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Salesforce Analytics-Con-301 考試大綱：

最新的 Salesforce Consultant Analytics-Con-301 免費考試真題 (Q49-Q54):

問題 #49
A performance recording of a workbook shows that a query to an extracted data source is taking too long.
Which area should the consultant focus on optimizing if "Executing Query" is taking a long time?

• A. The use of filters on the Tableau dashboard
• B. The database's underlying data structure
• C. Replacing nested calculations and Levels of Detail (LODs)
• D. The number of VizQL processes

答案：C

解題說明：
Comprehensive and Detailed Explanation From Exact Extract:
In Tableau Performance Recording, "Executing Query" refers to the amount of time Tableau spends executing the SQL or hyper query generated by the workbook. When an extract is used, the query is executed against the .hyper extract, not the original database.
Tableau documentation identifies several causes of slow query execution within extracts, including:
* Nested row-level calculations
* Complex logic in calculated fields
* Multiple Levels of Detail (LOD) expressions
* Non-optimized expressions that force Tableau to compute additional temporary tables These directly increase query complexity and cause longer "Executing Query" durations.
Therefore, optimizing the query requires simplifying or replacing:
* Nested calculations
* Unnecessary LOD expressions
* Complex expressions that increase the workload on the extract engine
Option A is incorrect because the number of VizQL processes affects concurrency, not query execution time.
Option B is partially relevant, but dashboard filters affect the overall workload, not the specific query complexity. If the performance recording shows "Executing Query" as the slow section, the query itself (not the filter UI layer) is the problem.
Option D does not apply because extracts use the hyper engine, not the underlying database. Optimizing the original database structure does not change the extract query execution time.
Thus, the consultant should focus on simplifying nested calculations and LODs to reduce extract query complexity.
* Tableau Performance Recording guide describing "Executing Query" as dependent on calculation complexity.
* Tableau extract engine documentation explaining that nested logic, multiple LODs, and granular calculations generate slower extract queries.
* Best practices recommending simplification of calculated fields to improve extract query performance.

問題 #50
A client creates a report and publishes it to Tableau Server where each department has its own user group set on the server. The client wants to limit visibility of the report to the sales and marketing groups in the most efficient manner.
Which approach should the consultant recommend?

• A. Prepare a row-level security (RLS) entitlement table to define limitations of the access and use it to build user filters in the report's data source.
• B. Add user filters from Tableau Server to each worksheet and select only sales and marketing user groups.
• C. Grant access to the report on the Tableau Server only to the members of sales and marketing user groups.
• D. Use user groups defined on Tableau Server to build user filters in the report's data source.

答案：C

解題說明：
The most efficient way to limit report visibility to specific user groups on Tableau Server is to manage permissions directly on the server. By granting access to the report only to the sales and marketing user groups, the client ensures that only members of these groups can view the report. This method is straightforward and does not require the additional steps involved in setting up row-level security or user filters.
References: The approach is supported by best practices in managing user permissions and visibility on Tableau Server, as described in the Tableau Community and official Tableau resources12.

問題 #51
A client collects information about a web browser customers use to access their website. They then visualize the breakdown of web traffic by browser version.
The data is stored in the format shown below in the related table, with a NULL BrowserID stored in the Site Visitor Table if an unknown browser version accesses their website.

The client uses "Some Records Match" for the Referential Integrity setting because a match is not guaranteed.
The client wants to improve the performance of
the dashboard while also getting an accurate count of site visitors.
Which modifications to the data tables and join should the consultant recommend?

• A. Add an "Unknown" option to the Browser Table, reference its BrowserID in the Site Visitor Table, and change the Referential Integrity to "All Records Match."
• B. Add an "Unknown" option to the Browser Table, reference its BrowserID in the Site Visitor Table, and leave the Referential Integrity set to
  "Some Records Match."
• C. Continue to use NULL as the BrowserID in the Site Visitor Table and leave the Referential Integrity set to "Some Records Match."
• D. Continue to use NULL as the BrowserID in the Site Visitor Table and change the Referential Integrity to "All Records Match."

答案：A

解題說明：
To improve the performance of a Tableau dashboard while maintaining accurate counts, particularly when dealing with unknown or NULL BrowserIDs in the data tables, the following steps are recommended:
* Modify the Browser Table: Add a new row to the Browser Table labeled "Unknown," assigning it a unique BrowserID, e.g., 0 or 4.
* Update the Site Visitor Table: Replace all NULL BrowserID entries with the BrowserID assigned to the "Unknown" entry. This ensures every record in the Site Visitor Table has a valid BrowserID that corresponds to an entry in the Browser Table.
* Change Referential Integrity Setting: Change the Referential Integrity setting from "Some Records Match" to "All Records Match." This change assumes all records in the primary table have corresponding records in the secondary table, which improves query performance by allowing Tableau to make optimizations based on this assumption.
References:
Handling NULL Values: Replacing NULL values with a valid unknown option ensures that all data is included in the analysis, and integrity between tables is maintained, thereby optimizing the performance and accuracy of the dashboard.

問題 #52
A consultant wants to improve the performance of reports by moving calculations to the data layer and materializing them in the extract.
Which calculation should the consultant use?

• A. POWER(ZN(SUM([Sales]))/
  LOOKUP(ZN(SUM([Sales])), FIRST()),ZN(1/(INDEX()-1)))- 1END
• B. SUM([Profit])/SUM([Sales])
• C. ZN([Sales])*(1 - ZN([Discount]))
• D. CASE [Sector Parameter]
  WHEN 1 THEN "green"
  WHEN 2 THEN "yellow"

答案：B

解題說明：
To improve performance by moving calculations to the data layer and materializing them in the extract, the consultant should choose calculations that benefit from pre-computation and significantly reduce the load during query time:
* Aggregation-Level Calculation: The formula SUM([Profit])/SUM([Sales]) calculates a ratio at an aggregate level, which is ideal for pre-computation. Materializing this calculation in the extract means that the complex division operation is done once and stored, rather than being recalculated every time the report is accessed.
* Performance Improvement: By pre-computing this aggregate ratio, Tableau can utilize the pre- calculated fields directly in visualizations, which speeds up report loading and interaction times as the heavy lifting of data processing is done during the data preparation stage.
References:
Materialization in Extracts: This concept involves pre-calculating and storing complex aggregations or calculations within the Tableau data extract itself, improving performance by reducing the computational load during visualization rendering.

問題 #53
SIMULATION
From the desktop, open the CC workbook. Use the US Population Estimates data source.
You need to shape the data in US Population Estimates by using Tableau Desktop. The data must be formatted as shown in the following table.

Open the Population worksheet. Enter the total number of records contained in the data set into the Total Records parameter.
From the File menu in Tableau Desktop, click Save.

答案：

解題說明：
See the complete Steps below in Explanation
Explanation:
To shape the data in the "US Population Estimates" data source and enter the total number of records into the "Total Records" parameter in Tableau Desktop, follow these steps:
Open the CC Workbook and Access the Worksheet:
From the desktop, double-click on the CC workbook to open it in Tableau Desktop.
Navigate to the Population worksheet by selecting its tab at the bottom of the window.
Format and Shape the Data:
Ensure the data types match those specified in the requirements: Sex, Origin, Race as strings; Year, Age, Population as whole numbers.
To verify or change the data type, click on the dropdown arrow next to each field name in the Data pane and select "Change Data Type" if necessary.
Calculate Total Number of Records:
Create a new calculated field named "Total Records". To do this, right-click in the Data pane and select "Create Calculated Field".
Enter the formula COUNT([Record ID]) or SUM([Number of Records]) depending on how the data source identifies each row uniquely.
Drag this new calculated field onto the worksheet to display the total number of records.
Enter the Value into the Total Records Parameter:
Locate the "Total Records" parameter in the Data pane. Right-click on the parameter and select "Edit".
Manually enter the number displayed from the calculated field into the parameter, ensuring accuracy to meet the data shaping requirement.
Save Your Changes:
From the File menu, click 'Save' to ensure all your changes are stored.
References:
Tableau Desktop Guide: Provides detailed instructions on managing data types, creating calculated fields, and updating parameters.
Tableau Data Shaping Techniques: Outlines effective methods for manipulating and structuring data for analysis.
This process will ensure the data in the "US Population Estimates" is accurately shaped according to the specified format and that the total number of records is correctly calculated and entered into the designated parameter. This thorough approach ensures data integrity and accuracy in reporting.

問題 #54
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