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[Hardware] Analytics-Con-301 Prüfungsfrage & Analytics-Con-301 Prüfung

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【Hardware】 Analytics-Con-301 Prüfungsfrage & Analytics-Con-301 Prüfung

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Wenn Sie PrüfungFrage wählen, können Sie 100% die Prüfung bestehen. Nach den Veränderungen der Prüfungsthemen der Salesforce Analytics-Con-301 aktualisieren wir auch ständig unsere Schulungsunterlagen und bieten neue Prüfungsinhalte. PrüfungFrage bietet Ihnen rund um die Uhr kostenlosen Online-Service. Falls Sie in der Salesforce Analytics-Con-301 Zertifizierungsprüfung durchfallen, zahlen wir Ihnen die gesammte Summe zurück.
Viele Kandidaten wissen einfach nicht, wie sie sich auf die Prüfung vorbereiten können und hilflos sind. Aber mit den Schulungsunterlagen zur Salesforce Analytics-Con-301 Zertifizierungsprüfung von PrüfungFrage ist alles ganz anders geworden. Mit ihr können Sie sich ganz selbstsicher auf Ihre Prüfung vorbereiten. Sie haben kein Risiko, in der Prüfung durchzufallen, mehr zu tragen. Das ist nicht nur seelische Hilfe. Am wichitgsten ist es, dass Sie die Prüfung bestehen und eine glänzende Zukunft haben können.
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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
  • Business Consulting: For Tableau Consultants, this section involves designing and troubleshooting calculations and workbooks to meet advanced analytical use cases. It covers selecting appropriate chart types, applying Tableau’s order of operations in calculations, building interactivity into dashboards, and optimizing workbook performance by resolving resource-intensive queries and other design-related issues.
Thema 3
  • 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 4
  • 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.

Salesforce Certified Tableau Consultant Analytics-Con-301 Prüfungsfragen mit Lösungen (Q55-Q60):55. Frage
A client wants to see data for only the most recent day in the dataset that is updated intermittently. The solution should offer the best caching performance.
Which approach should the consultant use to produce the desired results?
  • A. Fixed Level of Detail (LOD) date calculation
  • B. Quick filter
  • C. Relative date filters
  • D. TODAY function
Antwort: A
Begründung:
Comprehensive and Detailed Explanation From Exact Extract:
The client wants to always show the most recent day present in the data, not today's date. The dataset is updated intermittently, meaning some days may have no new rows. Tableau documentation states that:
* Using TODAY() recalculates on every query and prevents effective caching because Tableau must compute the current date for each refresh.
* Using Relative Date Filters like "Last 1 day" also prevents caching because Tableau evaluates relative conditions each time the workbook loads.
* Quick Filters also break caching and decrease performance because they require interactive evaluation on each render.
* A FIXED LOD calculation allows Tableau to compute the maximum date inside the extract, which preserves caching because it is data-driven, not time-driven.For example:{ FIXED : MAX([Date]) } Then filtering where [Date] = { FIXED : MAX([Date]) } ensures only the most recent date in the dataset is shown.
Tableau's documentation on performance emphasizes that caching is maximized when calculations depend only on the data itself and not on functions like TODAY() or relative filters.
A FIXED LOD provides the best caching performance and correctly returns the most recent date based on the dataset rather than the current system date.
* Tableau extract caching behavior describing how data-dependent filters cache better than time- dependent filters.
* LOD Expressions guidance recommending FIXED for identifying values like "latest date in the dataset."
* Tableau performance guidelines discouraging TODAY() and relative date filters when caching is important.

56. Frage
A new Tableau user created a simple dashboard on Tableau Server using supply chain data. Now, the user wants to know if they created the dashboard in accordance with specific performance best practices.
Which approach should the consultant recommend for the client to make this determination?
  • A. Run Workbook Optimizer.
  • B. Use inbuilt dashboards in Tableau Server to troubleshoot the performance.
  • C. Use Performance Recording in Tableau Desktop.
  • D. Use Performance Recording on Tableau Server.
Antwort: A
Begründung:
The Workbook Optimizer is a tool specifically designed to evaluate a workbook against performance best practices. It provides feedback on key design characteristics and offers concrete guidance on how to improve workbook performance. This tool is beneficial for both new and experienced Tableau users to ensure their dashboards are optimized for performance1.
References: The Workbook Optimizer's functionality is detailed in Tableau's official documentation, which explains how it assesses workbooks against a set of rules derived from best practices1. Additionally, the Performance Recording feature in Tableau Desktop and Server can be used to identify performance issues, but the Workbook Optimizer gives a more comprehensive analysis of the workbook's adherence to best practices23.

57. Frage
A client wants to see the average number of orders per customer per month, broken down by region. The client has created the following calculated field:
Orders per Customer: {FIXED [Customer ID]: COUNTD([Order ID])}
The client then creates a line chart that plots AVG(Orders per Customer) over MONTH(Order Date) by Region. The numbers shown by this chart are far higher than the customer expects.
The client asks a consultant to rewrite the calculation so the result meets their expectation.
Which calculation should the consultant use?
  • A. {FIXED [Customer ID], [Region]: COUNTD([Order ID])}
  • B. {EXCLUDE [Customer ID]: COUNTD([Order ID])}
  • C. {INCLUDE [Customer ID]: COUNTD([Order ID])}
  • D. {FIXED [Customer ID], [Region], [Order Date]: COUNTD([Order ID])}
Antwort: A
Begründung:
The calculation {FIXED [Customer ID], [Region]: COUNTD([Order ID])} is the correct one to use for this scenario. This Level of Detail (LOD) expression will calculate the distinct count of orders for each customer within each region, which is then averaged per month. This approach ensures that the average number of orders per customer is accurately calculated for each region and then broken down by month, aligning with the client's expectations.
References: The LOD expressions in Tableau allow for precise control over the level of detail at which calculations are performed, which is essential for accurate data analysis. The use of {FIXED} expressions to specify the granularity of the calculation is a common practice and is well-documented in Tableau's official resources12.
The initial calculation provided by the client likely overestimates the average number of orders per customer per month by region due to improper granularity control. The revised calculation must take into account both the customer and the region to correctly aggregate the data:
FIXED Level of Detail Expression: This calculation uses a FIXED expression to count distinct order IDs for each customer within each region. This ensures that the count of orders is correctly grouped by both customer ID and region, addressing potential duplication or misaggregation issues.
Accurate Aggregation: By specifying both [Customer ID] and [Region] in the FIXED expression, the calculation prevents the overcounting of orders that may appear if only customer ID was considered, especially when a customer could be ordering from multiple regions.
References:
Level of Detail Expressions in Tableau: These expressions allow you to specify the level of granularity you need for your calculations, independent of the visualization's level of detail, thus offering precise control over data aggregation.

58. Frage
A business analyst needs to create a view in Tableau Desktop that reports data from both Excel and MSSQL Server.
Which two features should the business analyst use to create the view? Choose two.
  • A. Union
  • B. Cross-Database Joins
  • C. Data Blending
  • D. Relationships
Antwort: B,D
Begründung:
Comprehensive and Detailed Explanation From Exact Extract:
To combine Excel and SQL Server data in the same logical data model, Tableau offers two supported capabilities:
Relationships
* Recommended modern method for combining tables from multiple sources.
* Supports cross-database relationships between Excel and SQL Server.
* Maintains separate physical layers but integrates data at query time.
Cross-Database Joins
* Allows joining data from different databases in the physical layer.
* Fully supported for Excel + MS SQL Server.
* Useful when granular row-level merging is needed.
Why the other options are incorrect:
C). Data Blending
* Legacy feature, used only when no direct combination is possible.
* Tableau recommends relationships instead.
* Produces separate queries and may lose row-level detail.
D). Union
* Requires tables to have equivalent structure.
* Cannot union Excel with SQL Server unless identical column structure exists.
* Not appropriate for most mixed-source reporting.
Therefore, the correct techniques are Relationships and Cross-Database Joins.
* Tableau data modeling documentation recommending Relationships for multi-source modeling.
* Cross-database join support list including Excel + SQL Server.

59. Frage
A client has many published data sources in Tableau Server. The data sources use the same databases and tables. The client notices different departments give different answers to the same business questions, and the departments cannot trust the data. The client wants to know what causes data sources to return different data.
Which tool should the client use to identify this issue?
  • A. Tableau Catalog
  • B. Ask Data
  • C. Tableau Prep Conductor
  • D. Tableau Resource Monitoring Tool
Antwort: A
Begründung:
The Tableau Catalog is part of the Tableau Data Management Add-on and is designed to help users understand the data they are using within Tableau. It provides a comprehensive view of all the data assets in Tableau Server or Tableau Online, including databases, tables, and fields. It can help identify issues such as data quality, data lineage, and impact analysis. In this case, where different departments are getting different answers to the same business questions, the Tableau Catalog can be used to track down inconsistencies and ensure that everyone is working from the same, reliable data source.
References: The recommendation for using Tableau Catalog is based on its features that support data discovery, quality, and governance, which are essential for resolving data inconsistencies across different departments12.
When different departments report different answers to the same business questions using the same databases and tables, the issue often lies in how data is being accessed and interpreted differently across departments.
Tableau Catalog, a part of Tableau Data Management, can be used to solve this problem:
Visibility: Tableau Catalog gives visibility into the data used in Tableau, showing users where data comes from, where it's used, and who's using it.
Consistency and Trust: It helps ensure consistency and trust in data by providing detailed metadata management that can highlight discrepancies in data usage or interpretation.
Usage Metrics and Lineage: It offers tools for tracking usage metrics and understanding data lineage, which can help in identifying why different departments might see different results from the same underlying data.
References:
Tableau Catalog Usage: The Catalog is instrumental in providing a detailed view of the data environment, allowing organizations to audit, track, and understand data discrepancies across different users and departments.

60. Frage
......
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Analytics-Con-301 Prüfung: https://www.pruefungfrage.de/Analytics-Con-301-dumps-deutsch.html
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