Category: Filters and calculated fields

Using extensions in Tableau – Dealing with Complex Visualizations, Customizations, and APIs

Posted on by Mary Kimberlin

It is also possible to use third party services to create visualizations in Tableau. Tableau Exchange (https://exchange.tableau.com/extensions) provides an array of objects that can be used in a Tableau dashboard to create charts but also perform spatial analysis, add custom annotations to charts, and even collaborate in Teams.

Salesforce has its own set of extensions, and there is also a set of extensions developed directly by Tableau.

To access them, follow the below-mentioned steps:

  1. Create a new dashboard by pressing the New Dashboard button at the bottom of your screen, as seen in Figure 6.71:

Figure 6.71: New dashboard

2. Next, drag the Extension object on your dashboard.

Figure 6.72: Add Extension

3. The interface which opens will show all the Extensions available on Tableau Exchange without needing to leave Tableau.

Each extension has its own set of instructions, and in Chapter 9 – Exploring Einstein AI and Advanced Analytics, we will show you how to use the Salesforce Einstein extension, but in the meantime, explore the available range to find the extension that mostly fits your needs. And if you cannot find the perfect one, you are now well-equipped to create every sort of visualization in Tableau.

Conclusion

In conclusion, as we wrap up this insightful journey into the realm of advanced visualizations using Tableau and Salesforce CRM data, it is our hope that you have gained a deeper understanding of the vast capabilities that this visualization tool offers. The power to transform raw, often complex CRM data into meaningful and insightful visual representations lies at your fingertips.

Through this chapter, we aimed to elevate your skills from creating sophisticated Sankey diagrams and calendar-based visualizations to expertly customizing geographical data visualizations. We also discussed the power of third-party integrations, a crucial aspect in today’s interconnected technological landscape. The potential for innovation here is vast, and we encourage you to explore further, continually pushing boundaries to uncover deeper insights from your CRM data.

Remember, fostering a data-curious culture within your organization is a journey, not a destination. Every dataset brings new questions, unique insights, and innovative perspectives. The beauty of data visualization is that it brings us closer to the story hidden within the data, enabling data-driven decision-making crucial for business growth.

We will now move back into Salesforce to look at using Tableau Visualizations within the CRM.

Join our book’s Discord space

Join the book’s Discord Workspace for Latest updates, Offers, Tech happenings around the world, New Release and Sessions with the Authors:

https://discord.bpbonline.com

Advanced maps – Dealing with Complex Visualizations, Customizations, and APIs-1

Posted on by Mary Kimberlin

We can convey several layers of information by using maps in Tableau. We started in the previous chapter with a simple filled map, and we will now take it one step forward by looking at the number of accounts and the revenues on the same map.
Before we do so, you will have to upload some additional data to your org that is required for this visualization. First, download the files available at the GitHub repository for the book.
Now follow these instructions to load the opportunities:

  1. Login to Salesforce and navigate to the ‘Setup’ area by clicking the gear icon in the upper right corner.
  2. In the Quick Find box, type and select Data Import Wizard.
  3. Click on the Launch Wizard button within the Data Import Wizard.
  4. Select the type of object that matches your CSV data, such as Opportunities for opportunity data.
  5. Click on Choose a CSV file, browse to your tfs_opps.csv file, and upload it.
  6. Review the field mappings. The wizard will try to auto-map CSV columns to Salesforce fields. Adjust manually if necessary.
  7. After verifying the field mappings, click Next.
  8. Review your import settings in the summary page and click Start Import.
  9. Monitor the import progress. Salesforce will indicate when the import is complete.
  10. Once the import is complete, check the relevant object in Salesforce, like Opportunities, to ensure the data is correctly imported.
  11. Review any error reports generated by Salesforce and address any issues highlighted.

Repeat this process for the tfs_accs.csv file, the Account object, the tfs_users.csv file, and the Users object.
For this chart, the Account object was used as a primary data source, and the Opportunity object as a secondary data source. Please refer to Chapter 3, Building and Integrating Data Pipelines for details on how to blend data sources.
To create our map, follow these steps:

  1. Double-click on the Billing State/Province field (from the Accounts object). This will create a map, as shown in Figure 6.49:

Figure 6.49: Add Billing State to view

  1. From the Marks menu, change the mark type to Circle, as shown in Figure 6.50:

Figure 6.50: Change mark type to circle

  1. Right-click on Account ID and drag it onto the Size card, choose Count Distinct from the menu that opens, as shown in Figure 6.51:

Figure 6.51: Size by Account count

  1. From the Opportunity object drag Expected Amount to Color (make sure to have set the blend correctly), as shown in Figure 6.52:

Figure 6.52: Color by Expected Revenue

  1. Click on the Color card, then choose Edit Colors, as can be seen in Figure 6.53:

Figure 6.53: Edit colors

  1. Choose the Red – Blue Diverging palette, as shown in Figure 6.54:

Figure 6.54: Change color palette

Funnel charts– Dealing with Complex Visualizations, Customizations, and APIs

Posted on by Mary Kimberlin

One of the most indicative charts for Salesforce data is the funnel chart, which is the chart in which we can follow the progression of our sales pipeline from initial contact to final conclusion.
For this chart, we will use the custom dataset Opportunity History that comes with this book. If you are working with real Salesforce data, you should be able to replicate this chart using the Opportunity History object from your Salesforce environment or your data warehouse, following the instructions in Chapter 3 – Building and Integrating Data Pipelines.
To create a funnel chart, follow these steps:

  1. Filter out “Closed Lost” by using Stage Name as a filter and excluding “Closed Lost”.
  2. Drag Stage Name onto Rows, as shown in the following figure:

Figure 6.24: Drag Stage Name to Rows

  1. Right-click on Opportunity ID and drag it to Columns. In the menu that opens, choose Count Distinct (Figure 6.25).

Figure 6.25: Count distinct Opportunities by Stage

  1. Sort Stage Names in descending order according to the number of opportunities.

Figure 6.26: Sort Stages by count descending
We now need to trick Tableau into creating our funnel chart. To do so:

  1. Right-click on Opportunity ID, drag it to Columns, and drop it next to the green pill you already have there, as shown in Figure 6.27:

Figure 6.27: Copy Opportunity Id to Columns
You should now have two identical bar charts which look like the chart below:

Figure 6.28: Two identical bar charts

  1. Right-click on the left axis and click Edit Axis from the menu that opens, as shown below:

Figure 6.29: Copy Opportunity Id to Columns

  1. Select Reversed, as shown in Figure 6.30:

Figure 6.30: Reverse left axis
Your chart should now look like the one below, already much more like a funnel.

Figure 6.31: Funnel

  1. Drag Stage Name to the Color mark in the All card, as shown in Figure 6.32:

Figure 6.32: Color Stages

  1. Press Ctrl on your keyboard and drag the CNTD (Opportunity ID) field to the Label mark in the All card, as shown in Figure 6.33:

Figure 6.33: Add label

  1. Click on the Label mark on the top CNTD (Opportunity ID) card, as shown in Figure 6.34:

Figure 6.34: Select label

  1. In the Alignment menu, choose left, as shown in Figure 6.35:

Figure 6.35: Align labels left
A funnel would not be a proper funnel without percentages, so we will create a new calculated field and paste the following formula:
This formula divides the number of opportunities at each stage by the number of opportunities in the first stage, thus giving us a view of the percentage of opportunities that continue to the next stage of our sales pipeline.

  1. Give your calculated field a name. The one below, for example, is called “Share of total”.

Figure 6.36: Share of total calculation

  1. Drag your new calculation onto the Label mark in the bottom CNTD (Opportunity ID) card, as can be seen in Figure 6.37:

Figure 6.37: Add calculation to label

  1. Drag CNTD (Opportunity ID) away to remove it from the chart, as can be seen in Figure 6.38:

Figure 6.38: Remove count

  1. Click on the Label mark on the bottom CNTD (Opportunity ID) mark, as shown in Figure 6.39:

Figure 6.39: Select bottom label

  1. In the Alignment menu, choose left, as shown in Figure 6.40:

Figure 6.40: Align bottom labels left

  1. Right click on the calculation you have created and select Default Properties from the menu that opens, next click on Number Format.

Figure 6.41: Open number formatting

  1. In the pane that opens, select percentage, decrease the decimal places to 0, and click on OK, as shown in Figure 6.42:

Figure 6.42: Set percentage format
We are almost there, but we need some cosmetic adjustments for this chart to look like a funnel, follow the below steps to do so:

  1. From the Format menu, click on Borders, as can be seen in Figure 6.43:

Figure 6.43: Open Borders menu

  1. Select None from each menu in Sheet, Rows and Columns (if it does not say so already), as can be seen in Figure 6.44:

Figure 6.44: Select no borders

  1. Click on the Lines icon (Figure 6.45).

Figure 6.45: Open Lines menu

  1. Select None from each menu in Sheet, Rows and Columns (if it does not say so already), as shown in the figure below:

Figure 6.46: Select no lines

  1. Right click on the left axis and untick “Show Header”, as shown in Figure 6.47:

Figure 6.47: Hide left axis header
Your chart should look something like the one below:

Figure 6.48: Funnel final

Objectives– Dealing with Complex Visualizations, Customizations, and APIs

Posted on by Mary Kimberlin

Introduction

In this chapter, we explore the untapped potential of Tableau in conjunction with Salesforce CRM data, diving deep into advanced visualizations to unlock richer insights. From a comprehensive look at advanced capabilities, including Sankey charts and calendar-based visualizations, to mastering customized geographical data visualizations, we will take you through the endless customization possibilities that Tableau offers. We will cap it off with a look at third-party integrations, examining how they can enrich your visualizations and optimize decision-making. This chapter aims to inspire you to push boundaries, fostering an innovative and data-curious culture within your organization. Let us embark on this exciting journey together to unravel the full extent of Tableau’s power and transform your CRM data into meaningful, actionable information.

Structure

The chapter covers the following topics:

  • Introducing the advanced capabilities of Tableau
  • Using extensions in Tableau

Objectives

Upon completing this chapter, readers will be able to understand the advanced capabilities of Tableau in visualizing CRM data by learning to create and interpret advanced charts such as Sankey diagrams and calendar visualizations and exploring ways to customize visualizations using geographical data. They will also discover how to utilize third-party integrations to augment data visualization capabilities and develop the necessary skills to uncover deeper insights and patterns from your CRM data. Finally, they will gain proficiency in transforming raw CRM data into meaningful, actionable visual insights and learn to use Tableau features and tools effectively to support data-driven decision-making processes.

Introducing advanced visualizations

At this point, we should feel quite comfortable with creating charts in Tableau, so we will now take it a bit further by looking at creating charts that require to make use of the full range of customization options in Tableau. We will use calculated fields and table calculations and finally bring together several datasets to showcase the possibilities of spatial analysis in Tableau’s maps.

Filled map– Extracting Deeper Insights with Funnels, Maps, and Hybrid Visualizations

Posted on by Mary Kimberlin

To create a filled map:

  1. Double click on the Billing State/Province field.
  2. Drag Expected Revenue on the Colors mark.
  3. Change the mark type to Maps, as shown in Figure 5.65.

Figure 5.65: Creating filled map

The result should look something like the map in Figure 5.66:

Figure 5.66: Final filled map visualization

We can use the tools mentioned above to zoom in and bring to the center of the view exactly the section of the map we want to show. From here we can see there is a distinct geographic pattern to the revenue we expect, with clusters of states that are close geographically and also present higher revenues.

Conclusion

In conclusion, this chapter has provided you with the knowledge and tools needed to create more advanced visualizations like donut charts, bar-in-bar charts, and maps. You’ve also learned how to harness the power of filters and calculated fields to customize and improve your data analysis. By following the steps outlined in this chapter, you can now dive deeper into your Salesforce data using Tableau, and more effectively communicate your insights to stakeholders.

Understanding geographical patterns, funnel analysis, and performance tracking are just a few of the many insights you can gain from the techniques discussed in this chapter. With this knowledge in hand, you can leverage the full potential of Tableau and Salesforce to make better-informed decisions for your organization. Keep experimenting with different visualizations and techniques as you continue to explore these powerful tools and uncover new insights into your data.

In the next chapter, we will move on to discussing advanced topics for visualization with Tableau.

Filters and calculated fields – Extracting Deeper Insights with Funnels, Maps, and Hybrid Visualizations

Posted on by Mary Kimberlin

We will again use donut charts to look at the ratio of lost to won opportunities per lead source. To do so, we will have to perform two operations:
• Filter the stage so that it only shows opportunities that have been either Lost or Won.
• Create a new field that labels each opportunity as lost, won, or still open.
From a new sheet, the steps to perform are as follows:

  1. Drag Stage to the Filters card. A menu will open, as shown in Figure 5.30:

Figure 5.30: Adding Stage filter

  1. Select Closed Lost and Closed Won from the available list and press OK, as shown in Figure 5.31:

Figure 5.31: Selecting specific Stage values to filter

  1. There are several ways to create a calculated field in Tableau. The two most popular ones are the following: 1. Click on the caret next to the search function on top of your dimension list, then select Create Calculated Field, as shown in Figure 5.32:

Figure 5.32: Accessing Create Calculated Field option

  1. From the Analysis menu at the top of your sheet, click on Create Calculated Field , as shown in Figure 5.33:

Figure 5.33: Accessing Create Calculated Field via Analysis menu

  1. The calculated field window will now open. In this window, you can find five things, as shown in Figure 5.34:
  1. Calculation title: This is where you can type the name you will give to the new field you are creating.
  2. Calculation area: This is where you will write the logic that determines the output of the field you are creating.
  3. Function list: This is the list of ready-made functions available to use, which are not too dissimilar from what you can find in Excel or SQL. When you select a function, Tableau shows you what it does and gives you an example of how to use it.
  4. Apply button: Clicking this button will create your calculated field or modify your calculated field but will not close the window. It is useful if you are trying different calculations until you set on the final one.
  5. OK button: Clicking this button will create your calculated field or modify your calculated field, then close the window. It is useful if you are satisfied with the calculation.

Figure 5.34: Calculated Field window overview

  1. Since we want to create a new field based on Stage, we will use an IF function. The formula is as follows:
    IF [Stage] = ‘Closed Lost’ THEN ‘Lost’

ELSEIF [Stage] = ‘Closed Won’ THEN ‘Won’

ELSE ’Still Open’

END

  1. As a title, we will write Lost, Won or Open, then press OK, as shown in Figure 5.35:

Figure 5.35: Creating Lost, Won or Open calculated field
Calculated fields are automatically added to the list of fields and can be distinguished by the little equal sign that precedes their data type, as shown in Figure 5.36:

Figure 5.36: New calculated field added to dimensions list
You can always change a calculated field in Tableau, just by right clicking on the name and selecting Edit from the menu that opens, as shown in Figure 5.37:

Figure 5.37: Editing a calculated field

  1. Now that you have filtered your Opportunities and created a new calculated field, follow the steps in the previous section to create a new donut chart. The final result should look something like Figure 5.38:

Figure 5.38: Final donut chart with calculated field

  1. To compare the share of lost and won opportunities by lead source so we will drag Lead Source to Columns, as shown in Figure 5.39:

Figure 5.39: Adding Lead Source to Columns shelf

  1. Tableau has created a series of donut charts, one for each lead source, as shown in Figure 5.40:

Figure 5.40: Donut charts showing breakdown by Lead Source

  1. We can see that some lead sources provide opportunities that are more likely to close, but our calculation does not show the share of lost and won opportunities per lead source.
    To change it, click on the field used for the share calculation. It has a triangle next to its name, as shown in Figure 5.41.

Figure 5.41: Selecting share calculation pill

  1. From the menu that opens, click on Edit Table Calculation, as shown in Figure 5.42:

Figure 5.42: Accessing Edit Table Calculation

  1. From the menu that opens, click on Cell, then click on the x in the top right corner to close the menu, as shown in Figure 5.43:

Figure 5.43: Changing table calculation to Cell level
Your calculation should now be correct, as shown in Figure 5.44:

Figure 5.44: Correct donut chart calculations

Donut charts – Extracting Deeper Insights with Funnels, Maps, and Hybrid Visualizations-1

Posted on by Mary Kimberlin

Donut charts are an alternative to pie charts, which allows for better use of screen space. I would not recommend using donut charts for more than three categories. In this case, we will use it to look at the rate of opportunities closed. To create a donut chart, the steps are as follows:

  1. Drag your Dimension (in this case, Closed) to the Color mark, as shown in Figure 5.1:

Figure 5.1: Dragging Closed field to Color mark to create donut chart

  1. From the Marks menu, choose Pie, as shown in Figure 5.2:

Figure 5.2: Changing marks type to Pie to create donut chart

  1. Take your measure (in this case a count distinct of Opportunity ID) and drag it to the Angle mark, as shown in Figure 5.3:

Figure 5.3: Dragging Opportunity ID count to Angle mark for donut chart

  1. Your data should now look like a pie chart, as shown in Figure 5.4:

Figure 5.4: Initial donut chart created

  1. To create a donut chart we need to ‘trick’ Tableau into thinking there are two pie charts. To do so, in the Rows space, type the following, as shown in Figure 5.5:
    AVG(0)

Figure 5.5: Adding AVG(0) calculation to rows shelf to create stacked pies

  1. Then, repeat the same step again, as shown in Figure 5.6:

Figure 5.6: Adding second AVG(0) calculation to rows shelf

  1. You should now have two pie charts vertically stacked, as shown in Figure 5.7:

Figure 5.7: Vertically stacked pie charts created

8. Click on the caret that appears when hovering on either of the measures you have just created. A menu will, now, open, as shown in Figure 5.8:

Figure 5.8: Hovering over measure pill to access menu

  1. Click on the Dual Axis, as shown in Figure 5.9:

Figure 5.9: Selecting Dual Axis option

  1. Your pie charts are now on top of each other, so that it looks like you only have one pie chart. You also have 3 Marks menus now; one for each measure and one that controls both, as shown in Figure 5.10:

Figure 5.10: Stacked pie charts now overlapping as one chart

  1. Open one of the measure menus and remove all pills by dragging them away from the menu, as shown in Figure 5.11:

Figure 5.11: Removing pills from secondary measure

  1. From the same menu, click on the Color mark and select the color which matches your background (in this case white), as shown in Figure 5.12:

Figure 5.12: Changing secondary measure’s color to match background

  1. Still in the same menu, click on the Size mark and drag the indicator left to reduce the size of your chart, as shown in Figure 5.13:

Figure 5.13: Reducing secondary measure’s size

  1. Your chart should now start to look like a donut chart, as shown in Figure 5.14:

Figure 5.14: Donut chart taking shape

Bringing all your insights together in a dashboard – Exploring Charts, Graphs, and Dashboards

Posted on by Mary Kimberlin

The previous example shows that sometimes the full extent of our analysis can only be achieved by comparing several charts. However, we would not want our users to keep switching back and forth between tabs to follow our conclusions. This is where Tableau’s dashboard functionality comes in handy.

To create a dashboard, click on the New Dashboard button as shown in Figure 4.53:

Figure 4.53: Clicking on ‘New Dashboard’ button to create a dashboard

This is the dashboard area. It displays the following as shown in Figure 4.54:

  1. Preview menu: This menu allows you to see how your dashboard will look on different devices.
  2. Size: From here, you can choose your dashboard size among a list of preset ones or define your own.
  3. Sheets: From here, you can choose which sheets to drag to the dashboard.
  4. Objects: From here, you can choose additional objects like images and text boxes to add to the dashboard.
  5. Layout: The layout tab allows you to finetune the way your dashboard looks.
  6. Dashboard: It is the actual dashboard, your canvas on which you will add your charts.

Figure 4.54: Turning data into visual insights on your dashboard

To add a sheet to the dashboard, select it from the sheets list, drag it, and drop it onto the dashboard as shown in Figure 4.55:

Figure 4.55: Adding a sheet to the dashboard by dragging and dropping from the sheets list

As you can see, Tableau has added the chart so that it takes the entire dashboard and added on the right a color and size legend. Now add the second chart on the right of the first one. Tableau will grey out the area which will be covered by your chart as you drag it as shown in Figure 4.56:

Figure 4.56: Tableau dashboard with enlarged chart and size legend, ready for placement of second chart

Figure 4.57: Second chart

Next, add your third chart underneath the first one (Figure 4.57) as shown in Figure 4.58:

Figure 4.58: The third chart is added below the first chart

Finally, add your last chart, in the bottom right quadrant as shown in Figure 4.59:

Figure 4.59: Bottom right quadrant chart added as final touch

This dashboard is not particularly informative therefore some adjustments are required. First, the size should be increased to obtain more space to work with. To change size, click on the Size menu as shown in Figure 4.60:

Figure 4.60: Adjusting dashboard size for enhanced working space

Click on Desktop Browser (1000 x 800) as shown in Figure 4.61:

Figure 4.61: A desktop browser displayed on a screen

Choose your preferred size. Here, we have chosen Generic Desktop, as shown in Figure 4.62:

Figure 4.62: Selecting Generic Desktop size for customized experience

You can also alter the Width and Height values directly to your preferred values, as shown in Figure 4.63:

Figure 4.63: Customize dimensions effortlessly by directly inputting preferred Width and Height values

Next, we will add the dashboard title by clicking on the Dashboard menu as shown in Figure 4.64:

Figure 4.64: The Dashboard title is added by clicking on the Dashboard Menu

And we will click on Show Title as shown in Figure 4.65:

Figure 4.65: Click “Show Title”

Dashboard 1 is not a very insightful title. To change a title, double-tap on it, to open a menu as shown in Figure 4.66:

Figure 4.66: Changing the title of Dashboard 1 using the menu.

Type in your desired title as shown in Figure 4.67:

Figure 4.67: Title input field on a digital screen

Click on OK as shown in Figure 4.68:

Figure 4.68: Confirming user action with a simple click of ‘OK’

Following the same method, we will change the titles of each chart as shown in Figure 4.69:

Figure 4.69: Chart titles undergo transformation with consistent approach

Since we have added labels to all my charts, the legends are unnecessary, so we will remove them to give more space to my charts. To do so, click on a legend as shown in Figure 4.70:

Figure 4.70: Removing legends to create more space for charts

Next click on the x button in the top right corner, as shown in Figure 4.71:

Figure 4.71: Closing the opportunity score popup

Repeat for all the legends you do not wish to show. The dashboard looks more professional now, as can be seen below:

Figure 4.72: Dashboard with hidden legends

Your users can now see all your charts at a glance and quickly absorb the knowledge you wish to impart.

Using ‘Show Me’ menu and bar charts – Exploring Charts, Graphs, and Dashboards

Posted on by Mary Kimberlin

The quickest way for a beginner to start creating visualizations in Tableau is to use the Show Me menu, which will showcase a range of ready-made charts and the combinations of Dimensions and Measures you will need to create Figure 4.2:

Figure 4.2: A beginner’s guide: Explore Tableau’s Show Me menu for effortless chart creation

For example, to answer a question like who my largest customer is, you can select Account Name, hold CTRL, and select Annual Revenue, then click on Horizontal Bars in the Show Me menu, as shown in Figure 4.3:

Figure 4.3: Selecting account name and annual revenue, then choose horizontal bars

Tableau will recommend which chart to use with a border. This time, we will agree with the recommendation.

Figure 4.4: Tableau chart

So, this is your first Tableau chart (Figure 4.4). It looks strange, but we wanted to know who our largest customers were. To do that, we need to sort our chart so that the customers with the largest revenue are at the top.

There are several ways to do that; for now, we will click on the Sort button above the columns/rows area, as shown in Figure 4.5:

Figure 4.5: Clicking on the sort button to organize columns/rows

Our chart looks as shown in Figure 4.6:

Figure 4.6: Account chart

It seems that we have a lot of customers with the same level of revenue, so this is probably not the most insightful chart we could create. But with Tableau, we are never more than a few clicks away from finding more information. For example, which industries bring the largest revenue?

To answer that question, we will select the Industry field and drag it on top of the Account Name field in the Rows panel.

We now have a much better-looking chart as shown in Figure 4.7:

Figure 4.7: Better chart

After sorting it in descending order as we did before, this is what our chart looks as shown in Figure 4.8:

Figure 4.8: Descending sorted chart.

We now know that Engineering and Apparel are the largest industries by revenues, with Energy being a distant third.

Relationships – Building and Integrating Data Pipelines

Posted on by Mary Kimberlin

Introduced in 2020.2, relationships are a new way of connecting different data objects. While joins happen on the physical layer of the data source, relationships happen at the logical layer. This means that there is no new data source created, and Tableau will automatically handle duplicates and null values.

Relationships are the default way used by Tableau to connect data objects. Therefore, the process of using relationships requires fewer steps than joins. To start using relationships with your tables, follow these steps:

  1. Drag a table from the left side of the screen.
  2. Drag the second table you wish to join from the left side of the screen.
  3. If Tableau has enough information, it will set up an automatic relationship.
  4. If Tableau cannot establish a relationship automatically, it will highlight the problem just as it finds a link. It will highlight the problem with a triangle, as shown in Figure 3.20:

Figure 3.20: Tableau indicating it cannot automatically create a relationship between two tables

  1. If that is the case, you can use the menu at the bottom of your screen to specify which fields should be used to establish the relationship.
  2. Just as before, the join is configured so that Tableau can use the table Account with the table Contact by using the field Account ID present in both tables but labeled as Account ID (Contact) in the Contact table, as shown in Figure 3.21.

Figure 3.21: Manually defining the relationship in Tableau using the relationship editor

  1. As you can see, the red triangle mark has disappeared, and the two tables are now joined. This process can be repeated on as many objects as necessary. Simply drag any additional table into the join area, as shown in Figure 3.22, and proceed with the steps defined above.

Figure 3.22: Multiple tables successfully related in Tableau

To remove a table, follow the same steps outlined in the Joins section.

Joins versus relationships

At first glance, it may seem that relationships and joins are quite similar, if not identical. However, there are differences in their substance and behaviors worth understanding to decide which option to use.

The obvious advantage of relationships is that they do not require any prior understanding of SQL-like join behavior, which makes them a great option for beginner users. Advanced users, however, may prefer the additional degree of flexibility that comes from defining which type of join to employ and which fields to use.

It is also worth mentioning that relationships may not work as intended for data where the quality is exceptionally poor and may cause performance issues if large quantities of data are needed.