TABLEAU TCC-C01 NEW BRAINDUMPS SHEET & TCC-C01 CERT GUIDE

Tableau TCC-C01 New Braindumps Sheet & TCC-C01 Cert Guide

Tableau TCC-C01 New Braindumps Sheet & TCC-C01 Cert Guide

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Tableau Certified Consultant Sample Questions (Q50-Q55):

NEW QUESTION # 50
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 on calculation [Ship Date]=TODAY()-1.
  • B. Filter MONTH/DAY/YEAR on [Ship Date] field and use an option to filter to the latest date value when the workbook opens.
  • C. Filter on calculation [Ship Date]={MAX([Ship Date])}.
  • D. Filter on Ship Date field using the Yesterday option.

Answer: A

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 ofTODAY()-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.
ReferencesThis 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.


NEW QUESTION # 51
A client uses Tableau Data Management and notices that when they view a data source, they sometimes see a different count of workbooks in the Connected Workbooks tab compared to the lineage count in Tableau Catalog.
What is the cause of this discrepancy?

  • A. Some workbooks have been connected to the data source, but do not use any fields from it.
  • B. Some workbooks have not been viewed by enough users yet.
  • C. Some Creators have connected to the data source in Tableau Desktop but have not yet published a workbook.
  • D. Some of the workbooks connected to the data source are not visible to the user due to permissions.

Answer: D

Explanation:
The discrepancy between the count of workbooks in the Connected Workbooks tab and the lineage count in Tableau Catalog can occur because of user permissions. In Tableau Data Management, the visibility of connected workbooks is subject to the permissions set by administrators. If a user does not have permission to view certain workbooks, they will not see them listed in the Connected Workbooks tab, even though these workbooks are part of the data source's lineage and are counted in Tableau Catalog.
References:This explanation is based on the functionality of Tableau Data Management and Tableau Catalog, which includes managing user permissions and access to workbooks.The information is supported by Tableau's official documentation on data management and security practices1.


NEW QUESTION # 52
A client is working in Tableau Prep and has a field named Orderld that is compiled by country, year, and an order number as shown in the following table.

What should the consultant use to transform the table in the most efficient manner?

  • A. The Aliases option
  • B. A calculated field that uses the TRIM function
  • C. The Split option
  • D. A calculated field that uses the LEFT function

Answer: C

Explanation:
To transform theOrderldfield in Tableau Prep, the Split option is the most efficient and straightforward method. Here's how you can apply it:
* In Tableau Prep, drag your dataset into the flow.
* Click on theOrderldfield in the workspace to select it.
* Look for the option in the toolbar that says "Split" and select it.
* Choose "Automatic Split" if the delimiters (such as hyphens) are consistent; Tableau Prep should automatically detect the hyphen as the delimiter and split theOrderldinto multiple new fields.
* The dataset should now show new columns: one for the country code (CA, FR, US), one for the year (2017), and one for the order number (152156, 152157, etc.).
The Split option works effectively here because it automatically identifies and uses the hyphen as the delimiter to divide the originalOrderldinto the desired components without manual specification of conditions or writing any formulas.
ReferencesThis procedure is based on the standard functionalities provided in Tableau Prep for splitting a field into multiple columns based on a delimiter, as described in the Tableau Prep user guide.


NEW QUESTION # 53
A client has many published data sources in Tableau Server. The data sources use the same databases and tables. The client notices different departments give different answers to the same business questions, and the departments cannot trust the data. The client wants to know what causes data sources to return different data.
Which tool should the client use to identify this issue?

  • A. Ask Data
  • B. Tableau Catalog
  • C. Tableau Resource Monitoring Tool
  • D. Tableau Prep Conductor

Answer: B

Explanation:
The Tableau Catalog is part of the Tableau Data Management Add-on and is designed to help users understand the data they are using within Tableau. It provides a comprehensive view of all the data assets in Tableau Server or Tableau Online, including databases, tables, and fields. It can help identify issues such as data quality, data lineage, and impact analysis. In this case, where different departments are getting different answers to the same business questions, the Tableau Catalog can be used to track down inconsistencies and ensure that everyone is working from the same, reliable data source.
References:The recommendation for using Tableau Catalog is based on its features that support data discovery, quality, and governance, which are essential for resolving data inconsistencies across different departments12.
When different departments report different answers to the same business questions using the same databases and tables, the issue often lies in how data is being accessed and interpreted differently across departments.
Tableau Catalog, a part of Tableau Data Management, can be used to solve this problem:
* Visibility: Tableau Catalog gives visibility into the data used in Tableau, showing users where data comes from, where it's used, and who's using it.
* Consistency and Trust: It helps ensure consistency and trust in data by providing detailed metadata management that can highlight discrepancies in data usage or interpretation.
* Usage Metrics and Lineage: It offers tools for tracking usage metrics and understanding data lineage, which can help in identifying why different departments might see different results from the same underlying data.
References:
* Tableau Catalog Usage: The Catalog is instrumental in providing a detailed view of the data environment, allowing organizations to audit, track, and understand data discrepancies across different users and departments.


NEW QUESTION # 54
An online sales company has a table data source that contains Order Date. Products ship on the first day of each month for all orders from the previous month.
The consultant needs to know the average number of days that a customer must wait before a product is shipped.
Which calculation should the consultant use?

  • A. Calc1: DATETRUNC ('month', DATEADD ('month', 1, [Order Date]))
    Calc2: AVG(DATEDIFF ('day', [Order Date], [Calc1]))
  • B. Calc1: DATETRUNC ('day', DATEADD('week', 4, [Order Date]))
    Calc2: AVG([Order Date] - [Calc1])
  • C. Calc1: DATETRUNC ('day', DATEADD ('day', 31, [Order Date]))
    Calc2: AVG ([Order Date] - [Calc1])
  • D. Calc1: DATETRUNC ('month', DATEADD('month', 1, [Order Date]))
    Calc2: AVG(DATEDIFF ('week', [Order Date], [Calc1]))

Answer: A

Explanation:
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 usingDATETRUNC('month', DATEADD('month', 1, [Order Date])). Then, the average difference in days between the order date and the shipping date is calculated usingAVG(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.
References:The solution is based on Tableau's date functions and their use in calculating differences between dates, which are well-documented in Tableau's official learning resources and consultant documents12.
To calculate the average waiting days from order placement to shipping, where shipping occurs on the first day of the following month:
* Calculate Shipping Date (Calc1): Use the DATEADD function to add one month to the order date, then apply DATETRUNC to truncate this date to the first day of that month. This represents the shipping date for each order.
* Calculate Average Wait Time (Calc2): Use DATEDIFF to calculate the difference in days between the original order date and the calculated shipping date (Calc1). Then, use AVG to average these differences across all orders, giving the average number of days customers wait before their products are shipped.
References:
* Date Functions in Tableau: Functions like DATEADD, DATETRUNC, and DATEDIFF are used to manipulate and calculate differences between dates, crucial for creating metrics that depend on time intervals, such as customer wait times in this scenario.


NEW QUESTION # 55
......

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