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Microsoft Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI Sample Questions (Q89-Q94):

NEW QUESTION # 89
You are running a diagnostic against a query as shown in the following exhibit.

What can you identify from the diagnostics query?

• A. All the query steps are folding.
• B. Some query steps are folding.
• C. The query is timing out.
• D. Elevated permissions are being used to query records.

Answer: B
NEW QUESTION # 90
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have the Power Bl data model shown in the exhibit. (Click the Exhibit tab.)

Users indicate that when they build reports from the data model, the reports take a long time to load.
You need to recommend a solution to reduce the load times of the reports.
Solution: You recommend normalizing the data model.
Does this meet the goal?

• A. Yes
• B. No

Answer: B Explanation:
Instead denormalize For Performance.
Even though it might mean storing a bit of redundant data, schema denormalization can sometimes provide better query performance. The only question then becomes is the extra space used worth the performance benefit.
NEW QUESTION # 91
You manage a dataset that contains the two data sources as shown in the following table.

When you attempt to refresh the dataset in powerbi.com, you receive the following error message: "[Unable to combine data] Add Columns is accessing data sources that have privacy levels which cannot be used together. Please rebuild this data combination." You discover that the dataset contains queries that fold data from the SharePoint folder to the Azure SQL database.
You need to resolve the error. The solution must provide the highest privacy possible.
Which privacy level should you select for each data source? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer: ** Explanation:

NEW QUESTION # 92**
You use Azure Synapse Analytics and Apache Spark notebooks to You need to use PySpark to gain access to the visual libraries. Which Python libraries should you use?

• A. Seaborn and TensorFlow
• B. Matplotlib and Seaborn
• C. Matplotlib only
• D. Matplotlib and TensorFlow
• E. TensorFlow only
• F. Seaborn only

Answer: B Explanation:
Matplotlib
You can render standard plotting libraries, like Matplotlib, using the built-in rendering functions for each library.
Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy.
Additional libraries
Beyond these libraries, the Azure Synapse Analytics Runtime also includes the following set of libraries that are often used for data visualization:
Seaborn
Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics.
Reference:
https://seaborn.pydata.org/
NEW QUESTION # 93
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You are using an Azure Synapse Analytics serverless SQL pool to query a collection of Apache Parquet files by using automatic schema inference. The files contain more than 40 million rows of UTF-8-encoded business names, survey names, and participant counts. The database is configured to use the default collation.
The queries use open row set and infer the schema shown in the following table.

You need to recommend changes to the queries to reduce I/O reads and tempdb usage.
Solution: You recommend using openrowset with to explicitly define the collation for businessName and surveyName as LatimGenerai100BiN2UTF8.
Does this meet the goal?

• A. No
• B. Yes

Answer: B Explanation:
Query Parquet files using serverless SQL pool in Azure Synapse Analytics.
Important
Ensure you are using a UTF-8 database collation (for example Latin1General100BIN2UTF8) because string values in PARQUET files are encoded using UTF-8 encoding. A mismatch between the text encoding in the PARQUET file and the collation may cause unexpected conversion errors. You can easily change the default collation of the current database using the following T-SQL statement: alter database current collate Latin1General100BIN2UTF8'.
Note: If you use the Latin1General100BIN2UTF8 collation you will get an additional performance boost compared to the other collations. The Latin1General100BIN2UTF8 collation is compatible with parquet string sorting rules. The SQL pool is able to eliminate some parts of the parquet files that will not contain data needed in the queries (file/column-segment pruning). If you use other collations, all data from the parquet files will be loaded into Synapse SQL and the filtering is happening within the SQL process. The Latin1General100BIN2UTF8 collation has additional performance optimization that works only for parquet and CosmosDB. The downside is that you lose fine-grained comparison rules like case insensitivity.
NEW QUESTION # 94
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