The latest Microsoft DP-900 Azure Data Fundamentals certification actual real practice exam question and answer (Q&A) dumps are available free, which are helpful for you to pass the Microsoft DP-900 Azure Data Fundamentals exam and earn Microsoft DP-900 Azure Data Fundamentals certification.
Table of Contents
- DP-900 Question 11
- Exam Question
- Correct Answer
- Explanation
- Reference
- DP-900 Question 12
- Exam Question
- Correct Answer
- Explanation
- Reference
- DP-900 Question 13
- Exam Question
- Correct Answer
- Explanation
- Reference
- DP-900 Question 14
- Exam Question
- Correct Answer
- Explanation
- DP-900 Question 15
- Exam Question
- Correct Answer
- Explanation
- Reference
- DP-900 Question 16
- Exam Question
- Correct Answer
- Explanation
- DP-900 Question 17
- Exam Question
- Correct Answer
- Explanation
- Reference
- DP-900 Question 18
- Exam Question
- Correct Answer
- Explanation
- Reference
- DP-900 Question 19
- Exam Question
- Correct Answer
- Explanation
- Reference
- DP-900 Question 20
- Exam Question
- Correct Answer
- Explanation
- Reference
DP-900 Question 11
Exam Question
What should you use to build a Microsoft Power BI paginated report?
A. Charticulator
B. Power BI Desktop
C. the Power BI service
D. Power BI Report Builder
Correct Answer
D. Power BI Report Builder
Explanation
Power BI Report Builder is the standalone tool for authoring paginated reports for the Power BI service.
Reference
Microsoft Learn > Power Platform > Power BI > What are paginated reports in Power BI?
DP-900 Question 12
Exam Question
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
Statement 1: Azure Synapse Analytics scales storage and compute independently.
Statement 2: Azure Synapse Analytics can be paused to reduce compute costs.
Statement 3: An Azure Synapse Analytics data warehouse has a fixed storage capacity.
Correct Answer
Statement 1: Azure Synapse Analytics scales storage and compute independently: Yes
Statement 2: Azure Synapse Analytics can be paused to reduce compute costs: Yes
Statement 3: An Azure Synapse Analytics data warehouse has a fixed storage capacity: No
Explanation
Statement 1: Azure Synapse Analytics scales storage and compute independently: Yes
Compute is separate from storage, which enables you to scale compute independently of the data in your system.
Statement 2: Azure Synapse Analytics can be paused to reduce compute costs: Yes
You can use the Azure portal to pause and resume the dedicated SQL pool compute resources.
Pausing the data warehouse pauses compute. If your data warehouse was paused for the entire hour, you will not be charged compute during that hour.
Statement 3: An Azure Synapse Analytics data warehouse has a fixed storage capacity: No
Storage is sold in 1 TB allocations. If you grow beyond 1 TB of storage, your storage account will automatically grow to 2 TBs.
Reference
Azure Pricing > Azure Synapse Analytics pricing
DP-900 Question 13
Exam Question
Match the Azure services to the appropriate requirements. Each service may be used once, more than once, or not at all.
Services:
- Azure Data Factory
- Azure Data Lake Storage
- Azure SQL Database
- Azure Synapse Analytics
Requirements:
- Output data to Parquet format
- Store data that is in Parquet format
- Persist a tabular representation of data that is stored in Parquet format
Correct Answer
Azure Data Factory: Output data to Parquet format
Azure Data Lake Storage: Store data that is in Parquet format
Azure Synapse Analytics: Persist a tabular representation of data that is stored in Parquet format
Explanation
Azure Data Factory: Output data to Parquet format
Azure Data Lake Storage: Store data that is in Parquet format
Azure Data Lake Storage (ADLA) now natively supports Parquet files. ADLA adds a public preview of the native extractor and outputter for the popular Parquet file format
Azure Synapse Analytics: Persist a tabular representation of data that is stored in Parquet format
Use Azure Synapse Analytics Workspaces.
Reference
Microsoft Learn > Azure > Data Factory > Supported file formats and compression codecs by copy activity in Azure Data Factory and Azure Synapse pipelines
DP-900 Question 14
Exam Question
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
Statement 1: A pipeline is a representation of a data structure within Azure Data Factory.
Statement 2: Azure Data Factory pipelines can execute other pipelines.
Statement 3: A processing step within an Azure Data Factory pipeline is an activity.
Correct Answer
Statement 1: A pipeline is a representation of a data structure within Azure Data Factory: No
Statement 2: Azure Data Factory pipelines can execute other pipelines: Yes
Statement 3: A processing step within an Azure Data Factory pipeline is an activity: Yes
Explanation
Statement 1: A pipeline is a representation of a data structure within Azure Data Factory: No
A pipeline is a logical grouping of activities that together perform a task.
Statement 2: Azure Data Factory pipelines can execute other pipelines: Yes
You can construct pipeline hierarchies with data factory.
Statement 3: A processing step within an Azure Data Factory pipeline is an activity: Yes
A pipeline is a logical grouping of activities that together perform a task.
DP-900 Question 15
Exam Question
To complete the sentence, select the appropriate option in the answer area.
In a data warehousing workload, data __________.
Answer Area:
A. from a single source is distributed to multiple locations
B. from multiple sources is combined in a single location
C. is added to a queue for multiple systems to process
D. is used to train machine learning models
Correct Answer
B. from multiple sources is combined in a single location
Explanation
Note: The data warehouse workload encompasses:
- The entire process of loading data into the warehouse
- Performing data warehouse analysis and reporting
- Managing data in the data warehouse
- Exporting data from the data warehouse
Reference
Microsoft Learn > Azure > Synapse Analytics > What is workload management?
DP-900 Question 16
Exam Question
Match the types of workloads to the appropriate scenarios. Each workload type may be used once, more than once, or not at all.
Workload Types:
- Batch
- Streaming
Scenarios:
- Analyzing historical data containing web traffic collected during the previous year.
- Classifying images that were uploaded last month.
- Tracking in real time how many people are currently using a website.
Correct Answer
Batch: Analyzing historical data containing web traffic collected during the previous year.
Batch: Classifying images that were uploaded last month.
Streaming: Tracking in real time how many people are currently using a website.
Explanation
Batch: Analyzing historical data containing web traffic collected during the previous year.
The batch processing model requires a set of data that is collected over time while the stream processing model requires data to be fed into an analytics tool, often in micro-batches, and in real-time.
The batch Processing model handles a large batch of data while the Stream processing model handles individual records or micro-batches of few records.
In Batch Processing, it processes over all or most of the data but in Stream Processing, it processes over data on a rolling window or most recent record.
Batch: Classifying images that were uploaded last month.
Streaming: Tracking in real time how many people are currently using a website.
DP-900 Question 17
Exam Question
Match the Azure services to the appropriate locations in the architecture. Each service may be used once, more than once, or not at all.
Correct Answer
Explanation
Box Ingest: Azure Data Factory
You can build a data ingestion pipeline with Azure Data Factory (ADF).
Box Preprocess & model: Azure Synapse Analytics
Use Azure Synapse Analytics to preprocess data and deploy machine learning models.
Reference
- Microsoft Learn > Azure > Machine Learning > Data ingestion with Azure Data Factory
- Microsoft Learn > Azure > Architecture > Team Data Science Process > Build and deploy a model using Azure Synapse Analytics
DP-900 Question 18
Exam Question
What is the primary purpose of a data warehouse?
A. to provide answers to complex queries that rely on data from multiple sources
B. to provide transformation services between source and target data stores
C. to provide read-only storage of relational and non-relational historical data
D. to provide storage for transactional line-of-business (LOB) applications
Correct Answer
C. to provide read-only storage of relational and non-relational historical data
Explanation
Consider using a data warehouse when you need to keep historical data separate from the source transaction systems for performance reasons. Data warehouses make it easy to access historical data from multiple locations, by providing a centralized location using common formats, keys, and data models.
Query both relational and nonrelational data.
Incorrect Answers:
D: Data warehouses don’t need to follow the same terse data structure you may be using in your OLTP databases.
Reference
Microsoft Learn > Azure > Architecture > Data Architecture Guide > Data warehousing in Microsoft Azure
DP-900 Question 19
Exam Question
What are three characteristics of an Online Transaction Processing (OLTP) workload?
A. denormalized data
B. heavy writes and moderate reads
C. light writes and heavy reads
D. schema defined in a database
E. schema defined when reading unstructured data from a database
F. normalized data
Correct Answer
B. heavy writes and moderate reads
D. schema defined in a database
F. normalized data
Explanation
B: Transactional data tends to be heavy writes, moderate reads.
D: Typical traits of transactional data include: schema on write, strongly enforced. The schema is defined in a database.
F: Transactional data tends to be highly normalized.
Reference
Microsoft Learn > Azure > Architecture > Data Architecture Guide > Online transaction processing (OLTP)
DP-900 Question 20
Exam Question
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
Statement 1: You can copy a dashboard between Microsoft Power BI workspaces.
Statement 2: A Microsoft Power BI dashboard can only display visualizations from a single dataset.
Statement 3: A Microsoft Power BI dashboard can display visualizations from a Microsoft Excel workbook.
Correct Answer
Statement 1: You can copy a dashboard between Microsoft Power BI workspaces: No
Statement 2: A Microsoft Power BI dashboard can only display visualizations from a single dataset: No
Statement 3: A Microsoft Power BI dashboard can display visualizations from a Microsoft Excel workbook: Yes
Explanation
Statement 1: You can copy a dashboard between Microsoft Power BI workspaces: No
You can duplicate a dashboard. The duplicate ends up in the same Power BI workspace.
There is no current functionality that allows you to move reports from one workspace to another.
Statement 2: A Microsoft Power BI dashboard can only display visualizations from a single dataset: No
Statement 3: A Microsoft Power BI dashboard can display visualizations from a Microsoft Excel workbook: Yes
Reference
- Microsoft Learn > Power Platform > Power BI > Introduction to datasets across workspaces
- Microsoft Learn > Power Platform > Power BI > Dashboards for business users of the Power BI service
- Six ways Excel users save time with Power BI