Treemaps in Tableau – Extracting Deeper Insights with Funnels, Maps, and Hybrid Visualizations

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

Posted on 08/22/202408/22/2024 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:

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.

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Advanced maps – Dealing with Complex Visualizations, Customizations, and APIs-2

Posted on 06/11/202408/22/2024 by Mary Kimberlin

In one map, we can now see in which states we have the most accounts and the largest revenue. An even more interesting pattern emerges in which the number of accounts and the revenues do not go hand in hand. Rather, we can see even more clearly the clusters where we would expect large revenues (that is California) but are instead seeing poor performances. All of these clusters are close together, so there must be a geographical explanation of what we are seeing (Figure 6.55).

Figure 6.55: Colored dots
To proceed with the next step, we need to create a new dataset that joins the objects Accounts, Opportunities, and Users. This will allow us to bring together the geographical information related to the accounts, the financial information tied to opportunities, and the geographical locations pertaining to our sales representatives, which can be found in the User object. Alternatively, you can use the dataset provided in this book.
Since 2019, Tableau has allowed the option to perform spatial analysis even in cases where spatial files are unavailable, as long as information such as latitude and longitude is provided. Luckily, Salesforce provides this information out of the box for both Accounts and Users.
Let us go back to our original map and work from the assumption that since we have spotted a geographical pattern in our data, geography could also present a solution, in this case, by looking at where our sales representatives are located against our accounts and the revenue we expect to generate.
In the previous case, we have built a map at the state level. Now, we will go down to the city level. The process is the same as described before, but this time, we will start with the Billing City field rather than the Billing State. The final result should look something like the map below:

Figure 6.56: Sized dots
When we break our data down by cities, the contrast is even starker. We see that California has several accounts but low expected revenues, while revenues in Texas seem to be driven by a specific city. At the border between Nebraska and Iowa, we have our most profitable accounts. How does this compare with the geographical location of our sales representatives?
To answer this question, we will start by creating a spatial object out of the latitude and longitude of our User object. To do so, follow the below-mentioned steps:

Create a calculated field and write the following formula:
Give a name to your calculation, then press OK.
Drag the field you have just created to the map and then on top of the Add a Marks Layer icon on your map, as shown below.

Figure 6.57: Add user locations layer
You will notice now that there is an additional dop on top of each account; this is the location of each sales representative (Figure 6.58).

Figure 6.58: Users Layer

As usual, we can improve upon this. First, change the kind of mark for the User Location field from Automatic to Shape, as shown in Figure 6.59:

Figure 6.59: Change mark type to shape

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

Posted on 04/03/202408/22/2024 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:

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

Figure 6.24: Drag Stage Name to Rows

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

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:

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

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

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

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

Figure 6.32: Color Stages

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

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

Figure 6.34: Select label

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.

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

Figure 6.36: Share of total calculation

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

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

Figure 6.38: Remove count

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

Figure 6.39: Select bottom label

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

Figure 6.40: Align bottom labels left

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

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:

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

Figure 6.43: Open Borders menu

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

Click on the Lines icon (Figure 6.45).

Figure 6.45: Open Lines menu

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

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

Pareto charts– Dealing with Complex Visualizations, Customizations, and APIs-1

Posted on 02/06/202408/22/2024 by Mary Kimberlin

There is a rule in business (and sometimes in other areas of life) that states that 80% of consequences can be attributed to 20% of causes. It is called the Pareto rule and can be applied in a business context, too. For example, it is not uncommon for 80% of the revenues to be driven by only 20% of the accounts. Whether your business abides by this rule can be proven with a Pareto chart, which also allows you to identify the accounts driving your sales.
For this chart, we will be using the Account object joined with the Opportunity object in Salesforce, but you can also do it only with the Opportunity object.
We will start by selecting only the data we need and the opportunities that have turned into revenues. To do this:

Drag Stage into the Filters tab, as shown in Figure 6.1:

Figure 6.1: Add Stage filter for Closed Won

Select Closed Won, as can be seen in Figure 6.2:

Figure 6.2: Stage filter set to Closed Won

Click Ok.
Now it is time to start creating the chart. The steps are as follows: 1. Drag Id from the Accounts object to columns, as shown in Figure 6.3:

Figure 6.3: Drag ID to Columns

Drag Amount into the Rows, as can be seen in Figure 6.4:

Figure 6.4: Drag Amount to Rows

Click on the caret on the ID pill and select Sort, as shown in Figure 6.5:

Figure 6.5: Sort the ID field

A new menu will now appear. Follow the steps in the order below:
a. On this menu, choose to sort by field.
b. Select Descending.
c. Select Amount from Field Name.
d. Select Sum, if not already selected.
e. Close the menu.
Your chart should look similar to the one below:

Figure 6.6: Chart sorted by Amount descending

Click on the caret on the SUM(Amount) pill and select Add Table Calculation.

Figure 6.7: Add Running Total table calculation
A new menu will appear (Figure 6.8), follow the steps in the order below:

Select Running Total from the Primary Calculation Type.
Select Sum, if not already selected.
Select Specific Dimensions from the Compute Using menu; make sure Id is selected.
Tick Add Secondary calculation.
Select Percent of Total from the Secondary Calculation Type.
Select Specific Dimensions from the Compute Using menu; make sure Id is selected.
Close the menu.

Figure 6.8: Running Total and Percent of Total calculations added
Your chart should look much different, as shown in the following figure.

Figure 6.9: Cumulative chart
We will use a reference line to understand where 80% of our sales line is. To add a reference line, follow these steps:

Click on the Analytics tab next to Data, as shown in Figure 6.10:

Figure 6.10: Click on Analytics tab

Select Constant Line, as can be seen in Figure 6.11:

Figure 6.11: Select Constant Line

Drag it to the Table menu which now hovers on your chart, as shown in Figure 6.12:

Figure 6.12: Drag Constant Line to chart

Type 0.8 in the menu that opens, as seen below:

Figure 6.13: Set value to 0.8

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

Posted on 12/02/202308/22/2024 by Mary Kimberlin

To create a filled map:

Double click on the Billing State/Province field.
Drag Expected Revenue on the Colors mark.
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.

Bar-in-bar chart – Extracting Deeper Insights with Funnels, Maps, and Hybrid Visualizations

Posted on 09/06/202308/22/2024 by Mary Kimberlin

A useful case for Salesforce and Tableau is to compare sales performance across time and against a target. To showcase this, we will create a bar-in-bar chart that tracks the Expected Amount for each Opportunity Owner.
In the following example, User table has been added to the Opportunities standard connection in order to show the names, rather than the IDs of the opportunity owners. We will now proceed to build the bar-in-bar chart, using the following steps:

To start with, drag First Name to Rows, as shown in Figure 5.45:

Figure 5.45: Adding First Name to Rows shelf

Next drag SUM(Expected Amount) to Columns, as shown in Figure 5.46:

Figure 5.46: Adding Expected Revenue to Columns shelf
We want to choose only Opportunities that relate to Q1 2022 or Q1 2023. Furthermore, for Q1 2022, we only want to look at Closed Won Opportunities.
We will, therefore, use a calculated field to look only at relevant opportunities. To add the calculated field, follow these steps:

First, use one of the methods shown in the previous section to create a new calculated field. In the window that opens, we will write:
([Fiscal Year]=2023
AND
[Fiscal Quarter]=1)
OR
([Fiscal Year]=2022
AND
[Fiscal Quarter]=1
AND
[Stage]=”Closed Won”)
Then we will give it a name, say Relevant Opportunities.
Finally, we will click on OK, the final result is shown in Figure 5.47:

Figure 5.47: Creating relevant opportunities calculated field

Now that the field has been created, drag it onto the Filters card and select True from the menu that opens, then click OK, as shown in Figure 5.48:

Figure 5.48: Filtering data to relevant opportunities

Tableau will now filter all the opportunities to show only the ones that meet our criteria, as shown in Figure 5.49:

Figure 5.49: Data filtered to specified opportunities

Now drag the Fiscal Year to the Size mark, as shown in Figure 5.50:

Figure 5.50: Adding Fiscal Year to Size mark

Drag the Fiscal Year to the Color mark, as shown in Figure 5.51:

Figure 5.51: Adding Fiscal Year to Color mark

Right now, Tableau is putting the amount for 2022 after the amount for 2023, but that is not what we want for a bar-in-bar chart. To change that, click on the Analysis menu at the top of your screen, as shown in Figure 5.52:

Figure 5.52: Accessing Analysis menu

Click on Stack Marks in the menu that opens now, as shown in Figure 5.53:

Figure 5.53: Turning off Stack Marks option

Select Off, as shown in Figure 5.54:

Figure 5.54: Stack Marks set to Off

Your bar chart should look something like the chart below, as shown in Figure 5.55:

Figure 5.55: Final bar-in-bar chart

As you can see, Doroth and Charlotte’s performance this year is better than last. Everybody else, however, seems to be having a much tougher time.

Donut charts – Extracting Deeper Insights with Funnels, Maps, and Hybrid Visualizations-2

Posted on 06/12/202308/22/2024 by Mary Kimberlin

As usual we want to make it more informative. We will start by dragging our measure in the Label menu for our white pie chart, as shown in Figure 5.15:

Figure 5.15: Adding measure to label mark of main pie chart

We will repeat the same step, but for the other menu, as shown in Figure 5.16:

Figure 5.16: Adding measure to label mark of secondary pie chart

Next we will hide both axes, as they are not needed for our chart. To do so, right click on your left axis, and a menu will open, as shown in Figure 5.17:

Figure 5.17: Right clicking on vertical axis to access menu

Click on Show Header, as shown in Figure 5.18:

Figure 5.18: Selecting “Show Header” option to hide axis

To remove all unnecessary lines from the chart, click on Format at the top of your workbook and then on Lines, as shown in Figure 5.19:

Figure 5.19: Accessing Format | Lines menu

The Format Lines menu will open, as shown in Figure 5.20. Open each menu and select None. Repeat this step for the Sheet, Rows and Columns menu:

Figure 5.20: Setting line formatting to None

If you want to also remove the border lines, click on the square icon and select None, as shown in Figure 5.21, for all the menus in Sheet, Rows and Columns:

Figure 5.21: Removing chart border lines

Your donut chart should look, as shown in Figure 5.22. In the center, you can see the full amount and next to each slice, its relative amount.

Figure 5.22: Final customized donut chart

We can also change the absolute amounts into percentages. To do so, we select the menu for our colorful pie chart and click on the measure we have previously added to the Labels mark, as shown in Figure 5.23:

Figure 5.23: Selecting measure pill

Click on Add Table Calculation. A new menu will open, as shown in Figure 5.24:

Figure 5.24: Adding table calculation

In the menu that opens, select Percent of Total from the Calculation Type menu, as shown in Figure 5.25:

Figure 5.25: Setting calculation to Percent of Total

The absolute numbers have now changed into percentages, as shown in Figure 5.26:

Figure 5.26: Measure values converted to percentages

It is possible to have both percentages and absolute numbers by dragging your measure on the Label mark in the colored pie menu, as shown in Figure 5.27:

Figure 5.27: Adding second measure pill for both values

To further aid comprehension, we will add the dimension to the Label as well, and proceeded to format the menu as shown in Figure 5.28:

Figure 5.28: Formatting label marks
The final donut chart should look similar to the one in Figure 5.29:

Figure 5.29: Final informative donut chart

Introduction – Extracting Deeper Insights with Funnels, Maps, and Hybrid Visualizations

Posted on 03/01/202308/22/2024 by Mary Kimberlin

In this chapter, we will dive deeper into the world of Tableau visualizations, particularly focusing on intermediate-level charts and features that will help you gain valuable insights from your Salesforce data. We will explore donut charts, funnels, maps, and hybrid visualizations while also learning about filters and calculated fields. By the end of this chapter, you will be well-equipped to create more complex and informative visualizations that can provide powerful insights and help guide business decisions. So, let us get started and take your Tableau and Salesforce skills to the next level!

Structure

The chapter covers the following topics:

Introduction to deeper insights
Donut charts
Filters and calculated fields
Bar-in-bar charts
Maps

Objectives

In this chapter, we will get to know how to use different types of charts like donut charts and funnel charts. We will learn what they are good for and what their limits are. You will learn how to make donut charts that show your data clearly. We will also go over how to change your data with filters and special calculated fields to make it just right for your needs.

Next, we will cover how to put together bar-in-bar charts. These let you see two sets of data at the same time in one chart, which can give you better insights. Then, we will explore how to use Tableau’s tools to make maps with your data. This can help you see where things are happening in the world.

We will also make sure you know how to tweak these maps so people using them can interact with them easily. You will learn to create filled maps that add color to different areas based on your data. Lastly, we will look at different ways to use maps to spot trends and patterns that have to do with locations. This chapter will give you the skills to turn your data into maps and charts that tell a clear story.

Introducing intermediate visualizations

In the previous chapter, we learned to create several types of visualizations and put them together in a dashboard to help our audience understand our insights more quickly. We will now discuss some more complicated types of charts, use filters, and create calculated fields to bring our ability to gain insight from Salesforce data to the next level.

Treemaps in Tableau – Exploring Charts, Graphs, and Dashboards

Posted on 11/05/202208/22/2024 by Mary Kimberlin

The process to create treemaps in Tableau using the Show Me menu is the same as for creating pie charts. The only difference is that rather than clicking on the pie chart icon, you should click on the treemaps icon as shown in Figure 4.38:

Figure 4.38: Creating treemaps in Tableau is just like creating pie charts, but with a treemaps icon

In this case, rather than using Expected Amount, we will be using Amount. Following the same steps as before, this is the final chart, as shown in Figure 4.39:

Figure 4.39: Final chart showing the usage of “Amount” instead of “Expected Amount”

Just as before, we will change from the total amount to the average amount and add more information to the chart to benefit the reader. The final result is shown in Figure 4.40:

Figure 4.40: Chart displaying total and average amounts, enhanced with additional information

Just as in the previous case, it would seem that average amount is the same, but some sources generate more opportunities.

Scatterplots in Tableau

Looking at Opportunities Source gave us some insights, but we want to understand more about where our revenues are coming from, so we will look at Lead Source instead and compare expected revenues with nominal revenues in a scatter plot.

To create a scatter plot in Tableau, start by dragging one of your measures to Rows as shown in Figure 4.41:

Figure 4.41: Scatter plot creation in Tableau: Dragging a measure to Rows

Drag the other measure to Columns as shown in Figure 4.42:

Figure 4.42: Drag the measure to Columns

Drag the dimension used to breaking down your measures to Detail. In this case, we want to compare revenues by Lead Source, so Lead Source is the field we will add to Detail as shown in Figure 4.43:

Figure 4.43: Breaking down measures by Lead Source in a dimension drag

You now have your scatterplot as shown in Figure 4.44:

Figure 4.44: Visualization of the scatterplot

Just as before, to better aid comprehension, the chart can be customized. To add the name of the lead source to the chart, drag Lead Source to the Label mark as shown in Figure 4.45:

Figure 4.45: Adding lead source to the chart for better comprehension

To further differentiate, drag Lead Source to the Color mark. Each circle now has a different color as shown in Figure 4.46:

Figure 4.46: Differentiating lead sources by dragging to the mark, resulting in varying circle colors

It is also possible to choose which shape to display in the chart. To do so, click on the Shape mark. You will now see a selection of shapes from which you can choose your favorite as shown in the Figure 4.47:

Figure 4.47: Choosing a shape for the chart

Here, we chose to replace circles with dots as shown in Figure 4.48:

Figure 4.48: Circular shapes transformed into dots

When comparing totals, unsurprisingly, there is a strong positive correlation between expected revenues and nominal revenues, so the higher the amount in our pipeline, the higher the amount we expect to convert into actual revenues. We can further confirm this by adding a trend line to the chart. To add a trend line, click on the Analysis menu as shown in Figure 4.49:

Figure 4.49: Analysis menu

Hover on Trend Lines as shown in Figure 4.50:

Figure 4.50: Visualizing trends

Click on Show Trend Lines as shown in Figure 4.51:

Figure 4.51: Analyzing trends with the click of a button

This is not the full story though, so we will now compare the average expected amount with the average nominal amount. Following the same steps as before, including the customization, the final chart can be seen in Figure 4.52:

Figure 4.52: Comparing average expected and nominal amounts

Comparing these two charts reveals that some sources bring in higher quality opportunities than others. For example, the two sources that bring in the largest amounts of opportunities, tell a different story when comparing averages. Trade shows bring in more opportunities which are also more likely to realize as concrete revenues. However, opportunities brought in via employee referrals, while many, are less likely to close than they should be. Finally, opportunities brought in via Public Relations are fewer and less likely to close, so we may want to review our strategy there.

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

Posted on 04/23/202208/22/2024 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.