Salesforce Analytics-Con-301 - Salesforce Certified Tableau Consultant

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.

References

This 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 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.

References

Sankey 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.

When considering a migration from Tableau Server to Tableau Cloud, two critical factors to consider are the client’s need for single sign-on (SSO) and the volume of concurrent extract refreshes.

Single Sign-On (SSO): Tableau Cloud supports SSO, which can streamline user authentication and enhance security. If the client plans to leverage SSO, Tableau Cloud may be a suitable choice1.

Concurrent Extract Refreshes: The number of concurrent extract refreshes is a significant factor because it impacts performance and resource allocation. Tableau Server might be more appropriate if the client has a high volume of concurrent extract refreshes, as it allows for more control over the infrastructure to manage these workloads2.

The correct calculation to determine the average number of days a customer must wait before a product is shipped is to first find the shipping date, which is the first day of the following month after the order date. This is done using DATETRUNC('month', DATEADD('month', 1, [Order Date])). Then, the average difference in days between the order date and the shipping date is calculated using AVG(DATEDIFF('day', [Order Date], [Calc1])). This approach ensures that the average wait time is calculated in days, which is the most precise measure for this scenario.

To minimize the impact on users when reverting to a previous version of a published data source in Tableau Server, the consultant should use the built-in revision history feature. By selecting a previous version from the revision history and clicking ‘Restore’, the data source will revert to that version without the need for a full server backup restoration or manual recreation of the data source. This process is quick and has the least amount of disruption to users.

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%.