Salesforce Analytics-Con-301 Practice Test Questions Answers

To transform the Orderld field in Tableau Prep, the Split option is the most efficient and straightforward method. Here’s how you can apply it:

In Tableau Prep, drag your dataset into the flow.

Click on the Orderld field in the workspace to select it.

Look for the option in the toolbar that says "Split" and select it.

Choose "Automatic Split" if the delimiters (such as hyphens) are consistent; Tableau Prep should automatically detect the hyphen as the delimiter and split the Orderld into multiple new fields.

The dataset should now show new columns: one for the country code (CA, FR, US), one for the year (2017), and one for the order number (152156, 152157, etc.).

The Split option works effectively here because it automatically identifies and uses the hyphen as the delimiter to divide the original Orderld into the desired components without manual specification of conditions or writing any formulas.

References

This procedure is based on the standard functionalities provided in Tableau Prep for splitting a field into multiple columns based on a delimiter, as described in the Tableau Prep user guide.

To flag orders with sales higher than the regional average, the correct calculated field would compare the sum of sales for each order against the average sales of all orders within the same region:

Correct Formula: { FIXED [Order ID] : SUM([Sales]) } > { FIXED [Region] : AVG({ FIXED [Order ID] : SUM([Sales]) }) }

This calculation uses a Level of Detail (LOD) expression:

The left part of the formula { FIXED [Order ID] : SUM([Sales]) } calculates the total sales for each individual order.

The right part { FIXED [Region] : AVG({ FIXED [Order ID] : SUM([Sales]) }) } calculates the average sales per order within each region.

The > operator is used to compare these two values to determine if the sales for each order exceed the regional average.

References

This formula utilizes Tableau's LOD expressions to perform complex comparisons across different dimensions of the data, as explained in Tableau's official training materials on LOD calculations.

To optimize the dashboard rendering, particularly when dealing with a large dataset, a filter action is the most effective tool. Here's why the specified choice is optimal:

Add a filter action: This action creates a direct filter on the detail table based on the selection in the bar chart. It ensures that only data related to the selected sub-category is loaded into the table, significantly reducing load time and improving performance.

Set "Run action on" to Select: This setting means the filter action will be triggered as soon as the user selects a bar in the bar chart. Immediate activation of the filter ensures that the dashboard is interactive and responsive.

Set "Clearing the selection will" to Exclude all values: When the selection is cleared, this setting ensures that no data is shown, which avoids loading the entire dataset unnecessarily. This maintains performance when no sub-category is actively selected.

References

This strategy follows Tableau’s performance best practices by using actions to limit the amount of data processed and rendered, as detailed in the Tableau User Guide and training materials on Dashboard Actions for optimizing large datasets.

To calculate the Total Sales Value for all categories as displayed in the table, an LOD expression is ideal. An LOD calculation in Tableau allows you to compute values at the data level that is different from the view level. In this case, since the Total Sales Value appears consistent across different sub-categories within each category, an LOD expression can be used to fix the Total Sales Value irrespective of the sub-category detail. Here's how to set it up:

Go to the Calculations area by right-clicking in the data pane and selecting "Create Calculated Field".

Enter a name for the calculation, such as "Total Sales Value".

Enter the LOD expression: { FIXED [Category] : SUM([Sales]) }. This calculation fixes the total sales to the category level, effectively summing sales for all sub-categories within each category, irrespective of how the data is broken down in the view.

Drag this new calculated field into your visualization alongside the existing measures.

This method ensures that the Total Sales Value reflects the total for each category across all its sub-categories, matching the uniform values shown across different rows for each category in your table.

References

The explanation utilizes the concept of Level of Detail calculations in Tableau, which allows for advanced aggregations independent of the view level details. This concept is covered extensively in Tableau's official documentation and relevant training materials such as Tableau's online help resources.

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.

References

This 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.