Microsoft DP-700 Trustworthy Pdf & Reliable DP-700 Exam Tips
Microsoft DP-700 Trustworthy Pdf & Reliable DP-700 Exam Tips
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Microsoft Implementing Data Engineering Solutions Using Microsoft Fabric Sample Questions (Q54-Q59):
NEW QUESTION # 54
You have an Azure event hub. Each event contains the following fields:
BikepointID
Street
Neighbourhood
Latitude
Longitude
No_Bikes
No_Empty_Docks
You need to ingest the events. The solution must only retain events that have a Neighbourhood value of Chelsea, and then store the retained events in a Fabric lakehouse.
What should you use?
- A. a KQL queryset
- B. Apache Spark Structured Streaming
- C. a streaming dataset
- D. an eventstream
Answer: D
Explanation:
An eventstream is the best solution for ingesting data from Azure Event Hub into Fabric, while applying filtering logic such as retaining only the events that have a Neighbourhood value of "Chelsea." Eventstreams in Microsoft Fabric are designed for handling real-time data streams and can apply transformation logic directly on incoming events. In this case, the eventstream can filter events based on the Neighbourhood field before storing the retained events in a Fabric lakehouse.
Eventstreams are well-suited for stream processing, such as this case where you need to filter out only specific data (events with a Neighbourhood of "Chelsea") before storing it in the lakehouse.
NEW QUESTION # 55
You plan to process the following three datasets by using Fabric:
* Dataset1: This dataset will be added to Fabric and will have a unique primary key between the source and the destination. The unique primary key will be an integer and will start from 1 and have an increment of 1.
* Dataset2: This dataset contains semi-structured data that uses bulk data transfer. The dataset must be handled in one process between the source and the destination. The data transformation process will include the use of custom visuals to understand and work with the dataset in development mode.
* Dataset3. This dataset is in a takehouse. The data will be bulk loaded. The data transformation process will include row-based windowing functions during the loading process.
You need to identify which type of item to use for the datasets. The solution must minimize development effort and use built-in functionality, when possible. What should you identify for each dataset? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 56
You have a Fabric workspace that contains an eventstream named EventStream1. EventStream1 outputs events to a table in a lakehouse.
You need to remove files that are older than seven days and are no longer in use.
Which command should you run?
- A. OPTIMIZE
- B. VACUUM
- C. CLONE
- D. COMPUTE
Answer: B
Explanation:
VACUUM is used to clean up storage by removing files no longer in use by a Delta table. It removes old and unreferenced files from Delta tables. For example, to remove files older than 7 days:
VACUUM delta.`/path_to_table` RETAIN 7 HOURS;
NEW QUESTION # 57
HOTSPOT
You have a Fabric workspace.
You are debugging a statement and discover the following issues:
Sometimes, the statement fails to return all the expected rows.
The PurchaseDate output column is NOT in the expected format of mmm dd, yy.
You need to resolve the issues. The solution must ensure that the data types of the results are retained. The results can contain blank cells.
How should you complete the statement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 58
You have an Azure Data Lake Storage Gen2 account named storage1 and an Amazon S3 bucket named storage2.
You have the Delta Parquet files shown in the following table.
You have a Fabric workspace named Workspace1 that has the cache for shortcuts enabled. Workspace1 contains a lakehouse named Lakehouse1. Lakehouse1 has the following shortcuts:
A shortcut to ProductFile aliased as Products
A shortcut to StoreFile aliased as Stores
A shortcut to TripsFile aliased as Trips
The data from which shortcuts will be retrieved from the cache?
- A. Products. Stores, and Trips
- B. Trips and Stores only
- C. Products and Store only
- D. Stores only
- E. Products only
Answer: C
Explanation:
When the cache for shortcuts is enabled in Fabric, the data retrieval is governed by the caching behavior, which generally retains data for a specific period after it was last accessed. The data from the shortcuts will be retrieved from the cache if the data is stored in locations that support caching. Here's a breakdown based on the data's location:
Products: The ProductFile is stored in Azure Data Lake Storage Gen2 (storage1). Since Azure Data Lake is a supported storage system in Fabric and the file is relatively small (50 MB), this data is most likely cached and can be retrieved from the cache.
Stores: The StoreFile is stored in Amazon S3 (storage2), and even though it is stored in a different cloud provider, Fabric can cache data from Amazon S3 if caching is enabled. This data (25 MB) is likely cached and retrievable.
Trips: The TripsFile is stored in Amazon S3 (storage2) and is significantly larger (2 GB) compared to the other files. While Fabric can cache data from Amazon S3, the larger size of the file (2 GB) may exceed typical cache sizes or retention windows, causing this file to likely be retrieved directly from the source instead of the cache.
NEW QUESTION # 59
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