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Tableau Certified Consultant Sample Questions (Q45-Q50):

NEW QUESTION # 45
A client wants guidance for Creators to build efficient extracts from large data sources.
What are three Tableau best practices that the Creators should use? Choose three.

A. Include all the data from the original data source in the extract.
B. Keep only the data required for analysis by using extract filters.
C. Hide all unused fields.
D. Use aggregate data for visible dimensions, whenever possible.
E. Use only live connections as they are always faster than extracts.

Answer: B,C,D

Explanation:
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.

NEW QUESTION # 46
A client has a database that stores widget inventory by day and it is updated on a nonstandard schedule as shown below.

They want a data visualization that shows widget inventory daily, however their business unit does not have the ability to modify the data warehouse structure.
What should the client do to achieve the desired result?

A. Create a temporary table in the database.
B. Use Tableau Desktop to visualize null values.
C. Use Tableau Prep to add new rows.
D. Update the Widget Inventory Table to be a daily snapshot.

Answer: C

Explanation:
For a client who needs a daily visualization of widget inventory but cannot modify the data warehouse structure, the best approach is to use Tableau Prep to add new rows. Tableau Prep can be used to manipulate the existing dataset by adding missing date entries and appropriately adjusting inventory counts based on available data. This allows the creation of a complete daily snapshot for visualization without needing changes to the underlying database structure.

NEW QUESTION # 47
A client wants to produce a visualization to show quarterly profit growth and aggregated sales totals across a number of product categories from the data provided below.

Which set of charts should the consultant use to meet the client's requirements?

A. Line and bubble charts
B. Waterfall chart and tree map
C. Scatter plot and pie chart
D. Gantt and bar charts

Answer: B

Explanation:
To effectively display quarterly profit growth and aggregated sales totals across different product categories, a combination of a Waterfall chart and a Tree Map is recommended:
* Waterfall Chart: This chart type is excellent for visualizing the sequential growth or decline of profits across different quarters for each sub-category. It clearly shows how profits accumulate over time, highlighting both positive and negative changes, which makes it ideal for tracking profit growth or decline through the quarters.
* Tree Map: A Tree Map can efficiently display aggregated sales totals where each block size represents the total sales of a product category, providing a quick, visually impactful comparison across categories.
This is especially useful when the client wants to understand which categories contribute most to sales in a glanceable format.
Together, these charts provide a comprehensive overview of both profit trends over time (Waterfall Chart) and a comparative snapshot of sales performance across categories (Tree Map), meeting the client's need to analyze performance dynamics in a detailed yet consolidated manner.
ReferencesThese recommendations are based on common best practices for data visualization in Tableau, where specific chart types are chosen for their strengths in communicating certain types of data relationships and dynamics, as detailed in Tableau's official visualization guides.

NEW QUESTION # 48
A client wants to flag orders that have sales higher than the regional average.
Which calculated field will produce the required result?

A. { FIXED [Order ID] : SUM([Sales]) }
>
{ FIXED [Region] : AVG({ FIXED [Order ID] : SUM([Sales]) }) }
B. { FIXED [Order ID] : SUM([Sales]) }
>
{ INCLUDE [Region] : AVG({ FIXED [Order ID] : SUM([Sales]) }) }
C. [Sales]
>
{ FIXED [Order ID] : SUM([Sales]) }
D. { FIXED [Order ID] : SUM([Sales]) }
>
{ FIXED [Region] : SUM([Sales]) }

Answer: A

Explanation:
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.
ReferencesThis 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.

NEW QUESTION # 49
A company has a data source for sales transactions. The data source has the following characteristics:
. Millions of transactions occur weekly.
. The transactions are added nightly.
. Incorrect transactions are revised every week on Saturday.
The end users need to see up-to-date data daily.
A consultant needs to publish a data source in Tableau Server to ensure that all the transactions in the data source are available.
What should the consultant do to create and publish the data?

A. Publish a live connection to Tableau Server.
B. Publish an incremental extract refresh every day and publish a secondary data set containing data revisions.
C. Publish an incremental extract refresh every day and perform a full extract refresh every Saturday.
D. Publish an incremental refresh every Saturday.

Answer: C

Explanation:
Given the need for up-to-date data on a daily basis and weekly revisions, the best approach is to use an incremental extract refresh daily to update the data source with new transactions. On Saturdays, when incorrect transactions are revised, a full extract refresh should be performed to incorporate all revisions and ensure the data's accuracy.This strategy allows end users to have access to the most current data throughout the week while also accounting for any necessary corrections12.
References:The solution is based on best practices for managing data sources in Tableau Server, which recommend using incremental refreshes for frequent updates and full refreshes when significant changes or corrections are made to the data12.

NEW QUESTION # 50
......

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