Analytics-Con-301 Fragen Und Antworten, Analytics-Con-301 Prüfungsmaterialien

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>> Analytics-Con-301 Fragen Und Antworten <<

Analytics-Con-301 Prüfungsmaterialien - Analytics-Con-301 Quizfragen Und Antworten

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Salesforce Analytics-Con-301 Prüfungsplan:

ThemaEinzelheiten
Thema 1
  • Data Analysis: This domain targets Tableau Consultants to plan and prepare data connections effectively. It includes recommending data transformation strategies, designing row-level security (RLS) data structures, and implementing advanced data connections such as Web Data Connectors and Tableau Bridge. Skills in specifying granularity and aggregation strategies for data sources across Tableau products are emphasized.
Thema 2
  • Data Management: This part focuses on establishing governance and support for published content. Tableau Consultants are expected to manage data security, publish and maintain data sources and workbooks, and oversee content access. It includes applying governance best practices, using metadata APIs, and supporting administration functions to maintain data integrity and accessibility.
Thema 3
  • Data Visualization: This section evaluates the Tableau Consultant’s ability to design effective visual analytics solutions. It involves creating dashboards and visual reports that enhance user understanding, employing techniques like dynamic actions and advanced chart types, and ensuring performance optimization for an interactive user experience.
Thema 4
  • Business Analysis: This section of the exam measures skills of Tableau Consultants focusing on evaluating the current state of analytics within an organization. It covers mapping business needs to Tableau capabilities, translating analytical requirements to best practices in Tableau, and recommending appropriate deployment options like Tableau Server or Tableau Cloud. It also includes evaluating existing data structures for supporting business needs and identifying performance risks and opportunities.

Salesforce Certified Tableau Consultant Analytics-Con-301 Prüfungsfragen mit Lösungen (Q29-Q34):

29. Frage
A consultant is designing a dashboard that will be consumed on desktops, tablets, and phones. The consultant needs to implement a dashboard design that provides the best user experience across all the platforms.
Which approach should the consultant take to achieve these results?

Antwort: C

Begründung:
For a consultant designing a dashboard to be consumed across multiple device types, the best approach is:
* Multi-device Layout: Tableau provides the capability to design device-specific layouts within a single dashboard. This feature allows the dashboard to adapt its layout to best fit the screen size and orientation of desktops, tablets, and phones.
* Fixed Size Layouts: By fixing the size of each layout, the consultant can ensure that the dashboard appears consistent and maintains the intended design elements and user experience across devices.
Fixed sizes prevent components from resizing in ways that could disrupt the dashboard's readability or functionality.
* Implementation: In Tableau, you can create these layouts by selecting 'Device Preview' and adding custom layouts for each device type. Here, you define the dimensions and the positioning of sheets and controls tailored to each device's typical viewing mode.
References
This approach leverages Tableau's device designer capabilities, which are specifically designed to optimize dashboards for multiple viewing environments, ensuring a seamless user experience regardless of the device used. This functionality is well documented in Tableau's official guides on creating and managing device- specific dashboards.


30. Frage
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?

Antwort: C

Begründung:
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.


31. Frage
A client has a pipeline dashboard that takes a long time to load. The dashboard is connected to only one large data source that is an extract.
It contains two calculated fields:
. TOTAL([Opportunities])
* SUM([Value])
It also contains two filters:
. A Relative Date filter on Created Date, a Date field containing values from 5 years ago until today
. A Multiple Values (Dropdown) filter on Account Name, a String field containing 1,000 distinct values A consultant creates a Performance Recording to troubleshoot the issue, and finds out that the longest-running event is "Executing Query." Which step should the consultant take to resolve this issue?

Antwort: D

Begründung:
To improve the loading time of the pipeline dashboard, which primarily suffers from long query execution times due to a comprehensive Relative Date filter:
Relative Date Filter Issue: The existing Relative Date filter on "Created Date" covers a broad range (5 years), leading to significant data processing overhead as it includes granular date calculations over a large dataset.
Optimized Approach: By replacing the Relative Date filter with a Multiple Values (Dropdown) filter based on YEAR([Created Date]), the filter granularity is reduced. Filtering by year simplifies the query by limiting the volume of data processed and reducing the complexity of the filter condition.
Implementation Benefit: This approach still provides the flexibility to view data across different years but does so by reducing the load on the database during query execution, which is critical for improving the performance of the dashboard.
References
This recommendation aligns with Tableau performance optimization strategies, specifically regarding the management of date filters to minimize their impact on query load, as discussed in Tableau performance tuning sessions and guides.


32. Frage
Sales managers use a daily extract from Snowflake to see the previous day's snapshot.
Sales managers should only see statistics for their direct reports.
The company has Tableau Data Management on Tableau Cloud.
A consultant must design a centralized, low-maintenance RLS strategy.
What should the consultant implement?

Antwort: A

Begründung:
Comprehensive and Detailed Explanation From Exact Extract:
The key requirements:
* Tableau Cloud
* Extracts (not live data)
* Need RLS
* Want low maintenance
* Have Tableau Data Management
These requirements point directly to:
Data Policies (Virtual Connections RLS)
Tableau Data Management enables Virtual Connections and Data Policies, which provide:
* Centralized row-level security
* Integration with user identity via USERNAME()
* Reusable RLS logic across all downstream workbooks
* Works with extracts, unlike database RLS
* Minimal long-term maintenance
This is Tableau's recommended enterprise RLS method for Tableau Cloud with extracts.
Why the other options are incorrect:
A). Built-in RLS in Snowflake
Only works with live connections.
This client uses daily extracts, so database RLS is bypassed.
C). Manual user filter
High maintenance, must be edited manually per user - not scalable.
D). Dynamic user filter
Functional but must be recreated in each workbook, not centralized.
More maintenance than a data policy.
Therefore, Data Policy is the only low-maintenance, centralized RLS solution.
* Data Policies and Virtual Connections documentation describing centralized RLS
* Tableau Cloud & Extracts guidelines showing that database RLS cannot be reused
* RLS strategy best practices recommending Data Policies for scalable governance


33. Frage
A Tableau Cloud client has requested a custom dashboard to help track which data sources are used most frequently in dashboards across their site.
Which two actions should the client use to access the necessary metadata? Choose two.

Antwort: A,C

Begründung:
To track which data sources are used most frequently across a site in Tableau Cloud, the client should use the GraphiQL engine and the Metadata API. The GraphiQL engine allows for interactive exploration of the metadata, making it easier to construct and test queries1. The Metadata API provides access to metadata and lineage of external assets used by the content published to Tableau Cloud, which is essential for tracking data source usage2.
References: The actions are based on the capabilities of the GraphiQL engine and the Metadata API as described in Tableau's official documentation and learning resources321.


34. Frage
......

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Analytics-Con-301 Prüfungsmaterialien: https://www.zertpruefung.de/Analytics-Con-301_exam.html

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