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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Connect and Prepare Data | 25% | - Data Connections
|
| Topic 2: Explore and Analyze Data | 35% | - Statistical Analysis
|
| Topic 3: Create Visualizations and Dashboards | 25% | - Visualization Development
|
| Topic 4: Data Governance and Security | 15% | - Security and Ethics
|
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NEW QUESTION # 184
You have the following dataset in Microsoft Excel.
You are using Data interpreter to cleans the dataset. Data interpreter provides the following results.
How many rows of data will be ingested into Tableau as values?
Answer: D
Explanation:
Data interpreter is a feature that helps you clean and structure your data in Excel before importing it into Tableau. It detects and removes any headers, footers, subtotals, or other elements that are not part of the actual data. It also splits any merged cells and fills in any missing values. In this case, data interpreter provides the following results:
* It removes the first three rows and the last two rows that contain headers and footers.
* It splits the merged cells in column A and fills in the missing values with "Fiction" or "Non-Fiction".
* It does not remove or change any other rows or cells.
Therefore, the number of rows of data that will be ingested into Tableau as values is 17, which is the number of rows left after removing the headers and footers. References: https://help.tableau.com/current/pro/desktop
/en-us/importing_cleaning_up_data.htm https://help.tableau.com/current/pro/desktop/en-us
/importing_data_interpreter.htm
Based on the Data Interpreter ' s results and the provided Excel dataset screenshot, the number of rows of data that will be ingested into Tableau as values is 17. The Data Interpreter has identified and excluded headers and footers, and the rows with actual data are considered for analysis.
NEW QUESTION # 185
You are developing a data source in Tableau Prep.
You have two tables named Orders and Employees.
The Orders table was created in 2019 and contains the following columns.
The Employees table contains all the employee information for the various sales teams in the sales department and contains the following columns
You want to prepare the data so that you can analyze sales trends over time for every sales team.
Which three actions should you perform in order? (Place the three correct options in order. Use the arrows to move Options to Answer Area. Use Answer Area arrows to re-order the options.)
Answer:
Explanation:
Explanation:
There are different ways to prepare the data in Tableau Prep, but one possible answer is:
Answer area:
* Join the tables.
* Aggregate the data by Sales Team.
* Add the following filter to the Employees table: Sale Team - Team Alpha.
To analyze sales trends over time for every sales team, you need to combine the data from the Orders and Employees tables. You can do this by joining the tables on the Rep ID column, which is a common identifier for both tables. This will create a single table with all the columns from both tables. Next, you need to aggregate the data by Sales Team, which is the level of analysis you want. You can do this by grouping the data by the Sales Team column and applying an aggregation function (such as sum, average, count, etc.) to the other columns that you want to measure (such as Total Amount, Rep Tenure, etc.). This will create a summary table with one row for each sales team and the aggregated values for the other columns. Finally, you need to filter the data to focus on a specific sales team, such as Team Alpha. You can do this by adding a filter to the Employees table and selecting only the rows where Sales Team equals Team Alpha. This will remove the rows for other sales teams and keep only the data for Team Alpha.
References:
[Tableau Certified Data Analyst Exam Prep Guide], page 9, section "Preparing Data"
[Tableau Help: Join Your Data]
[Tableau Help: Aggregate Your Data]
[Tableau Help: Filter Your Data]
NEW QUESTION # 186
You receive a tab-delimited data file name sales.tsv.
You need to connect to the file.
Which option should you select in Tableau Desktop?
Answer:
Explanation:
Explanation:
To connect to a tab-delimited data file named sales.tsv, you should select the option To a File > Text file in Tableau Desktop. This option will allow you to browse and select the file from your local or network drive and connect to it as a data source. You can then specify the text file properties, such as the delimiter, the text qualifier, and whether the first row contains column names. You can also join, union, or blend the data with other data sources if needed. References:
* Text File - Tableau
* Tableau Certified Data Analyst Study Guide
NEW QUESTION # 187
You have the following primary data source that contains a dimension named Dorm_Code.
You receive the following secondary data source that contains updated dorm codes.
You need to bring the updated dorm codes into Tableau and use the codes in existing visualizations. The new dorm codes must use the existing field name of Dorm_Code.
What should you do?
Answer: D
Explanation:
* Using relationships: You can use relationships to link the secondary data source with the primary data source based on a common field. This will allow you to use fields from both data sources in your visualization without creating new fields or duplicating data. You can then replace references to update the dimension values. For example, you can use relationships to link the updated dorm codes with the primary data source and then replace Dorm_Code with Dorm_Code_New in your visualization.
https://community.tableau.com/s/question/0D54T00000C5ldZSAR/update-data-view-based-on-dimension To update existing visualizations with new codes without changing the field name, using relationships to bring in the secondary data source is appropriate. Then using Replace References allows you to update the references from the old dorm codes to the new ones while maintaining the existing field name.
NEW QUESTION # 188
A Data Analyst has the following chart that shows the number of song downloads per year since the release of the song.
The required result is a cumulative progression of downloads across the years.
Which quick table calculation should the analyst use?
Answer: C
Explanation:
A Running Total accumulates the measure sequentially across the addressing dimension. With Year on Columns and SUM(Downloads) in the view, Tableau starts with the first year ' s downloads and progressively adds each subsequent year ' s value to the accumulated total. The resulting bars therefore represent all downloads received up to each year since release rather than the downloads for that individual year alone.
YTD Total is intended for accumulation within a calendar year and commonly restarts with the new year.
Percent of Total expresses each value as a proportion of the full partition, while Year Over Year Growth compares the relative change between consecutive annual values. Tableau lists Running Total as a standard quick table calculation specifically for cumulative analysis. Therefore, B is the appropriate calculation.
NEW QUESTION # 189
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