Tableau TDS-C01 Dumps

Yes, due to the nature of blends, there are some conditions as follows from the official documentation that must be kept in mind while working with blends:

In addition to handling calculations slightly differently, there are some limitations on secondary data sources. You may not be able to sort by a field from a secondary data source, and action filters may not work as expected with blended data. For more information, see Other data blending issues.

When the Physical Tables option is selected for an extract in Tableau, an individual table is created for each physical table in the extract. This means that the extract will include a separate table for each underlying table in your database, maintaining the database's structure within the extract. This can be useful when you need to preserve the original granularity of the data or when working with certain database optimizations.

Explanation

As the question mentions, we need to create a SET with the following conditions -> Choose only those customers whose Sales > 30,000

1) Right click on customer name --> Create --> Set

2) Let's Name the Set - Customer>30k ( you can name it anything you want :) )

Select USE ALL, and then move to the CONDITION TAB:

3) In the Condition Tab, Choose BY FIELD -> Select Sales -> Sum -> Greater than 30000 , and click OK

4) You should now have a new Set in the Data Pane as follows:

5) Drag this set to the rows shelf, and click on SHOW MEMBERS IN SET. Now drag Sales to the Column Shelf.

6) Click on the Show Mark Labels, and Sort ascending icons as shown:

7) Voila! We have our answer:

c

Yes! We get different options for filtering depending on whether we use a categorical data (think dimension) or quantitative data (think measure).

Important Note: Each tab adds additional definitions to your filter. For example, you can select to exclude values under the General tab, and also add limits under the Top tab. Selections and configurations from both tabs are applied to your filter.At any time, you can see the definitions of your filter under Summary on the General tab.

Note: If you have a large data source, filtering measures can lead to a significant degradation in performance. It is sometimes much more efficient to filter by creating a set containing the measure and then apply a filter to the set. For more information about creating sets, see Create Sets

There are three benefits of using an extract as compared to a live connection to a data source:

A live connection to a data source can be slow due to network and user traffic, whereas a connection to an extract improves performance. An extract is a snapshot of data that is stored locally on your computer or on Tableau Server. An extract can reduce the load on the data source and speed up queries.

Extracts are stored in memory (RAM), resulting in faster query performance as compared with live data connections. When you use an extract, Tableau loads the data into memory and optimizes it for analysis. This allows Tableau to perform calculations and aggregations faster than with live connections.

Calculated fields perform better in workbooks connected to extracts than in workbooks with live connections to a data source. Calculated fields are custom fields that you create using formulas or expressions. When you use an extract, Tableau can process calculated fields more efficiently than with live connections.

Explanation

Relative date filters dynamically update to show a time period relative to when you open the view, such as the current week, the year to date, or the past 10 days. Relative date filters make it easy to create views that always show the most recent data.

Step 1: Drag a date field to the filter shelf

Right-click (control-click on Mac) and drag a date field from the Data window to the Filters shelf. In the Filter Field dialog box, click Relative Date, and then click Next.

Step 2: Select a time unit

In the Filter dialog box, click Relative dates, and then select the unit of time for the filter. For example, to show only the three most recent weeks, select Weeks.

Here, you can clearly see that the default date is TODAY

Explanation

This is true, indeed!

The LEFT JOIN keyword returns all records from the left table (table1), and the matched records from the right table (table2). The result is NULL from the right side, if there is no match.

When we create a reference line, we get the following 3 options for the scope:

Important question!

Explanation

Tableau displays data source connections and data fields for the workbook in the Data pane on the left side of the workspace.

The Data pane includes:

Dimension fields – Fields that contain qualitative values (such as names, dates, or geographical data). You can use dimensions to categorize, segment, and reveal the details in your data. Dimensions affect the level of detail in the view. Examples of dimensions include dates, customer names, and customer segments.

Measure fields – Fields that contain numeric, quantitative values can be measured. You can apply calculations to them and aggregate them. When you drag a measure into the view, Tableau applies an aggregation to that measure (by default). Examples of measures: sales, profit, number of employees, temperature, frequency.

For more information on what dimensions and measures are, see Dimensions and Measures, Blue and Green.

Calculated fields – If your underlying data doesn't include all of the fields you need to answer your questions, you can create new fields in Tableau using calculations and then save them as part of your data source. These fields are called calculated fields.

For more information on calculated fields, see Create Custom Fields with Calculations.

Sets – Subsets of data that you define. Sets are custom fields based on existing dimensions and criteria that you specify. For more information, see Create Sets.

Named sets from an MS Analysis Services server or from a Teradata OLAP connector also appear in Tableau in this area of the Data pane. You can interact with these named sets in the same way you interact with other custom sets in Tableau.

Parameters – Values that can be used as placeholders in formulas, or replace constant values in calculated fields and filters. For more information, see Create Parameters.

To assign a color to marks in the view, do the following:

From the Data pane, drag a field to Color on the Marks card.

Tableau applies different colors to marks based on the field’s values and members. For example, if you drop a discrete field (a blue field), such as Category, on Color, the marks in the view are broken out by category, and each category is assigned a color.

If you drop a continuous field, such as SUM(sales), on Color, each mark in the view is colored based on its sales value.

Explanation

Whenever we want to add actions to a Dashboard, we can trigger then in the following 3 ways:

1) Select

2) Hover

3) Menu

Hover is best for highlighting, select for filtering. Menu action is added to the tooltip and user can decide whether to run that action or not (best for URL actions)

Measure names and values CANNOT be deleted in Tableau like other columns can. These are auto-generated.

Calculated Fields, and Number of records can both be deleted.

In Tableau, when you initially add a measure to the rows shelf, you create one mark in the view that represents the aggregate value of that measure. When you then add a dimension with 11 members to the columns shelf, the view is subdivided into 11 separate marks, each representing the measure for one of the dimension members. This results in a total of 11 marks in the view after the dimension is added, one for each member of the dimension.

Explanation

Cluster analysis partitions marks in the view into clusters, where the marks within each cluster are more similar to one another than they are to marks in other clusters.

Explanation

The INNER JOIN keyword selects all rows from both tables as long as there is a match between the columns. Consider 2 tables "Orders" and "Customers".

If there are records in the "Orders" table that do not have matches in "Customers", these orders will not be shown!

Explanation

Here's how to add image files to your repository:

1) Find image file on the internet. I try to find consistent image formats if I plan to use a set of shapes such as logos or flags.

2) Download the image to your computer.

3) Drag images into your My Documents -> My Tableau repository -> Shapes folder.

4) Open Tableau and your new shapes will automatically be included in your "edit shapes" menu.

Explanation

Yes, it is possible to create worksheet-specific filters in Tableau.

When you add a filter to a worksheet, by default it applies to the current worksheet. Sometimes, however, you might want to apply the filter to other worksheets in the workbook.

Then, you can select specific worksheets to apply the filter to or apply it globally to all worksheets that use the same data source or related data sources.

Explanation

When you connect to a new data source, Tableau assigns each field in the data source as dimension or measure in the Data pane, depending on the type of data the field contains. You use these fields to build views of your data.

Date values in Tableau represent specific points in time and are typically formatted in a standard date format.

Option A, "2020-05-01", is a standard date format representing the 1st of May, 2020.

Option D, "January 1, 1995", is another example of a date value, representing the 1st of January, 1995. Options B ("December") and C ("Wednesday") represent a month and a day of the week, respectively, but do not specify a particular date.

Explanation

Remember that joins are defined in the physical layer and relationships in the logical layer.

You can still specify joins between tables in the physical layer of a data source. Double-click a logical table to go to the Join/Union canvas in the physical layer and add joins or unions.

Every top-level, logical table contains at least one physical table. Open a logical table to view, edit, or create joins between its physical tables. Right-click a logical table, and then click Open. Or, just double-click the table to open it.

When you create a data source, it has two layers. The top-level layer is the logical layer of the data source. You combine data between tables in the logical layer using relationships.

The next layer is the physical layer of the data source. You combine data between tables at the physical layer using joins. For more information, see Logical and physical tables in the data model

A URL action is a hyperlink that points to a web page, file, or other web-based resource outside of Tableau. You can use URL actions to create an email or link to additional information about your data. To customize links based on your data, you can automatically enter field values as parameters in URLs.

Explanation

After making changes to Data, we can save that new data source as a .tds file. To do so, go to data menu on top and then choose your current connected data source. Then next click on Add to Saved Data sources. This will save all calculated fields, changes to fields etc. It will be saved in My Tableau Repository -> Mydatasources. This will then also appear on Tableau Home Page under saved data sources like SampleSuperStore.

Note: Data source files do 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, adding groups, and so on.

twb and .twbx are not the BEST solutions since the questions nowhere mentions that we need to store our workbooks as well.

twm is a bookmark which contains a single worksheet and are an easy way to quickly share your work.

To visually group marks in Tableau, you typically start by selecting the marks directly in the view. Once the desired marks are selected, you can then create a group from them. This will visually group the selected marks, as indicated by the blue color in the example provided.

Explanation

To reach the correct answer, follow these steps:

1) Drag Order Date (Discrete Year) to the Column shelf, and Region to the Row Shelf as shown:

2) Drag Profit to Text in the Marks Shelf as shown:

3) Click on Analysis as shown -> Totals -> SELECT ROW GRAND TOTALS

The following will be the final view:

You could also Filter by Region to only Focus on Canada, but that's your choice:

THEREFORE,

2012 = 4,888

2011 -> 2014 = 17,817

The two types of aggregations that can be applied to string fields in Tableau are Count Distinct and Minimum. Count Distinct counts the unique values of a field, and Minimum finds the smallest value in a field based on the alphanumeric order. String fields do not support numeric aggregations like Sum or Average.

To provide additional information when hovering over a field in the Data pane, as shown in the exhibit, you need to configure a default comment for the field. This comment can be set by right-clicking on the field in the Data pane and selecting "Default Properties" and then "Comment." The text entered as a comment here will then be displayed as a tooltip when hovering over the field in the Data pane.

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.

According to the Tableau Help, headers are “labels that identify the different parts of your view”. The help also states that “Headers are created when you place a discrete dimension on Columns or Rows” (page 1).

This is a tricky question. We are talking about story POINTS, and not entire stories in the question.

To create a story, lets say I have a blank story with 1 dashboard and 1 worksheet.

I can simply drag the dashboard into the view to create a new story point.

Now, if I try to adjust the worksheet beside it in this same view, I cannot. See below:

The only option available is to replace the existing view. Therefore, the answer is NO since they both cannot be added.

Read more about stories in Tableau:

Explanation

Line charts connect individual data points in a view. They provide a simple way to visualize a sequence of values and are useful when you want to see trends over time, or to forecast future values.

Please refer to the images below:

Tables that you drag to the logical layer of the Data Source page canvas must be related to each other. When you drag additional tables to the logical layer canvas, Tableau automatically attempts to create the relationship based on existing key constraints and matching fields to define the relationship. If it can't determine the matching fields, you will need to select them.

If no constraints are detected, a Many-to-many relationship is created and referential integrity is set to Some records match. These default settings are a safe choice and provide the most a lot of flexibility for your data source.

Explanation

The different aggregations available for a measure determine how the individual values are collected: they can be added (SUM), averaged (AVG), or set to the maximum (MAX) or minimum (MIN) value from the individual row values.

For a complete list of the available aggregations, check out - List of Predefined Aggregations in Tableau.

The level of detail is determined by the dimensions in your view—for information about the concept of level of detail, see How dimensions affect the level of detail in the view.

Disaggregating your data can be useful for analyzing measures that you may want to use both independently and dependently in the view. For example, you may be analyzing the results from a product satisfaction survey with the Age of participants along one axis. You can aggregate the Age field to determine the average age of participants or disaggregate the data to determine at what age participants were most satisfied with the product.

Disaggregating data can be useful when you are viewing data as a scatter plot. See Example: Scatter Plots, Aggregation, and Granularity.

It is very much possible to specify the formatting at a WORKBOOK level (all sheets) instead of a single worksheet level.

You can quickly change how fonts, titles, and lines look in every view in a workbook by specifying format settings at the workbook level, instead of the worksheet level.

For example, you might want to use a specific font, size, and color so that all views adhere to your company's brand. You might also want to remove grid lines from your views—or make them more noticeable by increasing their pixel size or color.

You can also change the theme used by your workbook. Themes control items like the default font, colors, and line thickness. When you create a new workbook, it automatically uses the Default theme, which uses visual best practices.

Change fonts in your workbook:

You can change all fonts in your workbook or you can change fonts for only certain areas, such as just worksheet titles.

1) On the Format menu, select Workbook.

2) The Format Workbook pane replaces the Data pane on the left and provides a series of drop-down lists where you can change all font settings in a workbook, as well as the font settings for titles of worksheets, stories, and dashboards.

Note: If you have made font changes at the worksheet level, such as on a filter card or a worksheet title, changing the font at the WORKBOOK level will overwrite those changes.

Reset a workbook to its default settings

When you make changes to your workbook's font settings, a gray dot appears next to the setting in the Format Workbook pane. You can quickly switch back to default settings using the Reset to Defaults button.

1) On the Format menu, select Workbook.

2) In the Format Workbook pane, click Reset to Defaults.

Graphical user interface, application Description automatically generated

Explanation

Yes, it is very much possible to use measures in the same view multiple times. For example, refer to the image below:

We are using BOTH the Sum of the revenue and the AVG of the revenue in the same view!

To display the complete list of potential data connections when connecting to a server in Tableau, you should select "More" under the "To a Server" option. This action will provide a comprehensive list of server types and data sources that Tableau can connect to.

Explanation

If you chose 111,060 you were SO close to the correct answer but made a small mistake - you didn't change the aggregation to AVERAGE! This is one of the common mistakes many test takers make, so keep this in mind.

To reach the correct answer, follow the steps below:

1) Draw Assortment to the Column shelf, and drag Year to the Rows Shelf. Then Drill down further on Year to accomodate Quarters and Months as well!

Although this seems enough, DON'T FORGET to change the aggregation like in the next step, which will completely change the values!

The correct answer as you can see is 1,461 - Sales for Harware Assortment in 2017 Q4, October

The option to create bins in Tableau is available for numeric fields. Bins allow you to group a series of numeric values into larger segments, which can simplify analysis and help in creating histograms or other visualizations that show the distribution of data. For example, you can create bins to group ages into categories like 0-10, 11-20, etc.

In Tableau, parameters are dynamic values that can replace a constant in calculations, filters, and reference lines. If you have a parameter controlling a calculation, changing the parameter value can change the results of that calculation, thus impacting the visualization. Parameters can also be used to switch between different fields in the visualization; for example, allowing users to choose which measure or dimension to display.

Explanation

After creating a dual axis chart, make sure to synchronise their axis since they both might not be having the same y-axis.

Graphical user interface, chart, line chart Description automatically generated

To align the two axes in a dual axes chart to use the same scale, right-click (control-click on Mac) the secondary axis, and select Synchronize Axis. This aligns the scale of the secondary axis to the scale of the primary axis.

In this example, the Sales axis is the secondary axis and the Profit axis is the primary axis.

If you would like to change which axis is the primary, and which axis is the secondary, select the field on the Columns or Rows shelf that is the secondary, and drag it in front of the primary field on the shelf until you see an orange triangle appear.

In this example, you can select the SUM(Sales) field on the Rows shelf, and drag it in front of the SUM(Profit) field. The Sales axis is now the primary and the Profit axis is the secondary.

Visualization animations in Tableau can highlight changing patterns in data and can be either simultaneous or sequential:

A. Highlights changing patterns in data:

Visualization animations are designed to highlight changes in data over time or as filters are applied. They help users to see how data trends and patterns evolve.

B. Can be simultaneous or sequential:

Animations in Tableau can be configured to play simultaneously or sequentially. Simultaneous animations play all changes at once, while sequential animations play changes one after the other, allowing for a step-by-step view of data transformations.

Incorrect options:

C. Can be applied to map visualizations: While animations can be applied to map visualizations, the statement is not one of the two correct descriptions of visualization animations as per the question context.

D. Uses the Pages shelf: The Pages shelf is used for creating page animations, which is a different concept from visualization animations.

References:

Tableau's official documentation on animations: Formatting Animations

Explanation

Measure names and values CANNOT be deleted in Tableau like other columns can. These are auto-generated.

Calculated Fields, and Number of records can both be deleted.

To create a trend line, we need:

A parameter is a global placeholder value such as a number, date, or string that can replace a constant value in a calculation, filter, or reference line.

For example, you may create a calculated field that returns True if Sales is greater than $500,000 and otherwise returns False. You can replace the constant value of “500000” in the formula with a parameter. Then, using the parameter control, you can dynamically change the threshold in your calculation.

For example -

To set the default properties of a field to Currency in Tableau, you need to configure the number format of the field from the Data pane. This can be done by right-clicking the field in the Data pane and selecting Default Properties, then choosing the appropriate number format (in this case, Currency).

Explanation

Yes! It is possible to duplicate a field and add it to more than one hierarchy. Right click and choose duplicate.

Explanation

A histogram is a chart that displays the shape of a distribution. A histogram looks like a bar chart but groups values for a continuous measure into ranges, or bins.

By default, both field names are present in the Union, but contain several null values!

When field names in the union do not match, fields in the union contain null values. You can merge the non-matching fields into a single field using the merge option to remove the null values. When you use the merge option, the original fields are replaced by a new field that displays the first non-null value for each row in the non-matching fields.

You can also create your own calculation or, if possible, modify the underlying data to combine the non-matching fields.

For example, suppose you have the following customer purchase information stored in three tables, separated by month. The table names are "May2016," "June2016," and "July2016."

Table Description automatically generated

A union of these tables creates the following single table that contains all rows from all tables.

Now suppose a fourth table, "August2016", is added to the underlying data. Instead of the standard "Customer" field name, it contains an abbreviated version called "Cust."

Explanation

Tableau Public is a free service that lets anyone publish interactive data visualizations to the web. Visualizations that have been published to Tableau Public (“vizzes”) can be embedded into web pages and blogs, they can be shared via social media or email, and they can be made available for download to other users.

Check it out :

For a scatter plot view in Tableau, you can add reference lines and trend lines as part of the analytics options. Reference lines can be added to a visualization to mark certain values or to provide context, such as an average line across a scatter plot. Trend lines, on the other hand, are used to show the relationship between two variables in the view, indicating the general direction or pattern of the data points in a scatter plot.

To show how Internet Usage values change from year to year as a percentage, you should apply the "Percent Difference" quick table calculation to the Internet Usage field. This calculation compares each value to the previous value and computes the difference as a percentage, which is ideal for analyzing the rate of change over a sequential time period such as consecutive years.

Explanation

The word 'static tool' gives it away.

According to the official website :

Explanation

You can export the data in a Tableau data source, including all or part of the records from your original data. Alternatively, you can export only the portion of data used to generate the view.

Since the question mentions the data used to build the view, we'll focus on that :

*Export data in the view to Microsoft Access or .csv*

Export the data that is used to generate the view as an Access database (Windows only) or .csv file (Mac only).

1) In Tableau Desktop, select Worksheet > Export > Data.

2) Select a location and type a name for your Access database or .csv file.

3) Click Save.

4) If you're on Windows, the Export Data to Access dialog box displays to give you the option to immediately use the new Access database and continue working in Access without interrupting your work flow.

You can use a story to present a data narrative to lead your audience to your conclusions, or to assemble a sequenced analysis to share with collaborators. A story is a sequence of visualizations that work together to convey information. You can create stories to tell a data story, provide context, demonstrate how decisions relate to outcomes, or to simply make a compelling case4

You can combine two sets to compare the members. When you combine sets you create a new set containing either the combination of all members, just the members that exist in both, or members that exist in one set but not the other.

Combining sets allows you to answer complex questions and compare cohorts of your data. For example, to determine the percentage of customers who purchased both last year and this year, you can combine two sets containing the customers from each year and return only the customers that exist in both sets.

To combine two sets, they must be based on the same dimensions. That is, you can combine a set containing the top customers with another set containing the customers that purchased last year. However, you cannot combine the top customers set with a top products set.

Explanation

One way to view a measure in Tableau Desktop is to split it into bins. You can think of bins as buckets based on a range of values. For example, say you have a measure that represents age. Instead of aggregating the measure to calculate the average age, you can bin the measure to define age groups: 0–5, 6–10, 11–15, and so on. Then you can count the number of people in each age group.

Create a calculated field for variable bin size

Step 1

Select Analysis > Create Calculated Field.

Step 2

In the Calculated Field dialog box, complete the following steps:

Explanation

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.

To work with the MOST up-do-date data, use a live connection instead!

Explanation

Whenever you add a measure to your view, an aggregation is applied to that measure by default. This default is controlled by the Aggregate Measures setting in the Analysis menu.

If you decide you want to see all of the marks in the view at the most detailed level of granularity, you can disaggregate the view. Disaggregating your data means that Tableau will display a separate mark for every data value in every row of your data source.

To disaggregate all measures in the view:

Clear the Analysis >Aggregate Measures option. If it is already selected, click Aggregate Measures once to deselect it.

Exporting the visualisation gives us a static view of the visualisation.

It is NOT possible to interact with it, use filters, or dynamically enter anything in a visualisation exported PDF.

In Tableau Desktop, you can save views as PDF files rather than printing them as hard copies. You do not need to have Adobe Acrobat installed on your computer.

When you print an individual sheet to PDF, filters in the view are not included. To show filters, create a dashboard containing the sheet and export the dashboard to PDF. (IMPORTANT)

Names and Categories would be mostly used as dimensions (categorical data).

Profit and measures contain quantitative data and would be more suitable for Measures!

Unioning is the correct answer!

From the official documentation:

For example, suppose you have the following customer purchase information stored in three tables, separated by month. The table names are "May2016" , "June2016" and "July2016."

To make an axis bold, simply right click it, select format, and then click on Font to choose Bold:

None of the other options are valid ways to make the axis bold.

Read more about editing axis:

Explanation

By default, measures placed in a view are aggregated by SUM, which means that the data for that field in all of the rows is combined. Measures can also be aggregated as average, median, count, or count distinct.

By default, the shape that a Heap map uses is a "Square". See below:

A histogram is a chart that displays the shape of a distribution. A histogram looks like a bar chart but groups values for a continuous measure into ranges, or bins.

The basic building blocks for a histogram are as follows:

Demo :

Explanation

Since Sales is a measure, it can easily be depicted via size.

To drill down and change the level of detail, Country is the correct choice since it will contain STATE. We can then depict the various states by different shapes such as circle, square etc.

Finally, the Profit can be depicted via a color! Eg - Red for poor and green for excellent profits!

According to the official Tableau documentation:

Dimensions don't have aggregation properties, and adding properties manually each time defeats the whole DEFAULT aggregation purpose. Window tab doesn't have any default aggregation option!

When you click the icon to the right of Air Ticketing Cabin Type Name, the highlighter toggles on or off. The highlighter is a feature that allows you to highlight marks in the view that match a specific value or condition. You can access the highlighter by clicking the icon next to a dimension or measure in the legend, filter, or parameter. The icon looks like a light bulb with a plus sign. When you click the icon, a highlighter box will appear where you can enter or select a value to highlight. The marks that match the value will be highlighted in the view, while the others will be dimmed. You can also use the highlighter box to search for values, clear the highlighting, or lock the highlighting. To turn off the highlighter, you can click the icon again or close the highlighter box. The other options are not correct descriptions of what occurs when you click the icon to the right of Air Ticketing Cabin Type Name. The filter options do not open, because the icon is not for filtering, but for highlighting. The legend does not toggle on or off, because the icon is not for showing or hiding the legend, but for accessing the highlighter. The Edit Colors dialog box does not open, because the icon is not for changing the colors of marks, but for highlighting them.

Explanation

Yes! We get different color palettes. They are:

*From the official Tableau documentation*

To change the color for a value

1) Click on an item on the left, under Select Data Item.

2) Click a new color in the palette on the right. In Tableau Desktop you can hover over a swatch to identify the color.

3) Repeat for as many values that you want to change.

4) In Tableau Desktop, click OK to exit the Edit Colors dialog box. In Tableau Server or Tableau Online, simply close the dialog box.

AND

According to the official Tableau documentation:

Tableau data source files have the .tds file extension. Data source files are shortcuts for quickly connecting to the original data that you use often. Data source files do 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, adding groups, and so on. For more information, see Save Data Sources.

Extracts would be more beneficial for analyzing historical prices where we won't be making use of any real time data being streamed. Same is the case for enormous datasets having billions of rows (extracts will be more efficient in analyzing subsets of such large data).

As for live stock prices, flight updates, real time updates from production or mission critical systems - having a live connection is the most logical choice, since we need access to the most fresh and recent data possible at all times!

Explanation

When using a Blend, the primary data source appears with a BLUE tick-mark and the secondary data source appears with a ORANGE tick-mark.

See below:

1) Right click on Rows or Columns, and choose format. In the Font option click on Bold. (CORRECT) - this will modify only the selected axis (row or column)

2) Choose Format then Font from the Menu bar, and select Bold under the Header option (INCORRECT) - this modifies both rows and columns at the same time

3) Choose Format from the Menu bar, select Row or Column, and then select Bold under the header option (CORRECT) -  this will modify only the selected axis (row or column)

4) Select Text Label on the Marks Card, choose Rows or Columns, and then select Bold. (INCORRECT) - no such option exists

Explanation

Not too tough. Follow along the steps:

Drag Color to Filter and choose Red:

3) Now to display the percentage correctly, lets format it. Click on the In Stock % pill in the Row shelf, and select format:

And your final view will look like :

Explanation

The data that you analyze in Tableau is often made up of a collection of tables that are related by specific fields (that is, columns). Joining is a method for combining data on based on those common fields. The result of combining data using a join is a virtual table that is typically extended horizontally by adding columns of data.

For example, consider the following two tables originating from a single data source:

We can combine these 2 tables, simply by joining the tables on ID to answer questions like, "How much was paid in royalties for authors from a given publisher?". By combining tables using a join, you can view and use related data from different tables in your analysis.

 You can share a dashboard as an image file by using one of the following methods: Export Image on the Dashboard menu, or a dashboard export button. Export Image on the Dashboard menu allows you to export the dashboard as an image file in BMP, JPEG, PNG, or SVG format. A dashboard export button is a custom button that you can create on your dashboard to export it as an image file using a URL action

When creating a histogram in Tableau, bin size refers to the range of the continuous measure counted in each bin. A histogram is a chart that displays the shape of a distribution of a continuous measure. A histogram looks like a bar chart but groups values for a continuous measure into ranges, or bins. The basic building blocks for a histogram are as follows: Mark type: Automatic; Rows shelf: Continuous measure (aggregated by Count or Count Distinct); Columns shelf: Bin (continuous or discrete)4 To create bins from a continuous measure, you need to specify the size of bins, which determines how many bins are created and how wide they are. The size of bins is equal to the difference between consecutive values along the axis that represents the bins. For example, if you have bins with values 0-10, 10-20, 20-30, etc., then the size of bins is 10. You can either enter a value for the size of bins manually or have Tableau suggest an optimal bin size based on a formula that considers the number of distinct rows and the minimum and maximum values in the data5 The other options are not valid definitions of bin size when creating a histogram in Tableau. The minimum number of axis ticks in the view is determined by Tableau’s automatic scaling and formatting of axes, which can be adjusted manually if needed. The count distinct (COUNTD) of items on either axis is an aggregation function that returns the number of unique values in a field, which can be used as a measure in a histogram but not as bin size. The maximum number of marks in the view is limited by the performance and readability of the visualization, which can be improved by filtering, sorting, or aggregating the data4

When you drop a discrete field on Color in the Marks card, Tableau displays a categorical palette and assigns a color to each value of the field.

When you drop a continuous field on Color, Tableau displays a quantitative legend with a continuous range of colors.

Web version:

Desktop Version:

For more information about color palettes, see Color Palettes and Effects.

To clear all sorting in a Tableau visualization, you would go to the Worksheet menu, select the "Clear" option, and then choose "Sorts." This action removes all sorting that has been applied to the visualization, including any custom sorting or sorting based on multiple fields. This is a quick way to reset the view to its default sorting state and is particularly useful when you have applied various sorting layers and wish to start fresh.

According to the [Tableau Desktop Specialist Exam Guide], a join is a way to combine table columns in relational databases by using shared values. A join can be inner, left, right, or full, depending on how the matching rows are included or excluded.

By default, all filters that you set in Tableau are computed independently. That is, each filter accesses all rows in your data source without regard to other filters. However, you can set one or more categorical filters as context filters for the view. You can think of a context filter as being an independent filter (Option stating - To create a dependent filter eliminated here). Any other filters that you set are defined as dependent filters because they process only the data that passes through the context filter.

You may create a context filter to:

1) Improve performance – If you set a lot of filters or have a large data source, the queries can be slow. You can set one or more context filters to improve performance.

2) Create a dependent numerical or top N filter – You can set a context filter to include only the data of interest, and then set a numerical or a top N filter.

For example, suppose you’re in charge of breakfast products for a large grocery chain. Your task is to find the top 10 breakfast products by profitability for all stores. If the data source is very large, you can set a context filter to include only breakfast products. Then you can create a top 10 filter by profit as a dependent filter, which would process only the data that passes through the context filter.

You should select Size on the Marks card and use the slider to adjust the size to uniformly change the size for all marks in a view. The Size property on the Marks card allows you to control the size of marks in the view by moving the slider to the left or right. The Size slider affects different marks in different ways, such as making them bigger or smaller, wider or narrower, or thicker or thinner1 The other options are not valid ways to uniformly change the size for all marks in a view. Selecting Label on the Marks card and then selecting Alignment will allow you to change the position of labels on marks, not the size of marks2 Using the Fit dropdown menu on the toolbar will allow you to change how the view fits within the worksheet, not the size of marks3 Selecting Format on the menu, and then selecting Cell Size will allow you to change the height and width of cells in a text table, not the size of marks in other types of views4

With dimension filters in Tableau, you can use several filter modes, including "Multiple Values (drop-down)" which allows users to select one or more values from a drop-down list of all the dimension's members. Another mode is "Wildcard Match," which lets users filter the view by typing in a text box to match dimension members that contain the typed string. These filter types are particularly useful for string or categorical dimensions where users need to search or select specific members to display in the view.

Since Sales is a measure, it can easily be depicted via size.

To drill down and change the level of detail, Country is the correct choice since it will contain STATE. We can then depict the various states by different shapes such as circle, square etc.

Finally, the Profit can be depicted via a color! Eg - Red for poor and green for excellent profits!

According to the Tableau Help, one of the ways to improve a crosstab is to “Include an Other group”. The help also states that “If you have a large number of members in a dimension, you can create groups to combine low-frequency members into an Other group. This can help you focus on the most relevant data and reduce clutter in your view” (page 2).

Tree maps size begins from maximum in top left to smallest in bottom right.

See below to learn how to create a TreeMap and add colours to it:

To change a measure so that it automatically aggregates as an average instead of a sum, you should right-click the field in the Data pane and select Default Properties. In the Default Properties menu, you can set the default aggregation for the measure, such as setting it to calculate an average by default when added to a view.

Explanation

Sets are custom fields that are created within Tableau Desktop based on dimensions from your data source. They are subsets of your data, which can be created manually or computed. Either dimensions or measures can be used to determine what is included or excluded from a set using conditional logic, but to CREATE a set we use dimensions.

Reference :

Explanation

Explanation

The following is the official documentation for the String function LEFT:

Explanation

When you connect to a data source, Tableau automatically separates date fields into hierarchies so you can easily break down the viz. You can also create your own custom hierarchies. For example, if you have a set of fields named Region, State, and County, you can create a hierarchy from these fields so that you can quickly drill down between levels in the viz.

Explanation

Data is generated and analyzed at many different levels of granularity. Granularity is the level of detail of the data. For example, when looking at graduation data, granularity would describe whether a row in the data set represents a single person or the graduating class of a university.

According to Tableau's official documentation:

Explanation

A Pareto chart is a type of chart that contains both bars and a line graph, where individual values are represented in descending order by bars, and the ascending cumulative total is represented by the line.

On the primary axis, bars are used to show the raw quantities for each dimension member, sorted in descending order.

On the secondary axis, a line graph is used to show the cumulative total in percent format.

We can use scatter plots to visualize relationships between numerical variables!

In Tableau, you create a scatter plot by placing at least one measure on the Columns shelf and at least one measure on the Rows shelf (Total 2 minimum). If these shelves contain both dimensions and measures, Tableau places the measures as the innermost fields, which means that measures are always to the right of any dimensions that you have also placed on these shelves. The word "innermost" in this case refers to the table structure.

 ( Simple Scatter Plot)

 (Matrix of Scatter Plots)

A scatter plot can use several mark types. By default, Tableau uses the shape mark type. Depending on your data, you might want to use another mark type, such as a circle or a square. For more information, see Change the Type of Mark in the View.

To create a scatter plot, follow the steps below: