Latest TDS-C01 Practice Tests with Actual Questions

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Exam Code : TDS-C01
Exam Name : Tableau Desktop Specialist
Vendor Name : "Tableau"

Reference: https://www.w3schools.com/sql/sql_join_left.asp

Question: 53

You can use the in Tableau to clean / organise your data.

1. Data cleaner

2. Data manager

3. Data interpreter

4. Data organiser

Answer: C
Explanation:

When you track data in Excel spreadsheets, you create them with the human interface in mind. To make your spreadsheets easy to read, you might include things like titles, stacked headers, notes, maybe empty rows and columns

to add white space, and you probably have multiple tabs of data too. When you want to analyze this data in Tableau, these aesthetically pleasing attributes make it very difficult for Tableau to interpret your data. That’s where Data Interpreter can help.

Reference: https://help.tableau.com/current/pro/desktop/en-us/data_interpreter.htm

Question: 54

is a snapshot of the data that Tableau stores locally. Good for very large datasets of which we only need few fields.

1. Tableau Packaged Workbook (.twbx)

2. Tableau Workbook (.twb)

3. Tableau Data Extract (.tde)

4. Tableau Data Source (.tds)

Answer: C
Explanation:

Tableau Data Extract (TDE) is a snapshot of the data that Tableau stores locally. Good for very large datasets of which we only need few fields. Performance is optimised because it queries its own database engine instead of the local data source. When you create an extract of your data, you can reduce the total amount of data by using filters and configuring other limits. After you create an extract, you can refresh it with data from the original data. When refreshing the data, you have the option to either do a full refresh, which replaces all of the contents in the extract, or you can do an incremental refresh, which only adds rows that are new since the previous refresh.

Extracts are advantageous for several reasons:

1. Supports large data sets: You can create extracts that contain billions of rows of data.

2. Fast to create: If you’re working with large data sets, creating and working with extracts can be faster than working with the original data.

   
   

3. Help improve performance: When you interact with views that use extract data sources, you generally experience better performance than when interacting with views based on connections to the original data.

   
   

4. Support additional functionality: Extracts allow you to take advantage of Tableau functionality that’s not available or supported by the original data, such as the ability to compute Count Distinct.

   
   

5. Provide offline access to your data: Extracts allow you to save and work with the data locally when the original data is not available. For example, when you are traveling.

Question: 55

According to Tableau’s ‘Order of Operations’, which of the following filters is applied FIRST?

1. Dimension Filter

2. Measure Filter

3. Context Filter

4. Extract Filter

Answer: D
Explanation:

According to Tableau’s order of operations, the Extract filter is right at the top of the hierarchy. The data filtered in the Extract is then passed on to what we see in the Data Pane. See below:

Reference: https://help.tableau.com/current/pro/desktop/en-us/order_of_operations.htm

Question: 56

When using Animations in a Tableau, which of the following is the default duration for animations?

1. 0.4s

2. 0.3s

3. 0.5s

4. 0.2s

Answer: B
Explanation:

The LATEST Tableau Desktop Sepcialist exam blueprint now requires you to know some basics about animations as well!

NOTE: Animations are DISABLED by default and must be manually enabled.

You can also reset all settings to default by clickin on ‘Reset All’ Reference: https://help.tableau.com/current/pro/desktop/en-us/formatting_animations.htm

Question: 57

Which of the following is a benefit of using a Tableau Data Source (.tds)?

1. To hold one or more worksheets, plus zero or more dashboards and stories.

2. To not contain the actual data but rather the information necessary to connect to the actual data as well as any modifications you’ve made on top of the actual data such as changing default properties, creating calculated fields etc

3. To create a single zip file that contains a workbook along with any supporting local file data and background images. This is great for sharing your work with others who don’t have access to the original data.

4. To create a local copy of a subset or entire data set that you can use to share data with others, when you need to work offline, and improve performance.

Answer: B
Explanation:

The following are the official definitions from the Tableau documentation for the various file types:

1). tds (Tableau Data Source) – To not contain the actual data but rather the information necessary to connect to the actual data as well as any modifications you’ve made on top of the actual data such as changing default properties, creating calculated fields etc. (CORRECT ANSWER)

2). twbx (Tableau packaged workbook) – To create a single zip file that contains a workbook along with any supporting local file data and background images. This is great for sharing your work with others who don’t have access to the original data.

3) Extract (. hyper or .tde) C To create a local copy of a subset or entire data set that you can use to share data with others, when you need to work offline, and improve performance.

3) (.twb) Workbooks C To hold one or more worksheets, plus zero or more dashboards and stories. Reference: https://help.tableau.com/current/pro/desktop/en-us/environ_filesandfolders.htm
Question: 58

Larger image

What is this entire view referred to as in Tableau?

1. Data pane

2. Analytics Pane

3. Summary Pane

4. Distribution Pane

Answer: B
Explanation: Distribution Pane

This is the Analytics pane! Read more from the official documentation below:

Reference: https://help.tableau.com/current/pro/desktop/enus/environ_workspace_analytics_pane.htm

Question: 59

True or False: Bins can be created on dimensions

1. False

2. rue

Answer: B
Explanation:

Explanation Bin are a user-defined grouping of numerical data in the data source.

According to the official Tableau documentation: It’s sometimes useful to convert a continuous measure (or a numeric dimension) into bins. Have a look at the following image. When we right click a measure, we get the following options:

However, for a dimension (this is because the DATA TYPE of this dimension is a string:

But what if we have a dimension of type NUMBER (NUMERIC DIMENSION)? See below:

We can clearly create bins from dimensions too – they just have to be numeric

For more information, please refer to: https://help.tableau.com/current/pro/desktop/enus/calculations_bins.htm

Question: 60

Using the dataset, create a bar chart showing the average Quantity broken down by Region, and filtered by Country to only show Japan.

What was the average Quantity in the State of Tokyo? A. 3.000

B. 3.840

C. 3.704

D. 3.500

Answer: C
Explanation:

Explanation Since we need to focus on 1 country -> Japan, let’s filter on it first as follows:

1. Drag Country to the filter shelf, and choose only Japan. Click OK.

   
   

   
   

2. Read the Question Carefully, we need to break down the visualisation by Region, then by Country, and then by State. So let’s do that: Drag Region to the column shelf, followed by Country. Drill down into Country to include states as well. Then drag Quantity to the Row Shelf, and change the Aggregation to AVERAGE.

The following is our visualisation:

Now that you think of it, EVEN IF YOU REMOVE THE REGION, THE ANSWER REMAINS THE SAME. Such

elements will be present in the actual exam too, just to make the question sound a little difficult, but actually it is pretty straightforward