classifiers assign incoming requests to a workload group. Classifiers are evaluated with every request submitted. If a request is not matched to a classifier, it is assigned to the default workload group. The default workload group in is the ___________ resource class.

  • largerc
  • xlargerc
  • mediumrc
  • smallrc

Question 27)
Which T-SQL Statement loads data directly from Azure Storage?

  • COPY
  • LOAD DATA
  • INSERT FROM FILE

Question 28)
Which of the following indexing options are available in Dedicated SQL Pools? Select all options that apply.

  • Clustered index
  • Clustered columnstore index
  • Non-clustered index
  • Table Index

Question 29)
Which of the following index types can be defined on a table or view with a clustered index or on a heap?

  • Non-clustered
  • Clustered
  • Clustered columnstore

Question 30)
You can use Materialized Views to improve the performance of either complex or slow queries. As the data in the underlying base tables change, the data in the materialized view will automatically update without user interaction. However, there are certain restrictions you must comply with when defining a materialized view. Which of the following are valid when defining materialized views? Select all options that apply.

  • The round_robin table distribution is supported in the definition.
  • The Replicated tables distribution is supported in the definition.
  • Clustered Columnstore index is supported by materialized views.
  • Clustered index is supported by materialized views.
  • The hash table distribution is supported in the definition.

Question 31)
The Azure Synapse Apache Spark to Synapse SQL connector is designed to efficiently transfer data between which of the following?

  • Dedicated Apache Spark pools and Serverless SQL pools in Azure Synapse.
  • Serverless Apache Spark pools and Dedicated SQL pools in Azure Synapse.
  • Serverless Apache Spark pools and Serverless SQL pools in Azure Synapse.

Question 32)
Azure Synapse Analytics enables you to connect to its various components through endpoints. You can set up managed private endpoints to access these components in a secure manner known as private links. Which of the following statements are true in respect of Private Endpoints?

Select all options that apply.

  • You can manage the private endpoints in the Azure Synapse Studio manage hub.
  • You must have an Azure Synapse workspace with a Managed workspace Virtual Network.
  • When you use a private link, traffic between your Virtual Network and workspace traverses over the public Internet network.
  • When you use a private link, traffic between your Virtual Network and workspace traverses entirely over the Microsoft backbone network.

Question 33)
Transparent data encryption (TDE) is an encryption mechanism to help you protect Azure Synapse Analytics. The way TDE will do so, is by encrypting data at rest.

If you export a TDE-protected database, the exported content will be in a specific state. Which of the following represents the state of the exported content?

  • Will be in an unencrypted state
  • Remains in its original encrypted state
  • Will be encrypted using a new TDE Key

Question 34)
Processing data that arrives in real-time/near real-time is also referred to as streaming data processing. Azure offers purpose-built stream ingestion services such as Azure IoT Hub and Azure Event Hubs. To collect messages from these or similar services, and process them you can use which of the following features? Select all options that apply.

  • Azure Databricks
  • Azure IoT Central
  • Azure Stream Analytics
  • Azure Functions

Question 35)
Dedicated SQL pool workload management in Azure Synapse consists of three high-level concepts which give you more control over how your workload utilizes system resources.

Which of the following are valid concepts? Select all options that apply.

  • Workload Classification
  • Workload Isolation
  • Workload partitioning
  • Workload Importance

Question 36)
Which of the following table distributions available in Synapse Analytics SQL Pools creates a hash function to deterministically assign each row to a distribution and has a column designated as the distribution column?

  • Replicated tables
  • Hash distribution
  • Round robin distribution

Question 37)
To write data to a dedicated SQL Pool, you use the Write API. The Write API creates a table in the dedicated SQL pool. Which of the following is used to load the data into the table that was created?

  • JSON
  • Polybase
  • ORC
  • Parquet

Question 38)
What features are provided when using a managed workspace virtual network? Select all options that apply.

  • Management of the virtual network is offloaded to Azure Synapse.
  • You will need to create a subnet for your Spark clusters based on peak load.
  • You don’t have to configure inbound NSG rules on your own Virtual Networks to allow Azure Synapse management traffic to enter your Virtual Network.
  • Your workspace is network isolated from other workspaces.