TCC-C01 Exam Dumps : Tableau Certified Consultant

To modify the Percent Contribution calculated field to use a Level of Detail (LOD) expression and accurately calculate the percentage contribution of each manufacturer to the total quantity, follow these steps:

• Open the CC Workbook and Access the Worksheet:
• Modify the Percent Contribution Calculated Field:

{FIXED [Manufacturer]: SUM([Quantity])} / {SUM([Quantity])}Quantity])}

• uk.co.certification.simulator.questionpool.PList@1d327330
• Enter Percentage for Newell:
• Save Your Changes:

References:

• Tableau Help: Offers detailed guidance on using LOD expressions for precise and context-independent aggregations.
• Tableau Desktop User Guide: Provides comprehensive instructions on managing calculated fields and parameters, ensuring accurate data analysis.

By following these steps, you will have successfully updated the calculation for percent contribution using LOD expressions, providing a more accurate analysis of each manufacturer's contribution to the total quantity. Moreover, updating the parameter with Newell's specific contribution rounds out the task by reflecting precise data inputs for reporting or further analysis.

To ensure that each sales representative sees only data relevant to their territory, the best approach in the absence of a Tableau Data Management license involves using a joined data source with entitlements:

• Data Source Configuration: Create a data source that joins the sales data table with an entitlements table. The entitlements table contains mappings of sales representatives to their respective territories.
• Data Source Filter: Implement a data source filter that restricts data based on the current user’s access rights. This filter references the joined entitlements to dynamically control data visibility based on the logged-in user.
• Publishing the Data Source: Publish this filtered data source to Tableau Server. All workbooks or dashboards connecting to this data source inherently respect the row-level security established by the data source filter.

ReferencesThis approach aligns with Tableau’s capabilities for implementing row-level security directly within the data source, as detailed in the Tableau security management and data modeling best practices.

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.