Tableau TCC-C01 Practice Exams
Last updated on Oct 22,2026- Exam Code: TCC-C01
- Exam Name: Tableau Certified Consultant
- Certification Provider: Tableau
- Latest update: Oct 22,2026
A client has a pipeline dashboard that takes a long time to load. The dashboard is connected to only one large data source that is an extract.
It contains two calculated fields:
– TOTAL([Opportunities])
– SUM([Value])
It also contains two filters:
– A Relative Date filter on Created Date, a Date field containing values from 5 years ago until today
– A Multiple Values (Dropdown) filter on Account Name, a String field containing 1,000 distinct values
A consultant creates a Performance Recording to troubleshoot the issue, and finds out that the longest-running event is "Executing Query."
Which step should the consultant take to resolve this issue?
- A . Replace the Multiple Values (Dropdown) filter with a Multiple Values (Custom List) filter.
- B . Replace the Relative Date filter with a Multiple Values (Dropdown) filter on YEAR([Created Date]).
- C . Replace the TOTAL([Opportunities]) calculation with a Grand Total.
- D . Replace SUM([Value]) with WINDOW_SUM([Value]).
B
Explanation
To improve the loading time of the pipeline dashboard, which primarily suffers from long query execution times due to a comprehensive Relative Date filter:
– Relative Date Filter Issue: The existing Relative Date filter on "Created Date" covers a broad range (5 years), leading to significant data processing overhead as it includes granular date calculations over a large dataset.
– Optimized Approach: By replacing the Relative Date filter with a Multiple Values (Dropdown) filter based on YEAR ([Created Date]), the filter granularity is reduced. Filtering by year simplifies the query by limiting the volume of data processed and reducing the complexity of the filter condition.
– Implementation Benefit: This approach still provides the flexibility to view data across different years but does so by reducing the load on the database during query execution, which is critical for improving the performance of the dashboard.
References: This recommendation aligns with Tableau performance optimization strategies, specifically regarding the management of date filters to minimize their impact on query load, as discussed in Tableau performance tuning sessions and guides.
A client wants to see data for only the last day in a dataset and the last day is always yesterday. The date is represented with the field Ship Date.
The client is not concerned about the daily refresh results. The volume of data is so large that performance is their priority. In the future, the client will be able to move the calculation to the underlying database, but not at this time.
The solution should offer the best performance.
Which approach should the consultant use to produce the desired results?
- A . Filter MONTH/DAY/YEAR on [Ship Date] field and use an option to filter to the latest date value when the workbook opens.
- B . Filter on calculation [Ship Date] =TODAY ()-1.
- C . Filter on Ship Date field using the Yesterday option.
- D . Filter on calculation [Ship Date] = {MAX ([Ship Date])}.
B
Explanation
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 ()-1ensures 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.
A consultant migrated a data source to improve performance. The consultant wants to identify which workbooks need to be updated to point to the new data source.
Which Tableau tool should the consultant use?
- A . Data Management
- B . Prep Conductor
- C . Activity Log
- D . Tableau Advanced Management
D
Explanation
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.
From the desktop, open the CC workbook.
Open the City Pareto worksheet.
You need to complete the Pareto chart to show the percentage of sales compared to the percentage of cities. The chart must show references lines to visualize how the data compares to the Pareto principle.
From the File menu in Tableau Desktop, click Save.
– Open the CC Workbook and Access the Worksheet:
– From the desktop, double-click on the CC workbook to open it in Tableau Desktop.
– Navigate to the City Pareto worksheet by selecting its tab at the bottom of the window.
– Construct the Pareto Chart:
– Ensure that sales data is aggregated by city. If not, drag the ‘City’ dimension to the Columns shelf and the ‘Sales’ measure to the Rows shelf.
– Sort the sales data in descending order to properly align the cities according to their sales contribution.
– To create a running total of sales, right-click on the ‘Sales’ measure on the Rows shelf, select ‘Quick Table Calculation’, and choose ‘Running Total’.
– Drag the ‘Number of Records’ field to the Rows shelf next to the Sales running total. Right-click on it, select ‘Quick Table Calculation’, and choose ‘Running Total’. Set its calculation to ‘Percent of Total’ from the ‘Edit Table Calculation’ option to represent the percentage of cities.
– Add Reference Lines for the Pareto Principle:
– Click on the Analytics tab in the sidebar.
– Drag a ‘Reference Line’ element and drop it onto the chart area.
– Set the Reference Line for the Sales axis at 80% to represent the typical Pareto cutoff where 80% of effects come from 20% of causes.
– Add another Reference Line on the axis representing the percentage of cities, set at 20%, to visually assess the Pareto principle.
– Adjust the Appearance of the Chart:
– Format the reference lines by right-clicking on them, selecting ‘Edit’, and choosing a distinct style or color to make them stand out.
– Ensure the chart is clear and labels are appropriately adjusted for easy understanding of the data visualization.
– Save Your Changes:
– From the File menu, click ‘Save’ to ensure all your changes are stored.
References:
Tableau Help: Offers detailed guidance on creating Pareto charts and adding reference lines.
Tableau Visualization Best Practices: Provides tips on effectively displaying cumulative data and principles such as Pareto.
By following these steps, you will have successfully enhanced the City Pareto worksheet to include a complete Pareto chart with reference lines that illustrate how the sales data compares to the Pareto principle, making it easier to analyze and communicate the distribution of sales across cities.
A consultant builds a report where profit margin is calculated as SUM([Profit]) / SUM([Sales]). Three groups of users are organized on Tableau Server with the following levels of data access that they can be granted.
– Group 1: Viewers who cannot see any information on profitability
– Group 2: Viewers who can see profit and profit margin
– Group 3: Viewers who can see profit margin but not the value of profit
Which approach should the consultant use to provide the required level of access?
- A . Use user filters to access data on profitability to all groups. Then, create a calculated field that allows visibility of profit value to Group 2 and use the calculation in the view in the report.
- B . Specify in the row-level security (RLS) entitlement table individuals who can see profit, profit margin, or none of these. Then, use the table data to create user filters in the report.
- C . Use user filters to allow only Groups 2 and 3 access to data on profitability. Then, create a calculated field that limits visibility of profit value to Group 2 and use the calculation in the view in the report.
- D . Specify with user filters in each view individuals who can see profit, profit margin, or none of these.
C
Explanation
The approach of using user filters to control access to data on profitability for Groups 2 and 3, combined with a calculated field that restricts the visibility of profit value to only Group 2, aligns with Tableau’s best practices for managing content permissions. This method ensures that each group sees only the data they are permitted to view, with Group 1 not seeing any profitability information, Group 2 seeing both profit and profit margin, and Group 3 seeing only the profit margin without the actual profit values. This setup can be achieved through Tableau Server’s permission capabilities, which allow for detailed control over what each user or group can see and interact with12.
References: The solution is based on the capabilities and permission rules that are part of Tableau Server’s security model, as detailed in the official Tableau documentation12. These resources provide guidance on how to set up user filters and calculated fields to manage data access levels effectively.