Salesforce Analytics-Con-301 Dumps Questions Answers

Using an extract filter is an effective way to reduce the amount of data in a Tableau extract. Extract filters allow you to specify a subset of the data to include, which can significantly decrease the size of the extract by excluding unnecessary data. This is particularly useful when you only need partial data from a larger SQL Server data source.

To correctly calculate the percent of total sales for a particular region compared to all regions, and to ensure that the calculation does not get inadvertently recalculated with each region filter application, the recommended calculation is:

{FIXED [Region]: sum([Sales])}: This part of the formula computes the sum of sales for each region, regardless of any filters applied to the view. It uses a Level of Detail expression to fix the sum of sales to each region, ensuring that filtering by regions won't affect the calculated value.

SUM([Sales]): This part computes the total sum of sales across all regions and is recalculated dynamically based on the filters applied to other parts of the dashboard or worksheet.

Combining the two parts: By dividing the fixed regional sales by the total sales, we get the proportion of sales for each region as compared to the total. This calculation ensures that while the denominator adjusts according to filters, the numerator remains fixed for each region, accurately reflecting the sales percentage without being affected by the region filter directly.

References

This calculation follows Tableau’s best practices for using Level of Detail expressions to manage computation granularity in the presence of dashboard filters, as outlined in the Tableau User Guide and official Tableau training materials.

The best approach to ensure performance while providing data for only the last day (yesterday) in the dataset is to use a calculated field that filters the data to include only yesterday's date:

Filter on calculation [Ship Date]=TODAY()-1: This calculated field dynamically computes yesterday's date by subtracting one day from today’s date. This approach ensures that each day, only the data for the previous day is loaded, which keeps the volume of data minimal and improves performance.

Dynamic Date Calculation: The use of TODAY()-1 ensures the filter remains up-to-date with the changing dates, without the need for manual updates, providing accuracy and timeliness in the dashboard.

This approach is efficient because it avoids the overhead of processing the entire dataset and focuses only on the relevant day’s data. It also aligns with Tableau’s capabilities for creating dynamic filters using date functions, as highlighted in the Tableau help documentation on date calculations and filters.

References

This solution utilizes Tableau’s built-in date functions and dynamic calculations to optimize performance, as recommended in Tableau’s performance optimization resources and date calculation guidelines.