Reliable Microsoft DP-300 Test Tips - DP-300 Reliable Exam Pattern

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Microsoft Administering Relational Databases on Microsoft Azure Sample Questions (Q229-Q234):

NEW QUESTION # 229
You are designing a date dimension table in an Azure Synapse Analytics dedicated SQL pool. The date dimension table will be used by all the fact tables.
Which distribution type should you recommend to minimize data movement?

Answer: A

Explanation:
Section: [none]
Explanation:
A replicated table has a full copy of the table available on every Compute node. Queries run fast on replicated tables since joins on replicated tables don't require data movement. Replication requires extra storage, though, and isn't practical for large tables.
Incorrect Answers:
C: A round-robin distributed table distributes table rows evenly across all distributions. The assignment of rows to distributions is random. Unlike hash-distributed tables, rows with equal values are not guaranteed to be assigned to the same distribution.
As a result, the system sometimes needs to invoke a data movement operation to better organize your data before it can resolve a query.
Reference:
https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables- distribute


NEW QUESTION # 230
You need to design an analytical storage solution for the transactional dat a. 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://rajanieshkaushikk.com/2020/09/09/how-to-choose-right-data-distribution-strategy-for-azure-synapse/


NEW QUESTION # 231
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 area.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:

Box 1: Store the infrastructure logs in the Cool access tier the application logs in the Archive access tier Hot - Optimized for storing data that is accessed frequently.
Cool - Optimized for storing data that is infrequently accessed and stored for at least 30 days.
Archive - Optimized for storing data that is rarely accessed and stored for at least 180 days with flexible latency requirements, on the order of hours.
Box 2: Azure Blob storage lifecycle management rules
Blob storage lifecycle management offers a rich, rule-based policy that you can use to transition your data to the best access tier and to expire data at the end of its lifecycle.
Reference:
https://docs.microsoft.com/en-us/azure/storage/blobs/storage-blob-storage-tiers


NEW QUESTION # 232
You have the following Transact-SQL query.

Which column returned by the query represents the free space in each file?

Answer: B

Explanation:
Example:
Free space for the file in the below query result set will be returned by the FreeSpaceMB column.
SELECT DB_NAME() AS DbName,
name AS FileName,
type_desc,
size/128.0 AS CurrentSizeMB,
size/128.0 - CAST(FILEPROPERTY(name, 'SpaceUsed') AS INT)/128.0 AS FreeSpaceMB FROM sys.database_files WHERE type IN (0,1); Reference:
https://www.sqlshack.com/how-to-determine-free-space-and-file-size-for-sql-server-databases/


NEW QUESTION # 233
You have an Azure data factory that has two pipelines named PipelineA and PipelineB.
PipelineA has four activities as shown in the following exhibit.

PipelineB has two activities as shown in the following exhibit.

You create an alert for the data factory that uses Failed pipeline runs metrics for both pipelines and all failure types. The metric has the following settings:
Operator: Greater than
Aggregation type: Total
Threshold value: 2
Aggregation granularity (Period): 5 minutes
Frequency of evaluation: Every 5 minutes
Data Factory monitoring records the failures shown in the following table.

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:

Reference:
https://docs.microsoft.com/en-us/azure/azure-monitor/alerts/alerts-metric-overview


NEW QUESTION # 234
......

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