Tableau TCC-C01 Exam Questions

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.

Reference 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.

The correct calculation to count all distinct orders placed in 2010 involves placing the conditional inside the aggregation function, not the other way around. Here's how to correct the client's calculation:

Original Calculation Issue: The client's original calculation attempts to apply the COUNTD function within an IF statement, which does not work as expected because the COUNTD function cannot conditionally count within the scope of the IF statement.

Correct Calculation: COUNTD(IF YEAR([Date]) = 2010 THEN [OrderID] END). This calculation checks each order date; if the year is 2010, it returns the OrderID. The COUNTD function then counts all unique OrderIDs that meet this condition.

Why It Works: This method ensures that each order is first checked for the year condition before being counted, effectively filtering and counting in one step. It efficiently processes the data by focusing the distinct count operation only on relevant records.

Reference This approach is consistent with Tableau's guidance on using conditional logic inside aggregation functions for accurate and efficient data calculations, as detailed in the Tableau User Guide under 'Aggregations and Calculations'.

The most user-friendly solution is to use Dynamic Zone Visibility in combination with a Show/Hide Button. This approach allows the dashboard to dynamically display only the relevant quick filters based on the viewer's selection of shops or warehouses, thus reducing clutter and focusing the user's attention on applicable filters. The Show/Hide Button further enhances the user experience by allowing viewers to toggle the visibility of the filter container, providing a clean and organized dashboard interface1.

For a performant live connection in Tableau Cloud, especially when dealing with large datasets that preclude the use of extracts, relating the tables in Tableau Desktop is the recommended approach. This method allows for flexibility in how the data is queried and can improve performance by leveraging Tableau's relationships feature, which optimizes queries for the underlying database.