Thresholds and Alerts

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From the course by University of California, Davis

Creating Dashboards and Storytelling with Tableau

278 ratings

University of California, Davis

Creating Dashboards and Storytelling with Tableau

278 ratings

Course 4 of 5 in the Specialization Data Visualization with Tableau

Leveraging the visualizations you created in the previous course, Visual Analytics with Tableau, you will create dashboards that help you identify the story within your data, and you will discover how to use Storypoints to create a powerful story to leave a lasting impression with your audience. You will balance the goals of your stakeholders with the needs of your end-users, and be able to structure and organize your story for maximum impact. Throughout the course you will apply more advanced functions within Tableau, such as hierarchies, actions and parameters to guide user interactions. For your final project, you will create a compelling narrative to be delivered in a meeting, as a static report, or in an interactive display online.

From the lesson

Key Metrics, Indicators, and Decision Triggers

Welcome to Module 2. In this module, you will identify the key metrics that will provide the answers to your business question. You will develop an understanding of the types of ways KPIs can be visualized. You will create calculated fields for KPIs to build a figure that will be used to measure progress in the data. By the end of this module, you should be able to set thresholds and create alerts to trigger a decision. We will also discuss the topic of quality and constraints of the data.

Introduction to Key Metrics, Indicators, and Decision Triggers0:50

Key Performance Indicators (KPIs)6:59

Tableau Calculated Fields and KPIs4:11

Creating Complex KPIs Using Tableau15:47

Thresholds and Alerts6:26

Data Quality18:16

Meet the Instructors

Govind Acharya
Principal Analyst
Budget and Institutional Analysis
Hunter Whitney
Sr. Consultant, Author, Instructor
Design Strategy and Data Visualization

[MUSIC]

Welcome back.

In the last lesson, we calculated some KPIs, or key performance indicators.

In this lesson, we will discuss thresholds and alerts associated with KPIs.

Being alerted that a threshold has been crossed tells you that you need to

take a look at what's going on.

After this lesson, you will be able to explain how to use Tableau to set

thresholds to alert you to areas of concern related to your KPIs.

So let's get started.

[MUSIC]

In the last lesson, we calculated some KPIs, or key performance indicators.

A KPI alerts us if something is of concern.

It's done by setting thresholds.

And these thresholds are things that you set based on criteria that

were used to set up the KPI.

So for example,

you see from our last couple of lessons where we developed these KPIs.

Here's one where it basically sets a threshold that we

determine in terms of how we can, whether or

not a particular area is meeting the benchmark or not.

So that's exactly what a KPI does.

We set the threshold based on some strategic need.

And if there's an issue, we get alerted to it.

So there's one type of Tableau specific terminology around thresholds and

alerts, which we cannot do in this course.

And that are the ones that are based around Tableau server's exciting and

really cool capability of emailing specific

people that will alert them when specific thresholds are breached within a KPI.

It sends them an alert and then the person who gets

the email can then go onto Tableau and see what the issue is.

So for this lesson, I'm going to generalize the definition to one that

assumes that the audience of the visual will be viewing the KPI regularly.

So we will not be sending an email.

But the audience member will log on and see the information on a regular basis.

The key about KPIs is that it should be as real-time as possible, and

I want to stress as possible.

That means that there should be either a connection to data that are refreshed on

a regular basis or some other way of refreshing

it in a fairly straightforward way.

In other words, the data should or could be from an ODBC connection of some sort.

It could be hosted on a Tableau server, if you're really lucky, or

it could be an Excel spreadsheet that is manually updated.

And the latter is not terrible if it's not a big burden.

Regardless of the approach, if it's not

regularly updated, it's not really a KPI.

And by regular updates, I don't mean every minute, or every day,

or even every week, it means that the audience knows that when they see

the information on the screen, it's as fresh as it possibly could be.

So I want to go back to something I showed you in Course 2, which is a control chart.

In that example, we designed a kind of a KPI,

although I didn't call it that at the time because I wanted to talk about KPIs later.

That type of control chart is going to likely be instantaneous.

Because oftentimes, control charts are used in manufacturing environments

to ensure that there is quality control over something that's produced.

So a widget is produced in an assembly line.

If an issue crops up, you want to know as quickly as possible whether or

not there's a defect in that widget, so that it could be taken out and

gotten rid of in some way.

If it isn't instantaneous, it's kind of useless.

Now again, the key to it being a KPI is what I discussed when defining it at

the beginning of the course.

It is important, it is measurable, and what it measures is some sort of

performance marker, like profit, reliability, or other attribute.

A KPI will also have a pre-attentive attribute of some sort that would quickly

alert someone of an issue.

Now again, Tableau server allows you to email, we don't have to have a server for

this course.

So let's go back to the control chart.

As you learned how to do, we created a parameter that will allow us to see

how well we're doing within a set number of standard deviations.

If it's outside of that standard deviation, then it might be a problem.

The threshold is the standard deviation line, and

the alert is the change in color that occurs when it's outside of the line.

And the other example, which I just showed you, comes from the KPI, a very simple

KPI, but useful KPI that we created, with the sales super store data set earlier.

This is, again, it tells us everything we need to know about sales by region and

what's not hitting their benchmark.

It tells you nothing else.

And that's the idea of a KPI.

All it does is alert you that you have

passed a threshold that you need to be concerned about.

Then you can dig into the data and see if it's an issue or maybe it's not.

In the next couple of lessons, I'll be creating new visualizations with KPIs

using alerts and thresholds, and then we'll get them into dashboards.

So just head to the next lesson right now.

And we're going to be taking care of that.

And we'll be getting a nice cohesive story at the end of the course.

See you then, bye.

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