12. Comments and Containers

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In this lesson, you will learn how to properly label and annotate your work, minimizing errors and facilitating collaboration.



  • The Annotation icon in the configuration window allows users to rename individual tools


  • The Comment tool allows users to place free text on the canvas


  • A Container can be used to package workflows or portions of a workflow to organize the canvas


In the previous lesson, we discussed some of the key steps user should perform when connecting to a new data set, in order to minimise potential for error and prepare your data for onward analysis.

Now we're going to learn how to make our workflow easier to understand before sharing it with other people.

We can do this with a labeling, comment, and container options.

As your Alteryx workflows get more involved, the importance of labeling and segregation becomes apparent.

In this lesson, we're going to discuss some of the best practices with respect to workflow design.

We'll continue with our workflow from the filters and summarize lesson and start with the labeling options.

We'll click on the input data icon at the beginning of the workflow, and navigate to the configuration window.

On the left side, there are 4 small icons in the margin.

So far, we've focussed on the first choice.

Configuration symbolized by the ranch.

The second icon in the list of compass arrow in a circle brings you to the navigation tab.

This window shows you the name of any data connected to the current tool selected.

The third icon, a baggage label brings up the annotation choices which we can use to name each stage of the workflow.

We'll use it now to name this stage from a data set so others users know the data set that is connected to the input tool.

In the annotation window below, we'll write Pharma data set.

This will put the label beneath the icon.

If we would rather this label appear above the icon, we can tick the box place annotation on the top.

If we decide against labels, we can just leave the annotation box blank.

We'll now work our way through the entire workbook ensuring everything is easy for our colleagues to understand.

We'll label the select icon, select relevant fields, the record ID icon, apply unique ID, the filter icon, filter sales greater than or equal to 50 and the summarize icon, sales greater than or equal to 50.

Now that we have properly labeled each of our stages, we can finesse the workflow further using the comment tool.

From the documentation tab on the tools palette, we'll bring down the comment icon.

This tool allows us to place a free text on the canvas similar to PowerPoint.

We'll use it to add a source reference.

Reference Kubicle.

Finally, what if we are planning to add multiple workflows to this canvas? Operating on such a crowded space could get confusing especially if we are sharing our file with colleagues. To bring order to such a situation, Alteryx gives us the option of packaging workflows into a container.

It might be difficult to visualise exactly what this looks like, so we'll run a quick example.

To place the workflow inside a container we'll highlight all the icons on the canvas and then right click.

We'll select add to new container.

We'll navigate to the configuration window and name this container sales by product.

On the canvas, we can see that there's an arrow on the top right of the container.

This allows us to minimize and expand the workflow.

This is especially helpful when combining a number of different workflows into a larger piece of work.

Moving back to the configuration window, notice that there is a toggle called disabled.

This has the option of turning your workflow on or off within the container.

When working with multiple workflows on one canvas, it can be very useful to turn off one or more containers.

This will allow us to only run relevant workflows saving both time and computing resources.

Consistent use of labeling options and containers are essential to building a user friendly workflow.

Not only will these tools make workflows easier to share with colleagues but as we saw with containers, they can make your analysis more process and time efficient.

Over the previous number of lessons, we have learnt how to import and organize data as well some basic data manipulation techniques.

In the next course, we'll build on what we've learnt and look at how Alteryx can help users merge multiple data sets.

Getting Started in Alteryx


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