Salesforce Certified Tableau Data Analyst Analytics-DA-201 Exam Questions

Answer : D

Answer : B, D, F

In Tableau, the RANK function assigns a rank to each row within a partition of the data, based on the value of the field being ranked. It is important to understand that the rank is recalculated whenever the underlying data or the partitioning changes.

In the given scenario, the Overall Rank is based on the Sales figures, while the Rank (presumably) is based on the Sales within the Category. When filtering on the condition where [Overall Rank] - 1, it means we are excluding the sub-category that has an Overall Rank of 2.

Looking at the data:

Furnishings has an Overall Rank of 8, which does not meet the filter condition ([Overall Rank] - 1). Therefore, its rank remains the same.

Tables have an Overall Rank of 3. When the sub-category with an Overall Rank of 2 is removed (Chairs in this case), Tables move up in the overall ranking. However, since Tables are the top-ranked within the Furniture category, their Rank within the category would remain unchanged at 1.

Chairs have an Overall Rank of 2, which meets the filter condition and thus will be removed from the view. We cannot determine the change in Rank for Chairs because they are filtered out.

Accessories have an Overall Rank of 5. If any sub-category with a higher Overall Rank (1 to 4) is removed, the rank of Accessories within the Technology category could change because it is currently ranked 3 in its category. With the removal of Phones (Overall Rank 1), the Rank of Accessories could potentially increase.

Copiers have an Overall Rank of 6, which does not meet the filter condition. Therefore, its rank remains the same.

Machines have an Overall Rank of 4. If we remove Phones (Overall Rank 1), Machines will move up in the overall ranking and potentially within the Technology category as well, changing its Rank from 2 to 1.

Phones have an Overall Rank of 1, which does not meet the filter condition of being Overall Rank 2. Therefore, its rank remains the same.

Bookcases have an Overall Rank of 7, which does not meet the filter condition. Therefore, its rank remains the same.

Based on this analysis, when the sub-category with an Overall Rank of 2 (Chairs) is removed, the Rank value will change for Tables, Accessories, and Machines, as they will move up in the overall ranking within their respective categories. However, it's important to note that while Tables will move up in the overall ranking, their rank within the Furniture category would not change as they are already at the top. The rank changes for Accessories and Machines are due to the removal of Phones, which is ranked higher overall and within the Technology category.

Answer : A, D

To schedule a refresh of the data, you need to ensure that Tableau Server or Tableau Online can access the database without prompting for credentials. This can be done by embedding the credentials in the workbook or the published data source. You also need to extract the data from the database and publish it as a separate data source or as part of the workbook. A live connection would not allow you to refresh the data on a schedule, as it would always query the database directly. A hyper file is a format for storing extracted data, but it is not a requirement for scheduling a refresh.Reference:

Tableau Certified Data Analyst Exam Prep Guide, page 10, section ''Publishing and Scheduling Data Refreshes''

Tableau Help: Embedding Database Credentials

Tableau Help: Extract Your Data

Answer : B

To get the number of different types of awards that have been won, you should use the formula COUNTD({Award}). This formula will return the count of distinct values in the Award field, which are the different types of awards that have been won.

The other options are not correct for this scenario. COVAR({Award}) is not a valid function in Tableau. MAX({Award}) will return the maximum value in the Award field, which may not be a type of award. INDEX() will return the index or rank of each row in a partition, which is not related to the types of awards. Reference: https://help.tableau.com/current/pro/desktop/en-us/functions_functions_aggregate.htm#COUNTD https://help.tableau.com/current/pro/desktop/en-us/functions_functions_tablecalculation.htm#INDEX

The COUNTD function in Tableau calculates the number of distinct (unique) items in a field. When looking to get the number of different types of awards that have been won, the COUNTD([Award]) function will count each unique award name only once, regardless of how many times it appears in the dataset. This will return the total number of unique award types.

Answer : A

To create a histogram on the Quantity field by using bin size of 3, you need to do the following steps:

Open the link to Book1 found on the desktop. This will open the Tableau workbook that uses the Superstore data source.

Click on the Histogram tab at the bottom of the workbook to open the Histogram worksheet. You will see a blank worksheet with no marks.

Right-click on Quantity in the Measures pane and select Create Bins from the menu. This will open a dialog box that allows you to create bins for the Quantity field. Bins are groups of values that are treated as one unit in a histogram.

Enter 3 in the Size of bins text box. This will set the bin size to 3, which means that each bin will contain values that are 3 units apart. For example, one bin will contain values from 0 to 2, another bin will contain values from 3 to 5, and so on.

Click OK to create the bins. You will see a new field named Quantity (bin) in the Measures pane with a # sign next to it.

Drag Quantity (bin) from the Measures pane to Columns on the worksheet. This will create a histogram that shows the distribution of Quantity by bins. You will see bars that represent the frequency or count of values in each bin.

Optionally, you can adjust the width, color, and labels of the bars by using the options on the Marks card. You can also add filters, tooltips, or annotations to enhance your histogram.

Answer : B

Answer : A

To combine the two tables that contain data about books in a library and ensure that all the data is retained, you should use a full outer join. A full outer join is a type of join that returns all rows from both tables, regardless of whether there is a match or not. If there is no match, null values are filled in for the missing fields.

To perform a full outer join, you need to do the following steps:

Connect to both tables as your data sources in Tableau. You can use either live or extract connections.

Drag one table to the canvas and drop it on top of another table. This will create a join between them based on a common field.

Click on the join icon between the tables and select Full Outer Join from the drop-down list. This will change the join type to full outer join and show all rows from both tables.

Optionally, you can add or remove join clauses by clicking on Add or Remove buttons next to each clause. You can also change or rename fields by clicking on them.

The other types of joins are not correct for this scenario. An inner join returns only the rows that have a match in both tables, which will exclude any books that are missing from either table. A left join returns all rows from the left table and only the matching rows from the right table, which will exclude any books that are only in the right table. A right join returns all rows from the right table and only the matching rows from the left table, which will exclude any books that are only in the left table. Reference: https://help.tableau.com/current/pro/desktop/en-us/joining_tables.htm https://help.tableau.com/current/pro/desktop/en-us/join_types.htm

When combining two datasets that are both incomplete and where it's important to retain all data from both sources, a full outer join is appropriate. This type of join ensures that all records from both tables are included in the combined dataset, even if there are no matching records in the other table.