TCC-C01 Sample Questions Answers

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:
• Format and Shape the Data:
• Calculate Total Number of Records:
• Enter the Value into the Total Records Parameter:
• Save Your Changes:

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.

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.

When a filter is applied directly to the view, it can affect the calculation of percentages in a histogram because it changes the underlying data that the quick table calculation is based on. To avoid this, adding the [Profit] filter to the context will maintain the original calculation of percent shares while filtering out bins with less than a 15% share. This is because context filters are applied before any other calculations, so the percent shares calculated will be based on the context-filtered data, thus preserving the integrity of the original percent labels.

References:The solution is based on the principles of context filters and their order of operations in Tableau, which are documented in Tableau’s official resources and community discussions123.

When a histogram is created showing the distribution of profits with labels indicating percent shares using a quick table calculation, and a need arises to limit the view to bins with at least a 15% share, applying a standard profit filter directly may undesirably alter how the percent labels calculate because they depend on the overall distribution of data. Placing the [Profit] filter into the context makes it a "context filter," which effectively changes how data is filtered in calculations:

• Create a Context Filter: Right-click on the profit filter and select "Add to Context". This action changes the order of operations in filtering, meaning the context filter is applied first.
• Adjust the Percent Calculation: With the profit filter set in the context, it first reduces the data set to only those profits that meet the filter criteria. Subsequently, any table calculations (like the percent share labels) are computed based on this reduced data set.
• View Update: The view now updates to display only those bins where the profits are at least 15%, and the percent share labels recalculated to reflect the distribution of only the filtered (contextual) data.

References:

• Context Filters in Tableau: Context filters are used to filter the data passed down to other filters, calculations, the marks card, and the view. By setting the profit filter as a context filter, it ensures that calculations such as the percentage shares are based only on the filtered subset of the data.

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.

The calculationDATEPART('iso-weekday', [Order Date])=1 or DATEPART('iso-weekday', [Order Date])=7is recommended because the ISO standard considers Monday as the first day of the week (1) and Sunday as the last day (7). This calculation will correctly identify Saturdays and Sundays regardless of the locale settings of the workbook’s data source, ensuring that the report includes these days as specified by the client.

References:The use of the ‘iso-weekday’ part in the DATEPART function is consistent with the ISO 8601 standard, which is independent of locale settings.This approach is supported by Tableau’s documentation on date functions and their behavior with different locale settings123.

To accurately identify weekends across different locale settings, using the 'iso-weekday' component is reliable as it is consistent across various locales:

• ISO Weekday Function: The ISO standard treats Monday as the first day of the week (1), which makes Sunday the seventh day (7). This standardization helps avoiddiscrepancies in weekday calculations that might arise due to locale-specific settings.
• Identifying Weekends: The calculation checks if the 'iso-weekday' part of the date is either 1 (Sunday) or 7 (Saturday), thereby correctly identifying weekends regardless of the locale settings.

References:

• Handling Locale-Specific Settings: Using ISO standards in date functions allows for uniform results across systems with differing locale settings, essential for consistent reporting in global applications.

The correct calculation for classifying profit margins into categories based on specified thresholds involves the use of conditional statements that check ranges in a logical order:

• Highly Profitable Classification: The first condition checks if the profit margin is 50% or more. This must use the ">=" operator to include exactly 50% as "Highly Profitable".
• Profitable Classification: The next condition checks if the profit margin is between 0% and 50%. Since any value falling at or above 50% is already classified, this condition only needs to check for values greater than or equal to 0%.
• Unprofitable Classification: The final condition captures any remaining scenarios, which would only be values less than 0%.

References:

• Logical Order in Conditional Statements: It is crucial in programming and data calculation to ensure that conditions in IF statements are structured in a logical and non-overlapping manner to accurately categorize all possible values.

When “Apply to Nested Projects” is checked in Tableau Server, the permission rules set at the top-level project are enforced for all assets in the project and all nested projects. This means that any custom access previously granted to nested projects will be overridden, and the permissions will revert to those defined at the top-level project. This action ensures consistent application of the data governance strategy across all divisions.

References:The impact of checking “Apply to Nested Projects” is detailed in Tableau’s official documentation, which explains how locked nested projects can be used to govern site content with greater flexibility and efficiency12.

To ensure that users automatically see Tableau views of regional sales filtered by customer as they sign into Salesforce, embedding the views directly into Salesforce is most effective:

• Embedding Views: Tableau provides capabilities to embed its dashboards into web applications such as Salesforce. This approach ensures that the visualization is part of the Salesforce user interface, enhancing user experience by not requiring users to navigate away from Salesforce to view the data.
• Implement this by using Tableau's embedding code, which can be generated from the Tableau Server for each specific view. Place this embed code into the Salesforce Visualforce pages or use Salesforce Canvas to integrate these views seamlessly.
• This setup allows the Tableau views to inherit user credentials from Salesforce, enabling personalized data visualization based on the user's access rights and region, directly aligned with their Salesforce login session.

ReferencesThe embedding technique is documented in both Tableau's and Salesforce's official integration guides, which provide step-by-step instructions on embedding Tableau views into Salesforce platforms.

To minimize user impact and costs while migrating from Tableau Server to Tableau Cloud with multiple sites, the best solution is:

• Single Tableau Cloud Instance with Multiple Projects: Instead of multiple sites which could imply higher management overhead and possibly higher costs, configuring one Tableau Cloud instance with different project folders for each former site (Finance, Strategy, Marketing) is most efficient.
• Benefits: This setup maintains organizational separation of data and access similar to having different sites but leverages the unified management and simplicity of a single cloud instance. It reduces complexity in user access management and integration points.
• Implementation: Each project folder acts like a mini-site within the larger instance, where specific permissions and content can be managed independently, akin to the original server setup but within a single cloud-based environment.

ReferencesThis recommendation is in line with best practices for cloud migration focusing on consolidation and cost efficiency, as suggested in Tableau’s official documentation for cloud migration strategies.

To identify which workbooks need to be updated to point to a new data source after a migration, a consultant should use Tableau Advanced Management. This component of Tableau provides comprehensive management capabilities including the ability to track workbook dependencies and data source usage across your entire Tableau environment. Using Tableau Advanced Management allows consultants to assess the impact of changes in the data source on connected workbooks and efficiently manage updates.

To build efficient extracts from large data sources, it is crucial to minimize the load and optimize the performance of the extracts:

• A. Keep only the data required for analysis by using extract filters: This best practice involves using filters to reduce the volume of data extracted, thus focusing only on the data necessary for analysis.
• B. Use aggregate data for visible dimensions, whenever possible: Aggregating data at the time of extraction reduces the granularity of the data, which can significantly improve performance and reduce the size of the extract.
• E. Hide all unused fields: Removing fields that are not needed for analysis from the extract reduces the complexity and size of the data model, which in turn enhances performance and speeds up load times.

These practices are endorsed in Tableau’s official documentation and training sessions as effective ways to enhance the performance of Tableau extracts and optimize dashboard responsiveness.

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.

ReferencesThis 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.

To visualize the path students take as they change majors across different grade levels, a Sankey Diagram is highly effective. This type of visualization illustrates the flow and quantity between different stages or categories:

• Sankey Diagram: It allows for a visual representation of students' movements between majors over time. Each flow's thickness is proportional to the number of students moving from one major to another, giving a clear, immediate visual cue of major popularity and student migration patterns.
• To create a Sankey Diagram in Tableau, you typically need to prepare the data specifically for this type of chart. The data must include source (starting major), target (ending major), and the value (number of students). It often requires custom calculations and data reshaping to get the data in a format that a Sankey can use.
• Once the data is prepared, you can use a combination of calculated fields, path binning, and line charts to simulate the flow effect in Tableau. External plugins or web-based integrations might also be employed for more direct implementations.

ReferencesSankey Diagrams are not natively supported in Tableau but can be implemented through creative use of data preparation and calculations, as suggested in advanced Tableau user communities and demonstrated in various Tableau public galleries.